Nr4en2022

A JOURNAL OF MINING AND ENVIRONMENT

Vol. 28 Issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590

Editor in chief: Prof. Ilie ONICA

AJOURNALOF MININGAND ENVIRONMENT

Managing editors: Assoc.prof. Andrei ANDRAS Assoc.prof. Paul Dacian MARIAN

Editorial advisory board: Prof. Dumitru FODOR Prof. Nicolae ILIAŞ Prof. Mircea GEORGESCU Prof. Pascu Mihai COLOJA

Language editor: Lect. Lavinia HULEA

Technical editor: Radu ION

Scientific committee:

Prof. Iosif ANDRAȘ, University of Petrosani, Romania PhD. Eng. Marwan AL HEIB, Ecole des mines de Nancy, INERIS, France Assist. prof. Adam BAJCAR, Poltegor-Instytut, Poland PhD. Eng. Iosif Horia BENDEA, Politechnico di Torino, Italy Assoc. prof. Boyko BEROV, Bulgarian Academy of Sciences, Bulgaria Prof. Essaid BILAL, Centre Sciences des Processus Industriels et Naturels (SPIN), France Prof. Lucian BOLUNDUȚ, University of Petrosani, Romania Prof. Ioan BUD, Technical University of Cluj-Napoca (North Center of Baia Mare), Romania Prof. Nam BUI, Hanoi University of Science and Technology, Vietnam PhD. Eng. Constantin Sorin BURIAN, INSEMEX Petrosani, Romania Prof. Eugen COZMA, University of Petrosani, Romania PhD. Eng. György DEÁK, National Institute for Research and Development in Environmental Protection Prof. Nicolae DIMA, University of Petrosani, Romania Prof. Carsten DREBENSTEDT, TU Bergakademie Freiberg, Germany Prof. Ioan DUMITRESCU, University of Petrosani, Romania PhD. Eng. George-Artur GĂMAN, INSEMEX Petrosani, Romania Prof. Ioan GÂF-DEAC, Dimitrie Cantemir Christian University Bucharest, Romania Ph.D. Eng. Edmond GOSKOLLI, National Agency of Natural Resources, Albania Prof. Andreea IONICĂ, University of Petrosani, Romania Prof. Sair KAHRAMAN, Hacettepe University, Turkey Prof. Sanda KRAUSZ, University of Petrosani, Romania Prof. Krzysztof KOTWICA, AGH University of Science and Technology Krakow, Poland Prof. Maria LAZAR, University of Petrosani, Romania Prof. Monica LEBA, University of Petrosani, Romania Prof. Roland MORARU, University of Petrosani, Romania PhD. Eng. Vlad Mihai PĂSCULESCU, INSEMEX Petrosani, Romania Prof. Sorin Mihai RADU, University of Petrosani, Romania Prof. Ilie ROTUNJANU, University of Petrosani, Romania Prof. Mihaela TODERAȘ, University of Petrosani, Romania Assoc. prof. Sorin Silviu UDUBAȘA, University of Bucharest, Romania Prof. Ioel VEREȘ, Technical University of Cluj-Napoca, Romania Assoc. prof. Zoltan Istvan VIRÁG, University of Miskolc, Hungary Prof. Florin Dumitru POPESCU, University of Petrosani, Romania

Editorialcontact: IlieONICA,e-mail:onicai2004@yahoo.com,phone:0040729066723 Dacian-PaulMARIAN,e-mail:dacianmarian@upet.ro,phone:0040748130633 UniversityofPetroşani,20Universităţiistr.,332006Petroşani,Romania Phone+40254/542.580,fax.+40254/543.491

CONTENTS

Liliana ROMAN, Mircea GEORGESCU

Research on the quality of the soil and the land related to the mining perimeters in Valea Jiului 1

Vasile BOBEI, Daniela CIOLEA

Studies on lignite quality depending on storage conditions 14

George Ionuț Răzvan FAZACAȘ

The influence of the exploitation of mineral deposits and useful rocks on the environmental components analyzed in Sălaj County 24

Dacian-Paul MARIAN, Ilie ONICA

Exploitation of the polymetallic Antonio ore body, from Băița Plai Mine 33

Dacian-Paul MARIAN, Ilie ONICA, Ovidiu MARINA

Analysis of the influence of the vertical coaxiality of the pillars on the stability of the resistance structures, from the Ocnele Mari Saline 42

Klaus-Gerhart FISSGUS, Nelu ȘTEFAN

Monitoring of the deposit displacements and the settlement behavior in Simionești Village location, Cordun Commune, Neamţ County 51

Victor Gabriel VASILESCU, Roland Iosif MORARU

Conceptualization and quantitative assessment of risk associated with explosives 58

Victor Gabriel VASILESCU, Roland Iosif MORARU

Analytical tool for modeling the dispersion of material fragments generated by explosives blasting 70

Revista Minelor – Mining Revue

ISSN-L 1220-2053 / ISSN 2247-8590 vol. 28, issue 4 / 2022, pp. 1-13

RESEARCH ON THE QUALITY OF THE SOIL AND THE LAND RELATED TO THE MINING PERIMETERS IN VALEA JIULUI

Liliana ROMAN 1, Mircea GEORGESCU2 *

1 University of Petroșani, Petroșani, Romania, lilianaaprilie40@yahoo.com

2 University of Petroșani, Petroșani, Romania, mirgeorgescu@yahoo.com

DOI: 10.2478/minrv-2022-0025

Abstract: In the paper, special attention is paid to the sources that lead to soil and land degradation in Valea Jiului, as these are the components of the environment that are most affected by mining activities. Three sources of pollution are analyzed: dumps, mine yards and constructions, and mining and preparation activities chemically polluting of soil. Among the environmental changes, land degradation currently has the most important consequences for human settlements and economic activities, especially through induced subsidence processes and the presence of dumps with reduced stability. The authors of the article propose their own method for establishing a Global Land Degradation Index (GLDI) affected by mining activities in a mining perimeter (mine) taking into account the entire analyzed area (in our case Valea Jiului) and make a classification (in three classes) of this index.

Keywords: soil and land degradation, global land degradation index

1. Introduction

In a region, such as Valea Jiului, where the coal mining and preparation activity has been carried out for an appreciable period of time, special attention must also be paid to the sources that lead to soil and land degradation in that region, because these are the components of the environment that are most affected by mining activities.

In the following, an analysis will be made of the following sources of pollution:

• dumps;

• mine yards and constructions;

• mining and preparation activities that pollute the soil chemically.

2. Dumps

The underground mining activity has unwanted repercussions on the land surface by the fact that it involves the storage of relatively large amounts of mine tailings that contribute to changes in the morphology of the land, land uses and lead to the appearance of new forms of relief. Although compared to the area corresponding to the economic area of Valea Jiului (103,200ha), mining dumps, preparations, slag deposits and abandoned quarries occupy relatively small areas (402.02ha, 0.39%) the contrast between waste rock deposits (clays, marls, sandstones) and the surrounding areas, covered by forests, is an obvious one.

The economic units (predominantly the mining ones), which affected the land in Valea Jiului to the greatest extent (mines and preparations, the Paroșeni thermal power plant, forestry and household activities) and which generated/generate degraded lands of various types, are reproduced in table 1 [1,2].

Mining dumps in Valea Jiului are usually located on slopes or along valleys, with or without drainage. The elevations of the storage lands generally vary between 650m in the axis of the valleys and 750m on the slopes. The angle of inclination of the slopes varies between 60 and 350. In some situations, the dumps were built in such a way that they block valleys without permanent water courses, forming lakes from waters originating from precipitation (fig.1).

* Corresponding author: Mircea Georgescu, Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania mirgeorgescu@gmail.com)

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022

ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

The presence of these lakes is extremely unfavorable from the point of view of the stability of the dumps. The water that seeps into the dump can cause landslides or plastic or muddy flows (such landslides and muddy flows affecting the colony of Lupeni Municipality) (fig. 2).

Table 1. The economic units that affected the land in Valea Jiului - updated [3]

Economic unit Name of objective Area, ha Surface area of influence, ha Technical condition Stability Dumps resulting from tailings extracted from underground and from the surface

Jieț Shaft 5,70 0,40 Activate Relatively stable Lonea I 14,90 0,38 Conservative Stable Defor Valley 2,00 0,40 Conservative Relatively stable Defor open pit 12,65 1,05 Conservative Relatively stable Valley of Ciort 7,19 1,11 Conservative Relatively stable Valley Arsului 2,10 2,50 Conservative Stable Petrila mine 2 East 2,10 0,30 Rehabilitated Stable

Lonea mine

South Petrila mine Jieț West open pit 14,75 1,50 Rehabilitated Stable Shaft 4 3,12 0,20 Rehabilitated Stable Auxiliary Shaft 2, 3 2,50 0,20 Rehabilitated Stable

Dâlja mine PA-1 1,74 0,10 Rehabilitated Stable Run 1,74 0,10 Rehabilitated Stable PA-1, PA-2 7,90 4,80 Rehabilitated Stable Refuse heap PA-3 1,20 0,20 Rehabilitated Stable

Livezeni mine Auxiliary Shaft East 1,55 0,30 Activate Relatively stable PA-nr.2,3 Maleia 2,15 0,70 Rehabilitated Relatively stable Aninoasa mine Refuse heap Piscu 2,50 3,42 Rehabilitated Relatively stable South Funicular 2,73 0,34 Rehabilitated Stable

Vulcan mine Shaft 7 West (old) 9,10 7,60 Conservative Relatively stable ValleyArsului + P8,10 15,75 1,60 Activate Relatively stable Hypollit 3,10 0,30 Conservative Relatively stable Shaft7West 6,30 0,80 Conservative Relatively stable

Paroșeni mine

Lupeni mine

Bărbăteni mine

Valley Lupului 2,80 0,50 Conservative Relatively stable Funicular 1,17 0,40 Conservative Relatively stable Refuse heap 1,37 - Conservative Relatively stable

2 West Ileana 14,26 0,04 Activate Relatively stable New branch Ileana 4,61 2,12 Rehabilitated Relatively stable Victoria open pit 2,48 0,02 Conservative Stable New Victoria 6,69 2,62 Conservative Stable

Mierleaşu 4,70 0,30 Rehabilitated Stable Adit 0,20 - Rehabilitated Stable

Uricani mine Old Funicular 11,00 3,00 Conservation Stable Balomir 2,18 0,60 Conservation Stable Shaft7Sterminos 3,12 0,60 Conservation Relatively stable New Funicular 2,00 3,00 Conservation Relatively stable

Valea de Brazi mine Funicular 0,15 0,30 Rehabilitated Stable Shaft 8 0,04 0,01 Rehabilitated Stable

Câmpu lui Neag mine

Poiana Mare 9,60 - Rehabilitated Stable Galbena 1,10 - Rehabilitated Stable Șesul Șerbanilor 8,60 - Rehabilitated Stable Frasin 6,80 - Rehabilitated Stable

Sum 207,84 (45,17%) 42,11

Dumps from coal preparation plants

Preparation plants Petrila 25,50 4,00 Conservation Relatively stable Livezeni 2,50 0,70 Activate Stable Coroiești 16,50 - Activate Relatively stable Lupeni 22,10 2,00 Conservation Relatively stable Uricani 0,10 - Conservation Relatively stable

Total 66,70 (14,50%) 6,70

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022

ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

Waste dumps

Petroșani 1,00 2,00 Activate Unstable Petrila 2,00 4,00 Activate Unstable Vulcan 1,50 3,00 Activate Unstable Lupeni 0,50 2,00 Activate Unstable Uricani 2,00 4,00 Activate Unstable Aninoasa 0,50 1,00 Activate Unstable Sum 7,50 (1,63%) 16,00

Pot holes and ravines

Petroșani forestry 5,00 1,00 Conservation Unstable Petrila forestry 7,00 1,50 Conservation Unstable Lupeni forestry 9,50 2,00 Conservation Unstable Sum 21,50 (4,67%) 4,50

Slag and ash deposits from the power plant Power plant Paroșeni 20,00 - Activate Stable Sum 20,00 (4,35%) -

Abandoned coal pits

Cimpa open pit 9,30 0,75 Rehabilitated Stable Jieț Defor open pit 12,56 1,05 Rehabilitated Stable Jieț Vest open pit 6,41 0,50 Rehabilitated Stable Victoria Lupeni open pit 12,50 1,10 Rehabilitated Stable Uricani Sud open pit 4,37 0,30 Rehabilitated Stable Balomir open pit 5,25 0,60 Rehabilitated Stable Vineri open pit 0,87 0,10 Rehabilitated Stable Mîrșăveni open pit 2,50 - Rehabilitated Stable Câmpu lui Neag Zona E open pit 16,50 1,00 Rehabilitated Stable Câmpu lui Neag Zona A+C open pit 29,40 2,00 Rehabilitated Stable Galbena open pit 4,37 0,65 Rehabilitated Stable Jiri open pit 2,50 0,10 Rehabilitated Stable Buta open pit 0,95 - Rehabilitated Stable Sum 107,48 (23,36%) 8,150

Land ruptures and gaps

Petroșani 5,50 - Activate Relatively stable Petrila 4,30 - Activate Relatively stable Lupeni 15,30 - Activate Relatively stable Aninoasa 4,00 - Activate Relatively stable Sum 29,10 (6,32%) -

Sum total 460,12 77,46 a b c

Figure 1.

Water accumulations in the area of Lupeni dumps (a), Valley Arsului-Lonea (b) and between the branches of the Petrila preparation dump (c) [4,5]

The construction of tailing dumps was carried out with the help of funiculars or car transport (e.g. the Valley Arsului dump), thus ensuring both the transport and storage of tailings in the dump. Deposits were carried out on different alignments, and the discharge points were established according to the configuration of the land in the area of the respective alignment. To increase the storage capacity, the spilled material is generally leveled with the help of bulldozers, forming piling platforms. The platforms have widths at the lower part of 50-150m, and at the upper part of 15-50m. By leveling with the help of bulldozers, compaction is also achieved, which contributes to increasing the stability of waste heaps.

A characteristic of the heaps is the fact that they are executed, as a rule, in one step, their parameters being dependent on the morphology of the land, the heights at which the funicular is mounted and the characteristics of the heaped rocks.

The mentioned aspects have unfavorable repercussions on the stability of the dumps, affecting the lands in the immediate vicinity, in the area of influence. The height of the dumps varies between 3-4m and 30-40m. The slope angle in the situations where plastic leaks have occurred has values of 70-80, but in general it is 400500. During the dumping or pushing of the waste material, a granulometric sorting takes place in the sense that the coarse material is deposited at the base of the pile, also, there is a tendency for the material to settle at angles greater than the final ones. In the case of land with a high slope, the flattening of the slope is more obvious and the material requires more room for expansion.

Dumps are generally stable, and the stability reserve is above unitary. Relatively stable are those that have a small reserve of stability that can be canceled in the event of additional efforts or changes in the physicalmechanical characteristics of the piled rocks or the base ground due to the presence of water.

Since the dumps are formed in a single step, due to the large difference in level the rocks tend to move from the slope, facilitating their breaking at the top where cracks and material displacements occur downstream. Because of the plasticity of the bedrock and the high height of the dump steps, crank of rocks occur in many situations.

Currently (see table 1), tailing dumps from underground and surface mining (41) are active 4 (37.26ha18%), under conservation/rehabilitation 17 (91.51ha-44%), greened 20 (79.07ha-38%), are stable 23 (115.13ha-55%) and relatively stable 18 (92.71ha-45%).

Tailings from coal preparations (5) are active 2 (19ha-28%), in conservation/rehabilitation 3 (47.7ha72%), is stable 1 (2.50ha-4%), with stability relative 4 (64.2ha-96%).

The slag and ash deposits from the Paroșeni thermal power plant (the settling ponds) are in operation. The neighboring lands are not influenced at the moment, but the breaking of the dykes would have disastrous repercussions on them, the possibly affected surfaces being appreciable and difficult to estimate (fig.3).

Figure 2. Lupeni (a) and New Uricani Funicular (b) dumps affected by erosion, landslides and uneven settlement [9].

Figure 3. The settling pond of the Paroșeni thermal power plant [5]

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

The coal open pits (micro-open pits) in Valea Jiului, in most of them, have been freed from mining duties and tailings or household waste deposits have been created. All these warehouses have been closed and greened. The former Câmpu lui Neag open pit was filled with water, being currently used for recreation and sport fishing (fig. 4).

The waste dumps are in operation, consisting of household waste (textile materials, paper, glass, wood scraps, metal, plastic materials, food scraps, ash, rubber, etc.), special waste from hospitals (cotton wool, diapers, dressings, paper, organic waste, plastics, etc.) and animal waste (animal carcasses, animal waste). All these deposits show a marked instability (fig. 5).

Figure 5. Petrila waste dump [5]

The pot holes and ravines, resulting from the location of some roads for the close removal of the woody mass, on the slope, represent approx. 5% (26ha, including potentially affected adjacent areas) of the total area of occupied and denatured land in Valea Jiului (fig. 6).

Figure 6. Forest exploitation in the Jieț valley [14]

Figure 4. Former open pit Câmpu lui Neag [4]

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

Due to the relief of Valea Jiului, most of the time the forest exploitations are located in areas with very rugged terrain where the design and location of the access roads require special caution. The construction of some roads on the slope, very close to the line of the greatest slope, on friable substrate, constituted the premise for triggering the phenomena of deep rain erosion, which had the consequence of the formation of large gullies and ravines. These formations present very steep slopes (40°60°) deep into the bedrock which in turn contribute to the formation of torrents during periods of heavy rainfall. Another consequence of the exploitation of the woody mass, especially if the replanting works are delayed, is that of triggering landslides (fig. 7), which, unfortunately, have not been quantified, and their assessment is difficult because they are located in hilly and mountainous areas. This danger should not be neglected even if such phenomena currently affect negligible areas of land in Valea Jiului.

Land ruptures and gaps are in a slow evolution affecting the original uses of land and constructions in the exposed areas and represent 7% (29.1ha) of the affected land surface.

Relatively stable and unstable formations will require mine development interventions to bring them to a stable state in order to reintroduce these lands into the economic circuit and landscape reintegration. Table 2 shows the current and initial uses of land in this category of sources of land damage in Valea Jiului.

Table

2. Affected surfaces and changes of uses

[1]

Current uses

Slag and ash deposits from the power plant (the settling ponds)

274,54 15,00 0,50 140,54 118,50

Initial uses, ha Name Area, ha Forest Arable Meadow Pasture Dumps extracted from underground, surface and coal preparation plants

20,00 - 2,00 3,00 15,00

Abandoned coal pits 94,18 10,00 0.50 72,30 11,38

Waste dumps 7,50 - - 4,50 3,00 Pot holes and ravines 21,50 21,50 - -Land ruptures and gaps 29,10 - 1,50 19,20 8,40 Sum 446,82 46,50 4,50 239,54 156,28

3. Mine yards and constructions

Depending on the necessary arrangements, the opening method, the technological flow from the surface and the relief of the land, the surface of these mine yards (fig.8) [9] can occupy from several hectares to several tens of hectares (table 3) [6].

Figure 7. Landslides in the forest exploitation area [4]

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

Figure 8. The mine yard (abandoned) of Lupeni preparation plant (Shaft with skip in the background) [4]

Table 3. Areas occupied by mining premises and constructions No. crt. Mining entity Used surface, m2 Mine yard Constructions 1. Lonea mine 999.651 559.217 2. Petrila mine 283.758 76.129 3. South Petrila mine 754.196 59.946 4. Dâlja mine 276.383 129.003 5. Livezeni mine 421.550 116.115 6. Aninoasa mine 409.772 166.308 7. Paroșeni mine 456.591 68.416 8. Vulcan mine 558.398 218.003 9. Lupeni mine 1.114.726 713.628 10. Bărbăteni mine 311.305 96.174 11. Uricani mine 410.290 149.934 12. Valea de Brazi mine 165.326 36.974 13. Câmpu lui Neag mine 120.516 52.684 14. Petrila preparation plant 1.125.757 546.483 15. Livezeni preparation plant 320.592 65.138,20 16. Coroiești preparation plant 976.908 855.603 17. Lupeni preparation plant 788.335,62 557.374,83 18. Uricani preparation plant 400.267,95 146.867,70 Sum 9.336.880,57 4.614.000,73 Sum total 13.950.881,30m2 ᵙ 1395ha; 1,35% from the surface of Valea Jiului

Other areas of land occupied by access roads, assembly platforms, warehouses, etc. it is estimated at approximately 79 ha.

The general economic regression in Valea Jiului also led to a decrease in the population so that apart from the abandoned mining premises, important areas of land are occupied by other abandoned industrial premises (e.g. the GEROM premises, UPSRUEM, buildings belonging to the former Vâscoza enterprise from Lupeni etc.) as well as abandoned residential buildings (in all cities of Valea Jiului). Although there is no strict record of these lands, an approximation of their surface between 15 and 20ha can be made.

An estimated calculation regarding the land surfaces in Valea Jiului that are/were occupied by anthropogenic activities directly or indirectly related to mining in this area shows that around 1900ha (1.84% of Valea Jiului surface) were affected by these activities, surface which, at a first estimate, would not be relevant, but as has been shown, the objectives, mostly inactive, on these lands leave a landscape and visual aspect much more significant than their extent.

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

4. Mining and preparation activities that pollute the soil chemically

The soil of Valea Jiului is siliceous, with a low content of iodine and fluorine, poor in humus and therefore unfavorable for the growth of cultivated plants. These aspects have as a consequence the orientation of the population in the area towards herding and implicitly the risk of soil and stream contamination through animal droppings or their improper storage.

The chemical composition of the soil includes all the known elements, although they differ from one region to another, the deficiencies or excess of mineral elements being reflected in the geographic pathology of the population.

In table 4, the percentage distribution of the mineral elements in the soil on the surface of some dumps and in the one that constituted their foundation before deposition (vegetable soil) is given.

Table 4. Percentage distribution of mineral elements in the soil [7] No. crt. The mineral element in the soil MU

1. SiO2

Determined value

Paroșeni Vulcan Lupeni Uricani Vegetable soil

61,87 64,92 67,11 65,23 64,23

2. Al2O3 11,22 11,81 11,86 10,98 9,81

3. Fe2O3 3,60 3,63 3,28 3,21 3,45

%

4. MgO 0,93 0,92 0,90 0,78 0,71

5. CaO 0,87 0,84 0,87 0,76 0,77

6. Na2O 0,99 1,05 1,11 0,91 1,07

7. K2O 1,58 1,63 1,70 1,45 1,80

8. Volatile 18,94 15,20 13,28 16,68 18,16

In addition to the physical degradation processes, in Valea Jiului there are also processes of chemical degradation of the land, through pollution with heavy metals (in the areas occupied by tailings deposits and in the mining premises), with sedimentable powders transported from the dumps or other pollutants (e.g. SO2). These processes affect soil fertility, recovery being in most cases impossible.

Substances that pollute the soil are organic and inorganic in nature and have negative effects on the biological activity in the soil. The possibility of soil pollution with harmful substances resulting from the mining activity is primarily related to the presence of such substances in the material stored in the dumps, which then reach the neighboring lands through precipitation.

The following will present the results of the laboratory analyses, carried out in the chemistry laboratories of the University of Petroșani and the environmental laboratory of CNH Petroșani (with the S4 Pioneer Spectrometer), of the soil samples collected both from the mining premises and the surrounding areas, as well as from tailings dumps for several years (2010-2020).

It should be noted that most of the data presented here were taken from works developed during this period [8, 9, 10], with the aim of obtaining a more accurate picture of the situation regarding the quality of the soil, from a chemical point of view, in Valea Jiului (table 5). Table 5.

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

From table 5, it can be seen that there are no exceedances of the concentrations of chemical elements (except barium, chromium and vanadium) compared to those established within the norms for less sensitive uses.

The presence of certain elements, both in the composition of the soil and in that of the waste heaps in concentrations close in value, leads to the conclusion that there is no contamination of the soil caused by the chemical composition of the waste materials stored in the heaps.

Although not directly related to mining activities, it should be remembered that there are also small areas of land polluted with petroleum products (in the vicinity of fuel depots) and transformer oils (in the vicinity of transformer stations).

5. Assessment of soil/land degradation

In Valea Jiului, soil/land pollution has multiple causes, but mining and indirect activities related to it have a significant weight.

The negative effects exerted by mining (mainly) on the soils/land in Valea Jiului are highlighted by: changes in the relief, manifested by the degradation of the landscape and displacement of households and industrial facilities from the mining areas; the occupation of some areas of land for the activity of mining, piling, coal storage, access roads etc., areas that thus become totally unusable for other purposes, for a long period of time, with effects on local communities; land degradation, through vertical and horizontal movements of the surface (induced subsidence) and the sliding of dumps and settling ponds, causing serious accidents and chemical soil pollution, which can affect its fertile properties for many years.

The land surfaces in Valea Jiului that are/were occupied by human activities, directly or indirectly related to mining in this area, are valued at approx. 1900ha, which represents 1.84% of the surface of Valea Jiului, an area which, at first estimate, would not be relevant, but as it was shown, the objectives, mostly inactive, on these lands leave a much better landscape and visual aspect significantly than their extent.

Among the different categories of soil pollution (organic, chemical and biological), the chemical one can be attributed the biggest blame (approx. 50%).

Special attention must be paid to the role of mining activities in environmental degradation through the placement of tailings, the existence of abandoned quarries and tailing ponds, and subsidence induced by underground workings.

The extent of land degradation processes through mining activities can be appreciated through a series of indicators such as: the surface occupied by quarries, tailings dumps and settling ponds, the surface affected by induced subsidence, the surface affected by soil, groundwater and vegetation pollution, the surface of land rehabilitated through greening actions or the surface of naturally grassed land.

For a quantitative assessment of the negative effects induced by mining on land, in the specialized literature there are a series of assessments of the degree of land degradation by mining activities. The work of Andrei Costache [4] is noteworthy, which proposes the determination of the Land Degradation Index through mining activities (Id.min) by calculating some degradation indices for each objective (dump, quarry, dump instability).

We propose a proprietary method for establishing a Global Land Degradation Index (GLDI) affected by mining activities in a mining perimeter (mine) taking into account the entire analyzed area (in our case Valea Jiului) [3].

This is a global index because it includes several partial indices determined for each individual objective (dump, quarry, induced subsidence, area of influence, greened area, etc.), compared because the area of each objective is related to the largest area of analyzed objectives. It is also temporary because it is determined at a given moment, it being different over time with the implementation of measures to improve the technical condition of abandoned dumps and quarries and especially with the expansion of greening works on degraded lands.

The proposed calculation relationship is:

GLDI= ∑ �������� ���� ����=1 - ∑ �������� ���� ����=1 (1) where: Ii – partial indices corresponding to the objectives that cause land degradation in a mining perimeter (mine): dumps, open pits, subsidence, areas of influence for relatively stable/unstable dumps, mine yardsconstructions etc.

Ij - partial indices corresponding to the objectives that are/were reproduced in the economic circuit: the reconstruction of the landscape as it was before the degradation, finding new uses for the land, temporary development of the affected areas etc.

Revista Minelor – Mining Revue

vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 1-13

These partial indices take values from 0 (the value of the objective surface is zero) to 1 (the value of the objective surface is the maximum from the string of values of the entire analyzed area) and are calculated with the relation:

Ii or Ij = ������������ ���������������� (2) where: Sef – the effective area of an objective in a mining perimeter (mine); Smax – the maximum area of the objective from the series of areas of these analyzed objectives in an area.

For Valea Jiului, considering the current concrete situation [11] regarding land degradation by mining and the degree of greening of these lands, it will be considered: n = 5 (dumps, open pits, subsidence, mine yardsconstructions and areas of influence) and m = 1 (naturally or anthropically greened lands).

For the calculation of this Index (GLDI), tables 1 and 3 were used, from which the necessary data were extracted, data which were centralized in tables 6 and 7

Table 6. GLDI calculation parameters

Objective name

The maximum area of an objective in Valea Jiului Smax, ha

Dumps 50,14

Open pits 53,72 Subsidence 15,30 Mine yards and constructions 317,41 Influence zones 40,97 Rehabilitation lands 205,30

Table 7. Land degradation index, GLDI

Economic unit, mine and preparation plant

Name of objective Effective area of objective, (Sef), ha

Lonea

Petrila

Petrila Sud

Dâlja

Livezeni

Partial degradation indices, Ii or Ij

Global Land Degradation Index, GLDI

Dumps 44,54 0,89 1,84 Open pits 21,86 0,41 Subsidence -Mine yards and constructions 155,90 0,49 Influence zones 6,56 0,16 Rehabilitation lands 21,86 0,11

Dumps 27,60 0,55

0,47 Open pits -Subsidence 4,30 0,28 Mine yards and constructions 203,22 0,64 Influence zones -Rehabilitation lands 205,30 1,00

Dumps 20,37 0,41 0,39 Open pits 6,41 0,12 Subsidence -Mine yards and constructions 25,67 0,08 Influence zones -Rehabilitation lands 46,04 0,22

Dumps 12,58 0,25

0,48 Open pits -Subsidence 5,50 0,36 Mine yards and constructions 40,54 0,13 Influence zones -Rehabilitation lands 53,12 0,26

Dumps 6,20 0,12 0,42 Open pits -Subsidence - -

Mine yards and constructions 92,42 0,29 Influence zones 1,00 0,02 Rehabilitation lands 2,15 0,01

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Dumps

Open pits -Subsidence 4,00 0,26

Aninoasa

Vulcan

Mine yards and constructions 57,62 0,18 Influence zones 3,42 0,08 Rehabilitation lands 62,85 0,31

5,23 0,10 0,31

Dumps 34,25 0,68

Open pits -Subsidence - -

Mine yards and constructions 77,64 0,24 Influence zones 34,25 0,84 Rehabilitation lands - -

Paroșeni + Coroiești

Lupeni

Bărbăteni

Uricani

Valea de Brazi

Câmpu lui Neag

1,76

Dumps 21,84 0,43 1,69

Open pits -Subsidence -Mine yards and constructions 235,75 0,74 Influence zones 21,84 0,53 Rehabilitation lands 1,37 0,01

Dumps 50,14 1,00 3,57

Open pits 12,50 0,23 Subsidence 15,30 1,00

Mine yards and constructions 317,41 1,00 Influence zones 40,97 1,00 Rehabilitation lands 134,78 0,66

Dumps 4,90 0,10 0,01

Open pits -Subsidence -Mine yards and constructions 40,75 0,13 Influence zones -Rehabilitation lands 45,65 0,22

Dumps 18,40 0,37 0,85 Open pits 12,99 0,24 Subsidence -Mine yards and constructions 110,75 0,35 Influence zones -Rehabilitation lands 21,87 0,11

Dumps 0,19 0,01 0,00 Open pits -Subsidence -Mine yards and constructions 20,23 0,07 Influence zones -Rehabilitation lands 20,42 0,08

Dumps 28,30 0,56 1,13 Open pits 53,72 1,00 Subsidence -Mine yards and constructions 17,32 0,05 Influence zones -Rehabilitation lands 99,34 0,48

Table 8 presents a quantitative and qualitative classification of the degree of land degradation due to mining activities, which allowed the classification of each mining perimeter (mine) in a certain category of degradation.

Table 8 Classification of land degradation according to the Degradation Index, GLDI The value of IGDT The degree of land degradation Mining perimeter (mine)

Petrila, Petrila Sud, Dâlja, Livezeni, Aninoasa, Bărbăteni, Uricani, Valea de Brazi 1,01 ≤ IGDT ≤ 2,00 medium Lonea, Vulcan, Paroșeni, Câmpu lui Neag IGDT > 2,00 large Lupeni

0 ≤ IGDT ≤ 1,00 small

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6. Conclusions

In Valea Jiului, soil / land pollution has multiple causes, but mining and indirect activities related to it have a significant weight.

The paper analyzed the negative effects exerted by mining (mainly) on the soils / lands of Valea Jiului through: changes in the relief, manifested by the degradation of the landscape and displacement of households and industrial objects from the exploitation areas; the occupation of some areas of land for the activity of mining, dumping, coal storage, access roads, etc., areas that thus become totally unusable for other purposes, for a long period of time, with effects on local communities; land degradation, through vertical and horizontal movements of the surface and the sliding of dumps and settling ponds, causing serious accidents and chemical pollution of the soil, which can affect its fertile properties for many years.

As shown, the land surfaces in Valea Jiului that are/were occupied by human activities, directly or indirectly related to mining in this area, are valued at approx. 1900ha, which represents 1.84% of the surface of Valea Jiului, an area which, at first estimate, would not be relevant, but as it was shown, the objectives, mostly inactive, on these lands leave a much better landscape and visual aspect significantly than their extent

Among the environmental changes, land degradation currently has the most important consequences for human settlements and economic activities, especially through induced subsidence processes and the presence of tailings deposits with reduced stability. The calculation of the land degradation index caused by mining activities highlighted the fact that the most affected are the mining perimeters in the center and east of Valea Jiului, respectively Vulcan, Lupeni and Lonea, which also extend into the suburbs of Petrila settlements (Lonea colony, Cimpa), Jieț, Vulcan (north), Lupeni (east and north).

In the last 10-12 years, the closure of the majority of mines in Valea Jiului and the upgrading of some major sources of pollution (e.g. the Coroiești preparation plant), have contributed to an important extent to reducing the impact of extractive activities on the environment (e.g. the significant decrease in the concentration of suspensions solids in the waters of the Jiu). However, with the development of alternative economic activities, new sources of imbalance at the local level appeared, namely tourism (through the chaotic expansion of accommodation units in the mountain area, in Straja and in Parâng) and the exploitation and primary processing of wood. These, together with agro-pastoral activities and legislative changes, lead to pollution phenomena (e.g. water pollution with wood waste and animal residues), but also to new changes in land use and vegetation. Thus, the change in the land ownership regime, grazing in the forest, uncontrolled cutting, burning of some land and pastoral pressure on the land have caused changes in the structure and composition of forests and meadows.

References

[1]. Biro C., 2005

Rehabilitation of lands degraded by anthropogenic activities in the Petroșani mining basin, PhD thesis, University of Petroșani (in Romanian)

[2]. Georgescu, M., e.a., 2002

Evaluation of the impact of environmental pollution and socio-economic life in Valea Jiului, University of Petroșani, Grant No. 1 CNCSIS code 236 (in Romanian)

[3]. Roman L., 2022

Research on the impact of the closing of the mines in Valea Jiului on the environment, PhD thesis, University of Petroșani (in Romanian)

[4]. Costache A., 2020

Vulnerability of human settlements and social risks in the Petroșani Depression, Transversal Târgoviște Publishing House (in Romanian)

[5]. Faur F., 2009

Development of an environmental monitoring system in Valea Jiului, PhD thesis, University of Petroșani (in Romanian)

[6]. *** , 2001

Post-closure monitoring of isolated underground and surface mine constructions – S.C. I.C.P.M. S.A., Petroșani (in Romanian)

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[7]. Georgescu M., e.a., 2001

Identification of pollution sources and evaluation of the degree of pollution of Valea Jiului, Grant no. 2, CNCSIS code 915, Petroșani (in Romanian)

[8]. Buliga (Nălboc) I.V., 2017 The study of the impact on the environment of the pollutants generated by the mining units in the west of Valea Jiului, PhD thesis, University of Petroșani (in Romanian)

[9]. Onica I., e.a., 2015 Works to develop production capacity at E.M. Lonea - Feasibility study - University of Petroșani (in Romanian)

[10]. Vereș I., e.a., 2019 Development plan of E.M. Livezeni and E.M. Vulcan – Funding contract 1363/2019, University of Petroșani (in Romanian)

[11]. *** , 2017-2022 Reports on the inventory and inspection of tailings dumps and settling ponds, Environmental Protection Agency, Hunedoara (in Romanian)

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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STUDIES ON LIGNITE QUALITY DEPENDING ON STORAGE CONDITIONS

Vasile BOBEI 1 , Daniela CIOLEA2 *

1 Technical University of Cluj-Napoca, Cluj-Napoca, Romania, vasile.bobei@ceoltenia.ro

2 University of Petroșani, Petroșani, Romania, danielaciolea@upet.ro

DOI: 10.2478/minrv-2022-0026

Abstract: A small increase in the relative humidity in the air in a coal deposit can cause a 1% increase in the moisture content of the deposit resulting in the probability of spontaneous ignition. By depositing the freshly extracted coal over the coal already in the deposit, there is a direct contact between the two surfaces that have different characteristics in terms of physical and chemical properties, so that the latter acts as a primer. The coal with a higher temperature gives up the excess temperature to the coal with a lower temperature, thus initiating the formation of self-heating nuclei followed by self-ignition ones. The phenomenon is easy to observe in the colder periods of the season and especially usually after rain, when the vapors resulting from the exchange of temperature between the two types of coal are released into the atmosphere. The common cause is the movement of water vapor through the deposit correlated with the adsorption on the coal granules. The heat of condensation of vapor at storage temperature is about 580 cal./gram of water. Condensing the amount of water required to increase the content from 3% of the weight of the coal to 4% leads to an increase in the temperature of the coal by more than 170C. This increase in temperature is sufficient to increase the oxidation rate by 5 times.

Keywords: coal oxidation, lignite, calorific power, the storage process

1. Introduction

Coal oxidation is an unwanted phenomenon that occurs due to the interaction of coal with atmospheric oxygen, a phenomenon that takes place during the life cycle, namely from the moment the coal is extracted until it is consumed. From an economic point of view, the oxidation of coal causes significant losses of a qualitative and quantitative nature both in the producing and consuming units, as a result of not finding the initial parameters existing in the deposit.

In order to reduce this phenomenon, it is necessary to carefully follow the behavior of the coal over time in the technological warehouses, the periodic measurement of the temperature of the stocks, the continuous monitoring of the areas predisposed to auto-ignition, the methodical recording of all the factors involved in the oxidation of the coal.

The results of research on oxidation on different types of coal carried out by specialists in the field over the years, were not quite conclusive due to the multitude and complexity of the factors involved, and the investigations, no matter how well they were carried out, well conducted and interpreted, did not were completely satisfactory.

The motivation for supporting this theory lies in the fact that regardless of our will, oxidation takes place to a greater or lesser extent in the processes of excavation-transport-storage-storage of the coal and until its consumption.

Due to the lack of general accepted and established procedures for determining the degree of coal degradation, most conclusive results on the structure and reactivity of coal presented in the literature were obtained on laboratory samples, observations that were later extended to an industrial scale.

* Corresponding author: Daniela Ciolea, Assoc.Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania danielaciolea@upet.ro, 0254542580, int. 236)

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Coals naturally contain oxygen in different proportions depending on the degree of carbonization. The content of carbon and oxygen is inversely proportional. This fact leads to the conclusion that the weight of the carbon content represents a first assessment of the change in the progressive compositional changes.

It can be considered that what changes in the degradation process is the oxygen content. Therefore, the oxygen content can be used as the main parameter for coal classification.

In a fresh, non-oxidized state, coal contains oxygen, and oxygen can be used to measure the degree of degradation. This property is rarely used for this purpose due to the difficulties of determining the degree of degradation, whatever it may be.

The oxygen content can be found by determining the oxygen by 'difference', by adding up the content of the other chemical components determined by elemental analysis and subtracting it from the total content. The 'natural' oxygen content of coal is altered by degradation. Degradation and oxidation of coal change its physical and chemical properties. The quality of the coal depends on its behavior in the processes of technological use, and alteration leads to significant qualitative and quantitative losses over time.

Observations regarding the behavior in the oxidation process of different types of coal on different samples taken in the study, can be made by following the simultaneous loss of CO2, CO, and H2O content.

It was found that even after 20 years of oxidation, coal still produces carbon oxides. The release of CO2 in these experiments was estimated to be 88% of the absorbed oxygen. Under normal conditions, CO production is between 1 and 4% of absorbed oxygen [1].

2. Coal oxidation in the storage process

In the case of studying the oxidation phenomenon in peat, no release of CO was observed. Therefore, any net increase in oxygen content is far from being accurately reproduced.

Some methods allow the comparison of freshly mined coals with older and oxidized ones. In order to expand the research, it is necessary to correct the data obtained in the two cases with the characteristics of the existing coal in the layer.

No matter how restrictive the tests used, or which are proposed, in connection with the oxidation of coal, only some of them can accurately indicate the oxidation processes. [2]

Through the phenomenon of oxidation, a series of changes occur in the natural properties of coal, namely: - reduction of calorific power;

- reduction of combustion properties;

- substantial modification of the surface of the granules; - modification of carbonization and pyrolysis properties.

The results closest to reality were obtained in the case of analyzing samples in the laboratory at medium and low temperatures, in this context, the limitation refers to the study of oxidation on different models up to a temperature of 1500C. [3]

Sometimes the data from some of the authors' studies contradict the results obtained from other works, while others completely reject these hypotheses. This temperature level may seem arbitrary, but it is primarily based on experience in the field.

These phenomena were and are being debated by specialists in the field from several countries in the world, a problem that is being approached very seriously. In our country, the concerns are in the early stages and the results are inconclusive. The main cause of this is the lack of concern as well as the wrong optics of the factors of responsibility, the motivation being the relatively high expenses caused by experimentation in the laboratory phases or in the pilot installations, although the consequences of improper storage management are much more expensive.

For the energetic lignite extracted in the mining basin of Oltenia, the problem of methodically following its behavior over time has not yet been acutely raised, given the fact that the coal's stationary period in its own deposits was in most cases relatively short, of up to 3 months so that in few cases areas of self-heating or selfigniting coal appeared.

Currently, the situation has changed radically as a result of a reduced and fluctuating demand for coal from thermal power plants, a fact that led to the increase of the coal storage period in own depots over 3 months and implicitly to the appearance of problems related to oxidation-self-heating - self-ignition.

From this point of view, there is a need to manage coal stocks from the quarries in Oltenia [4] by taking technological measures aimed at:

- reduction of coal granulation to 0÷80 mm, by installing crushers on the conveyor belt circuits from the flow to the entrance to the warehouses;

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- depositing freshly separated coal in stacks and not on top of the old one;

- compaction of stacks with technological equipment (compactor cylinders, blade bulldozers);

- measuring the temperature of coal stocks and following the oxidation, self-heating and self-ignition processes over time;

- the separation of self-heating and self-igniting coal from storage, its extinguishing and delivery to thermal power plants in the shortest possible time.

A new orientation is required in terms of coal production forecasting at month and year level, by scheduling the operation of open-pit excavators with a greater weight in relation to their operation for coal extraction. The purpose of this action is to ensure a greater flexibility of the correlated production in relation to the oscillating coal demand from the beneficiaries, through a directed storage that falls within the prescribed time limits that does not affect the quality parameters of the coal.

It is necessary that in the calculation of the cost price of coal, the additional expenses caused by the arrangement and preservation of the coal stacks from the own warehouses for a longer stationary period should be foreseen, so that the mining operations can carry out their activity profitable.

3. The auto-oxidation tendency of lignite

The main characteristics of coals that have a strong tendency to auto-oxidize and by default to auto-ignite are:

- characteristic high oxidation rate;

- high friability;

- the presence of finely divided pyrites in the coal mass.

The characteristic high oxidation rate is often a characteristic of lower coals that have a relatively high content of moisture, oxygen, volatile matter and pyrite.

It was found that the moisture from the freshly deposited coal in the stacks and the one existing in the ambient environment has multiple effects in triggering the self-ignition process. First of all, the moisture in the deposit, or the moisture of the entire mass of coal in the stack is associated with the large internal surface, especially after the coal has dried, through the release of pores and the free access of oxygen through the deposit.

Reducing the risk of spontaneous combustion can only be done based on the application of an appropriate management of coal stocks based on experience in the field.

By depositing the freshly extracted coal over the coal already in the deposit, there is a direct contact between the two surfaces that have different characteristics in terms of physical and chemical properties, so that the latter acts as a primer.

The coal with a higher temperature gives up the excess temperature to the coal with a lower temperature, thus initiating the formation of self-heating nuclei followed by self-ignition ones. The phenomenon is easy to observe in the colder periods of the season and especially usually after rain, when the vapors resulting from the exchange of temperature between the two types of coal are released into the atmosphere.

The common cause is the movement of water vapor through the deposit correlated with the adsorption on the coal granules. The heat of condensation of vapor at storage temperature is about 580 cal/gram of water. Condensing the amount of water required to increase the content from 3% of the weight of the coal to 4% leads to an increase in the temperature of the coal by more than 170C. This increase in temperature is sufficient to increase the oxidation rate by 5 times [1].

Only a small increase in the relative humidity in the air in a coal deposit can cause a 1% increase in the moisture content of the deposit resulting in the probability of spontaneous ignition.

For example, when a wet coal is stored on top of another dry coal, the heat content of the wet coal also raises the temperature of the dry coal in one part of the storage thus initiating the cycle that ends in spontaneous ignition. Fire nuclei can appear after 13 days from the storage of fresh coal over one previously deposited for about 3 months, at the separation surface between the old and the new coal. The dry coal was exposed to atmospheric humidity of 100% relative humidity, in this particular case not only the heat of condensation of water vapor is the cause, but also the heat of drying of the wet coal, so that the temperature rises in the old coal and is transmitted through conduction and convection at points in the warehouse, triggering spontaneous ignition.

Based on the above theory, the spread of fires in warehouses can be explained, caused by the evaporation of water by becoming steam as a heat transfer agent.

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Lignite during storage exfoliates until complete degradation as a result of the woody structure, due to a drying of the coal block in successive layers from the surface to the center, which causes a contraction of the superficial layers without it having occurred and in the rest of the block. The different tensions that are born in the lignite mass, as a result of the inhomogeneous contractions, lead to the crumbling of the previously dry layers.

In prolonged contact with air, the coals change their physical and chemical properties, that is, they undergo a more or less profound alteration. Alteration begins by absorbing oxygen at the surface and along the cracks in the coal. There is an oxidation on the surface of the organic matter, as well as of some mineral substances.

The practice of storing coals in the open air shows that most types of coals are degraded more if they are not sheltered than those that are covered, which leads to the conclusion that humidity favors the alteration of coals. As a result of the alteration, the coal loses its luster, its hardness decreases and it crumbles easily.

Alteration also affects other coal properties [1], as follows:

- lowers the calorific value;

- the agglutination and coking capacity decreases;

- decreases the carbon and hydrogen content;

- increases the amount of oxygen;

- increases the ash content, etc.

At the same time, iron hydroxides, sulfates and carbonates of iron and calcium are deposited on the cracks. It was found that, usually, humic coals deteriorate more easily than bituminous ones. The explanation lies in the fact that humic substances are less resistant to oxidation than bitumens. Vitrite and clarite alter easily, durite is more resistant, and fusite is more difficult to alter.

Auto-oxidation occurs as a result of low-temperature oxidation of coals. Autooxidation is always followed by autoheating, which has a relatively long duration [3]. When the critical temperature (400÷6000C) is reached, the actual combustion starts. It is a very complex physical-chemical process, which depends on many local geological, technical-mining factors, etc.

The intensity of oxidation, which will trigger self-ignition, is directly related to numerous factors, among which I mention:

- the amount of oxygen in the coal;

- the amount of oxygen that enters the coal mass, through absorption;

- the state of the coal surface;

- the amount of volatiles in the coal;

- release of heat to the environment.

The explanation of the occurrence of the phenomenon of oxidation and autoignition corresponds to the following causes [5]:

- the larger the contact surface of the coal, the faster the oxidation occurs. it follows, therefore, that coals in powder form or broken into small fragments self-ignite more easily;

- volatile components react with oxygen more easily, increasing the auto-ignition tendency of the respective coals;

- the state of the coal surface influences the self-ignition phenomenon by the fact that oxygen absorption does not take place if the surface is occupied with water molecules in an absorbed state; this explains why for the coals that form humic acids in a humid environment, water can favor the self-ignition phenomenon;

- coals with a higher content in oxygen and poorer in hydrogen have a greater tendency towards self-ignition; Another cause that favors auto-ignition is the phenomenon of pyrite oxidation. research has shown that a coal with 3% pyrite can raise its temperature by about 680C (when it is in a dry state) and by about 1140C, in a wet state;

- due to the activity of some bacteria, which are found in the lower coals, mixtures of CH4 and CO2 are formed, which largely contribute to the initiation of self-ignition;

- additional heating of the coals, due to solar radiation, electrical discharges, or random sources of heat, leads to a rise in the temperature of the coal in the warehouses and favors self-ignition.

From the current practice, it is found that after the execution of some repairs to the work fronts (on the coal seams in operation) and to the own warehouses in the premises, due to negligence, a series of foreign bodies remain (wood, rags soaked in oil and diesel fuel, unextinguished fires where the workers warmed up), led to the appearance of direct fires in the coal seams and in warehouses that were difficult to extinguish.

The way coal is stored in silos influences the heat accumulation process. Thus, in large stacks the heat losses in the environment are small and the risks of self-ignition increase compared to small stacks where the risk of self-ignition is reduced [5].

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4. The parameters of the oxidation reaction

In general, the qualitative deterioration of coal is due to the action of atmospheric air, humidity and the temperature of the environment. For these reasons, before studying the chemical changes in the organic structure of the oxidized coals, the parameters that could affect the course of the oxidation reactions must be taken into account.

4.1. The mechanism of the oxidation reaction and the physical structure of coal

The reaction mechanism between gaseous oxygen and coal at low temperatures is quite complex. Currently, little is known about the stages of this process.

Experimental works have shown that following the oxidation reaction, the coal gains in weight after oxidation up to 12% of the initial weight [5]. This shows that the weight of oxygen remaining in the coaloxygen complex is greater than the weight of carbon and hydrogen removed in the gaseous products.

In the experiments where fine coal samples were oxidized at constant temperatures below the ignition point (below 2000C) in most cases - half of them, the consumed oxygen remains in the coal, the other half appears in the gaseous products, CO2, CO and the water. So it can be understood that steps 2 and 4 taken together have about the same rate as step 3. While in this case step 4 is slower than step 3, their result is that the amount of small solid 'charcoal-oxygen' increases with increasing coal oxidation.

References from the literature on this subject point out that the complex is very stable. However, apparently, at least at low temperature, the oxidized coal samples can be stored for a long time in sealed containers, with no appreciable changes being detected in the analyses. This solid complex does not have a defined stoichiometric composition.

The rapid initial decrease in oxygen consumption when a fresh surface is exposed to air, suggests that the carbon-oxygen complex can be highly resistant to oxidation, and this is how the effect of the attack on the active surface of the coal is manifested, so the decrease in oxygen permittivity under the fresh surface. The carbon-oxygen complex is probably similar to that formed when coal or charcoal is exposed to oxygen and undoubtedly has something in common with the peroxides found in the oxidation of hydrocarbons and other organic materials [1].

By completely oxidizing fine coal at low temperature, a product almost completely soluble in caustic solutions results. In fact the amount of soluble material formed by low temperature oxidation is a good measure of the extent of coal oxidation [3].

These soluble materials are called ullmines, ullmic acid, humines, and humic acids, and some authors assume from their own methods of preparation that they are closely related to the original carbon-oxygen complex.

After precipitation from acid solutions, these solid suspensions consume oxygen from the air at low temperature and have an undefined composition.

When oxidized coal is heated to temperatures below the decomposition temperature of coal, or oxygen is continuously added to the reaction, the coal-oxygen complex decomposes to form carbon dioxide, carbon monoxide, and water, the components appearing in varying proportions. Sometimes other complex decomposition products are found. It has also been reported that, upon discharge at 2000C, there is a decomposition and evolution of carbon dioxide, carbon monoxide and water and the characteristic oxidation rate of coal is restored to values close to those of fresh coal.

Consequently, a stable carbon-oxygen complex is formed at 2000C. The properties of the complex can differ greatly depending on the formation conditions and the type of coal. Studies on the initial appearance of carbon dioxide when fine coal is rapidly heated in oxygen showed that for preoxidized Illinois coal, carbon dioxide first appeared at about 1250C, while for fresh coal it first appeared at about 930C [5]. Both for fresh coal and oxidized coal heated in oxygen, these results are not a good criterion for the stability of the coaloxygen complex, except for the indication that the complex is not extremely unstable at these temperatures.

Under these circumstances, coals preheated to 3000C in vacuum doubled the characteristic oxidation rate for some coals and for others it was largely unaffected.

The interaction of oxygen with coal takes place at the gas-solid interface. As a result of the colloidal nature of coal the external surface of the sphere or cube of coal of known dimensions not understanding the equality of the surface of the solid-gas interface that reacts with oxygen at low temperatures.

In other words, the coal contains pores, so that oxidation at low temperature takes place on a surface that is the sum of the external surfaces and interiors. It is little known how the value of the total surface varies with the granulation, the type of coal, etc.

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Currently, experiments are carried out using the method of obtaining isothermal adsorption at low temperature with argon. Preliminary tests indicated that the total adsorption surface of this gas is 10...1000 times greater than the external surface [1]. The factor depends on the coal type and granulation. Despite the fact that adsorption experiments indicated that a very large surface area is available for gases, oxygen does not penetrate deep into the coal.

As a result of these considerations, it seems correct to assume that ordinary oxidation is reduced as a result of the pores, but that this surface is much larger because of the pores. This total pore surface area would be expected to be greater in coals with a high level of moisture, which responds to the high oxidation rate characteristic of these coals.

The oxygen diffusion rate in these pores can affect the oxidation rate, even at low temperatures. The results show that the measured characteristic rates increase with the cubic root of the equivalent surfaces of the coal particles [5]. If there are no internal surfaces covered by cracks, pores and fissures, a direct proportional relationship is expected. At high temperatures, the oxidation rate of the internal surfaces should be reduced compared to the external surface due to the formation of oxygen diffusion in the pores. In other words, at high temperatures the oxidation rate should be expected to become proportional to the external area

First of all, coal minerals will be taken into account in order to emphasize their presence in its structure and which can have considerable influences in the oxidation process.

4.2. The minerals

Examining coal samples taken from an exploration front with the Fourier transform infrared (FTir) spectroscope, a quantitative mineralogical low temperature ash analysis (LTA) was applied. It was found that the mineral bassanite (CaSO4×1/2 H2O) can be used as an oxidation indicator. Bassanite originates from coal calcite (CaCO3) [1].

Further oxidation studies by Painter P.C., in 1984 on bituminous coal from Pennsylvania, artificially oxidized at 600C and 1400C in dry air, it was observed that the minerals are represented by a series of spectral bands of the mineral components that can overlap those of the organic phase. The spectral bands around 1040 cm-1 show breaks in various spectra. The same result was obtained from the spectra taken before and after oxidation.

Demineralization with HCl/HF favors air oxidation of coal at low temperature. Observations indicated that, under conditions similar to those of demineralization, coal oxidation occurs in the absence of acid. The role of the acid may be as a catalyst that causes the coal to oxidize at low temperatures. Through coal demineralization, pores are created in its structure, which increase the oxidation surface [1]. To examine the distribution of iron between the iron phases in the samples, Mossbauer spectroscopes were used. The spectrum was obtained at 770K and showed that the iron was generally distributed among the following minerals: pyrites, clay, szomolnokit, jarosite, goethite, lepidocrocite.

The most interesting aspect of the Mossbauer spectrum was that, with increasing oxidation, pyrite was replaced by iron oxyhydroxide. It is considered that this formation of sulfates could be an intermediate step in the oxidation of pyrite. The total content of sulfur contained in the studied coals decreases with the degree of oxidation (they are in the surface area). This is accentuated with the flow of soluble sulfates from naturally degraded coals. As a result of this study, the Mossbauer ratio of α-FeOOH relative to pyrite was proposed as a measure of oxidation.

First of all, clay tends to be hygroscopic, so it can retain water for a longer time. This water, even in dry periods, can react with the coal.

Secondly, clay minerals can react with pyrite, moisture and oxygen as follows: ( ) ( ) + + + + → + + + + 2 2 2 4 4 2 2 2 2 4 5 2 2 2 22 * 2 7 19 2 Fe SiO O H SO FeAl H O O H FeS OH O Si Al (1)

4.3. Humidity

Humidity is one of the basic parameters in the oxidation process with major influences not only on the oxidation of pyrite, but also on the organic part of the coal.

Water can play an important role in the oxidation of coal in which it induces the formation of (hydro) peroxides, initiating oxidative reactions in organic macerals. At 1500C, oxidation is slower in moist air than in dry air.

The accelerating effect of moisture on the degradation processes shows that the water comes into action with the oxygen groups on the surface of the coal.

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High humidity tends to facilitate the formation of CO2 and prevents the formation of carbon monoxide. The oxidation is also accelerated by the soluble iron salts in the coal. These can result from pyrite especially in the presence of microbes. So, any effect of moisture on the oxidation of macerals is the opposite of the oxidation of minerals (and successive chemistry), it is difficult to appreciate.

When the coal is simultaneously oxidized and dried, water vapor diffuses out through the pores, partially reducing the oxygen pressure and reducing the reaction rate. If the coal is too dry, the oxidation rate increases. Although it is difficult to extrapolate experimental results found for lower-rank coals such as bituminous coal, the evidence from Australian lignites is valid [5]. The high humidity of the coal during storage seems to 'preserve' the reactivity of the coal in the face of subsequent oxidation. The behavior was explained by invoking 2 processes:

- degradation during storage reduces the reactivity, but it is partially released by the increase induced by the moisture content;

- at low temperature, oxidation is inhibited by humidity and growth.

Other factors that could be considered in the effect of humidity is the opening of the pores of the coal structure and therefore the exposure of new areas to the reaction.

Recent evidence on the role of water in the oxidation of organic macerals from coal seems to support the idea that oxidation reactions are sensitive to water. However, it is a real difficulty to separate the possible different effects of moisture on organic mineral matter.

4.4. Dry and thermal chemistry

The drying action of the coal can affect the reactivity of the coals towards O2 and can initiate other chemical changes. The most conclusive evidence on this subject was brought by Dack S.W. in 1984 through the studies carried out. He examined the effects of varying the drying temperature (-150C to 1500C) on the free radical content.

The results of this study of a sub-bituminous coal indicated that bulk drying at 1000C produces irreversible chemical changes (even if weak), of the capacitor (acid-base) type, which occur when the coal is heated. The results show that, right around the temperature of 1000C, thermal chemical reactions take place. Carbonyl species can be lost through thermal reactions even if they were formed through oxidation. It is believed that oxygen is added to the free radical centers, and the addition of O2 is reversible [1]. The reactions occur as follows: - thermal decarbonylation/decarboxylation: COCOOHcoal COOH coal +++→ 2 2 / (2) - oxidation/decarbonylation at room temperature: COCOHcoal O OCcoal +++ → => 2 2 2 ][ ] [ (3)

- thermal oxidation (1000C): OOHOCcoal coalOcoal =>→−→+ ] [ 2 (4)

Increasing the temperature favors the formation of carboxyl groups.

4.5. Granulation and total area

As previously discussed, it has been shown that the smallest coal particles oxidize the fastest. For the smallest particles sampled in the center of the stack (hot space) the intensity decreases. The smaller particles also have a higher weak alkane content than the larger particles collected from the base of the stack.

Macropore oxidation occurs when the determined rate of the oxidation stage of coal particles is made by diffusion of oxygen through the core of the entire lump. In micropore coal oxidation, the oxidation of coal particles is 'open' and the oxidation is not diffusion limited. The oxidation of the macropores depends on the granulation.

For any coal studied, the oxidation is of mixed micro / macropore type. The depth of oxygen penetration in the coal varies between 2 and 4.5 µm and in the hottest areas even reaching 20-50 µm, if the smallest particles in the hottest areas were completely exposed to oxygenation [5]. These small particles can lose carbonyl groups after all the active sites have reacted. An untouched area remains in the smaller areas and in the larger granules.

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Studies in the field have shown that there are variations in the reaction rates with granulation. The oxidation of the smallest particles was controlled by surface reaction while the oxidation of larger particles was controlled by surface diffusion. It was observed that the reactivity of sub-bituminous coal was approximately proportional to the fifth power of the specific surface area. The varied nature of coal pores may also help to explain the apparent intensity of some analytical techniques in the oxidation of coals. One test method for surface-only or particulate coal oxidation is to compare results from surface and core analytical techniques.

4.6. The chemical reaction of oxidation

To treat the kinetics of the reactions in the oxidation process, two methods are used: - adding up a set of 'pure' 'elementary' reactions and combining them; - obtaining semi-empirical equations.

The second method is usually used, because the complexity of the coal makes it difficult to identify the specific reactive constituents. The problem posed here is valid because the relationships between some kinetic data derived for coal are not well known.

Coal oxidation is not a single reaction but a group of reactions sometimes competing with each other. Moreover, given the heterogeneity of the coal, the defects between the data are not a surprise, as is the finding of the domains, the activation energies of 'oxidation' [1].

The oxidation reactions of coal are controlled by one of the following rates: - external mass transfer rate from the interior to the solid surface; - rate of gaseous diffusion in coal; - the intrinsic rate of the chemical reaction.

Constitutive reactions include: - reaction with O2 to form CO2 and CO directly; - physical adsorption of O2 on the coal surface; - chemical absorption of O2 in the coal surface; - the formation of H2O.

Activation energy estimates were obtained experimentally, concluding that the activation energy for the formation of water was very small. Some authors have studied coal oxidation as a 'single' or 'total' reaction obtaining the corresponding activation energies. It was observed that the effective activation energy decreases over time and the oxidation rate decreases faster for the samples with small grain size. These findings lead to the conclusion that the reaction rate decreases as the reaction progresses in general, the results fit the 'continuous reaction model'.

Based on the data in table 1, regarding the dependence between the heating-cooling time and the heatingcooling speed, the particularities of the coal are highlighted.

Table 1. Results of the experiments regarding the self-heating of lignite from the Roșia Quarry Temperature initial [0C] Temperature maxim [0C] The time of heating [min] Speed of heating [0C]/[min] Time of cooling [min] Speed of cooling [0C]/[min] 28 92 10,5 6,1 7,5 5,6

Figure 1. Variation of heating-cooling temperature of lignite

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5. Conclusions

The technological process of coal extraction is characterized by the monitoring and management of exploitation works based on quality parameters (total moisture, anhydrous ash, lower calorific value), the values of which are prescribed in the product standards specific to the mining basins and included in the contracts economic contracts concluded with the beneficiaries.

During the excavation-transport-storage processes, it is observed that the values of the parameters mentioned above, register larger or smaller variations compared to the reference values, depending on the internal and external technological factors.

The problems generated by the storage of the extracted production for longer periods of time (over 3 months), have major economic and technological implications resulting in the qualitative depreciation of the coal and the possibility of self-ignition phenomena.

The decrease in the calorific value of the delivered coal has as a consequence the increase in the production price/ton of lignite, by supplementing the storage-conservation expenses and implicitly leads to a decrease in the delivery price to the beneficiaries. Although this aspect is not at all negligible, the most important negative effect is the quality degradation depending on the storage time.

Knowing the phenomena that favor the oxidation of coal, requires a careful analysis of the variation of the physical and chemical properties of lignite, depending on the duration of storage and preservation. The analysis of the specific quality characteristics of each type of coal from the Roșia quarry, from the point of view of the capacity for oxidation, self-heating and self-ignition, ensures the possibility of preventing qualitative losses in time.

For this purpose, a series of laboratory determinations were carried out to establish the self-heating capacity of lignite at the Roșia quarry, which highlighted the existence of this phenomenon as well as the way the self-oxidation process unfolds.

In view of the laboratory determinations, a method was used which is based on tracking the increase in the temperature of the coal mixture with a strong oxidant (perhydrol - solution with a concentration of 20%). The samples designed for the analysis were made up of the initial laboratory ones where moisture determinations (imbibition, analysis, hygroscopic, total) and ash content during analysis and anhydrous were carried out, following the following stages: homogenization, quantitative reduction, drying, grinding, weighing.

In order for the autoxidation process between the coal granules and the perhydrol solution to be as strong as possible, coal with a grain size of 0.2 mm was used.

The amount of coal that was analyzed was 3 grams/sample, placed in a heat-resistant glass flask, being mixed with 2 ml of distilled water. After this, 9 ml of hydrogen peroxide solution with a concentration of 20% was poured, noting the temperature at the beginning of the reaction by measuring it with the help of a graduated thermometer. The temperature of the mixture of coal with perhydrol was recorded minute by minute, until the temperature of 500C was reached, and that constitutes the first heating period, characterized by a slow increase in the temperature of the mixture (phase 1 of oxidation). The higher the calorific value of the sample, the shorter the heating time, and vice versa; the lower the quality of the coal, the longer the duration of autooxidation.

After the temperature of the mixture has reached 500C, readings are taken in 10 degree increments until the maximum temperature is reached. This phenomenon manifests itself by increasing the turbulence of the mixture (coal-perhydrol) through the formation of effervescent bubbles that expand towards the upper part of the volumetric flask, in a very short time (reaction phase II). Shortly after reaching the maximum temperature, the reaction begins to decrease in intensity, registering a continuous cooling of the perhydrol-coal mixture. The temperature recording in the cooling phase of the reaction is done from the maximum value to the minimum, from 10 to 100C, until the temperature of 500C is reached. Below the temperature level of 500C, the autoxidation process is no longer representative, so the temperature drop is no longer recorded.

Based on the experiences carried out over a longer period of time, we found that in identical working conditions (initial temperature, weight, granulation), the coals behave differently, precisely because of the different characteristics (petrographic, elemental composition, etc.).

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References

[1] Bacalu I , 2003

The study of the dependence of the quality parameters of lignite on its exploitation and storage conditions. PhD Thesis.

[2] Karsner G.G., 1981

Reaction regimes in coal oxidation - AIChE Journal (United States), 27:6, Nov. https://doi.org/10.1002/aic.690270607

[3] Kaji R., 1985

Low temperature oxidation of coals: effects of pore structure and coal composition - Fuel, 64, Mar.

[4] ***, 2018

Explanatory note to Government Decision no. 664/2018 regarding the approval of some measures to achieve the safety stocks of the National Electric Power System in terms of lignite fuel

[5] ***, 2020

Report on the environmental impact assessment study for the continuation of works in the extended license perimeter of the investment objective "opening and putting into operation the Rosia de Jiu quarry, Gorj county, with a capacity of 8.0 million tons/year of lignite"

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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THE INFLUENCE OF THE EXPLOITATION OF MINERAL DEPOSITS AND USEFUL ROCKS ON THE ENVIRONMENTAL

COMPONENTS ANALYZED IN SĂLAJ

COUNTY

George Ionuț Răzvan FAZACAȘ 1 *

1 University of Petroșani, Petroșani, Romania, fazacasgir@gmail.com

DOI: 10.2478/minrv-2022-0027

Abstract: Starting from the importance of the mining industry and how it influences the environment, environmental components and human settlements, this study analysed the activity of Prodănești, Moigrad and Marca quarries, from Sălaj county and how their activity influences the environmental components, air, water and noise. The analysis focuses on the interpretation of the test reports for the years 2016-2019, imposed in the regulatory acts, by the environmental protection authority

Keywords: quarries, AM, water, air, noise, environmental impact, test reports

1. Introduction

Useful rocks are exploited in numerous quarries and gravel pits spread throughout the territory of the country, having national, regional and local importance [1], within the national economy it is necessary to capitalize on any resource especially the local ones [1].

The mining industry exerts on the environment special influences that manifest themselves in all technological phases and exploitation processes contributing to a great extent to the pollution of the natural receptors in the area [2].

Mainly, the sources of pollution regarding the exploitation of deposits in quarries are the emission of dust, particulate matter and noise that come mainly from the transport of cars and the handling of machinery and mineral aggregates, the detonation of explosives, affecting in particular the activity of personnel but also of nearby vegetation that leads to the diminosis of photosynthesis and implicitly the development of plant biomass [2].

The influence of useful mineral and rock deposits have an impact on environmental components, so it is important "to monitor, forecast, warn and intervene in order to systematically assess the dynamics of the qualitative characteristics of the environmental elements, in order to know their quality status and ecological significance, the evolution and social implications of the changes produced, followed by the necessary measures" [3].

Monitoring can be conducted for various purposes, including establishing environmental "baselines, trends and cumulative effects" [4].

In this study are analysed according to chapter III, the environmental monitoring, from AM [5], [6], [7], physico-chemical, bacteriological and biological indicators emitted, pollutant emissions, the frequency of environmental factors air, water as well as noise from the mining perimeters of Prodăneşti, Moigrad and Marca quarries.

The objects studied in Fig.1 are located partially in the inner city of the localities A) Prodănești locality, B) Moigrad locality, C) Marca locality, having as main activity the extraction of ornamental stone and stone for construction [5], [6], respectively the extraction of stone limestone, gypsum, chalk and slate.

* Corresponding author: Fazacaș George Ionuț Răzvan, PhD. Stud., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania fazacasgir@gmail.com)

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Figure 1 A) Prodănști quarry, B) Moigrad quarry, C) Marca quarry,.Salaj County

2. Materials and methods

In order to determine the sources of pollution, specific equipment was used for sampling and measuring the air, water and noise environmental factors, for the period 2016-2019, carried out by REANAR accredited laboratories, namely: for the Prodănești quarry, the test reports were made by the ICIA Cluj-Napoca laboratory [8],[9],[10],[11] for the Moigrad quarry the determinations were made by the Sălaj Environmental Protection Agency [12], [14], [16], [18], Someș-Tisa Water Basin Administration Sălaj Water Management System [13], [15], [17], and for the Marca quarry, the determinations were made by the laboratory S.C Minesa - Institute of Research and Design Minesa S.A [19], [20], [21], [22].

A. Equipment used for noise determination: - sound level meter BRUER&KJAER 2250 L; - SOLO sound level meter; - sound level meter DELTA OHM HD2010UC; - analytical balance.

B. Equipment used for the determination of suspended powders, sedimentable powders: - Zamelli sampler, ZB1; - isokinetic probe and sampling pump; - filter membrane d=0.85µm, ɸ=47 mm.

C. Equipment used, analysis of physical and chemical indicators of water quality: - sampling probe.

Sampling and analysis methods are according to STAS and current regulations. water: SR ISO 10523/97, STAS 6953-81, STAS 9187/84, SR7587/96 air: STAS 12.574/'8 noise: STAS 10.009/'88

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3. The result of the analyses

The results of the laboratory analysis for the air, water and noise environmental components are described in the tables: 1, 2, 3 and 4, it is found that there are no exceedances of the maximum allowed limits and the environmental legislation in force is respected.

Table 1 Average concentrations of suspended dust in the period 2016-2019

No. Crt. Quality Indicators M.U. Garndemar Quarry Prodănești Quarry Marca Quarry

Maximum addmited limits Stas 12574/87

mg/dm3 0.1 0.03 0.15 0.5 2 mg/dm3 0.2 0.07 0.08 0.5 3 mg/dm3 0.1 0.07 0.068 0.5 4 mg/dm3 0.4 0.09 0.1 0.5 5 mg/dm3 0.1 0.03 0.15 0.5 sedimentable powder g/m3 (30 days) 7.81 17

1 powder in suspension

Table 2 Average concentrations of water quality indicators in the period 2016-2019 No. Crt. Quality Indicators M.U. Moigrad Quarry Marca Quarry Maximum addmited limits

1 PH unit pH 7.02 7.8 6.5-8.5 2 suspended matter mg/dm3 16.2 50 60 3 fixed residue mg/dm3 118 113 2000 4 extra-attainable substances mg/dm3 8.8 <20 20

Table 3. Average noise level for the period 2016-2019 No. Crt. Analysis point M.U.

Average of measurement values LAeq Maximum addmited limits STAS 10.009/’88 Prodănești Quarry* Marca Quarry**

52.7 59.06 65 2 56.0 46.5 3 54.2 51.83 4 the southern boundary of the access perimeter to the quarry** 40.0 58.29

1 crushing activity* the main gate of the factory* boundary* dB(A)

Table 4 Average noise level for the Moigrad quarry period 2016-2019

No. Crt.

Maximum addmited limits STAS 10.009/’88 1 to the north towards the dwelling houses dB(A) 58.4 65 2 to east at career entry, treadmill 59.7 3 to south of entry into the quarry 63.6 4 to the west stage of the exploitation quarry 57.6

Analysis point M.U. Average of measurement values Laeq

4. Environmental impact assessment for the Prodăneşti, Moigrad and Marca quarries

4.1 Matrix environmental impact assessment for the environmental factors air, water and noise

In order to report the environmental components affected by the quarrying activity, the MERI (Rapid Impact Assessment Matrix) method was applied [23]. The MERI method is based on a standard definition of the important evaluation criteria and the means by which quasi-quantitative values can be deduced for each of these criteria Table 5 [23]

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The calculation procedure for MERI assumes the following equations:

����1 × ����2 = �������� ����1 + ����2 + ����3 = �������� (1) �������� × �������� = �������� where: A1, A2, B1, B2, B3 – evaluation criteria by the MERI method At, Bt – marks obtained by multiplying, respectively, adding the values of the evaluation criteria SM - average score for the analyzed factor

The established standard evaluation criteria fall into two broad types: A – criteria that can individually change the environmental score obtained B – criteria that individually cannot change the average score

Table 5 Evaluation criteria and stages by the MERI method Criterion Scale Description

A1 Importance of environmental change (effect)

A2 Magnitude of environmental change

4 Important for national/international interests 3 Important for regional / national interests 2 Important also for areas in the immediate vicinity of the site area 1 Important only for local conditions 0 Without importance

3 Important major benefit 2 Significant improvement of the actual / current state 1 Improving the current state 0 Unchanging the current state -1 Negative change of fact -2 Disadvantages or significant negative changes -3 Disadvantages or major negative changes B1 1 No changes

Residence 2 Temporary 3 Permanent B2 1 No changes

Reversibility 2 Reversible 3 Irreversible B3 1 No changes

Cumulativeness 2 Non-cumulative / unique 3 Cumulative / synergistic

After obtaining the environmental scores, they are transformed into impact categories (IC), based on the conversion scale in table 6 [23]

Table 6 Conversion of environmental scores into impact categories

Environmental score (ES) Categories (Code)

Description of the impact category (IC) + 72 → + 108 + E

Major positive impact + 36 → + 71 + D

Significant positive impact + 19 → + 35 + C

Moderate positive impact + 10 → + 18 + B Positive impact + 1 → + 9 + A

Slightly positive impact 0 N

Lack of change / status quo / Not applicable - 1 → - 9 - A

Slightly negative impact - 10 → - 18 - B Negative impact - 19 → - 35 - C

Moderate negative impact - 36 → - 71 - D Significant negative impact - 72 → - 108 - E

Major negative impact

The result of the calculation of the impact on the environmental component air, water and noise for the Prodăneşti, Moigrad and Marca quarries, evaluated by the MERI method, was carried out according to the input data and calculation formulas from Table 5, are presented in Tables 7; 8; 9 [24]

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Table 7. Evaluation by the MERI method Prodănești quarry Environment component Evaluation criteria Environmental score Categories (Code)

Description of the impact category (IC) A1 A2 B1 B2 B3

AIR 1 -1 2 3 2 -7 –A Slightly negative impact NOISE 1 -1 2 3 2 -7 –A Slightly negative impact

Table 8 Evaluation by the MERI method Moigrad quarry Environment component Evaluation criteria Environmental score Categories (Code) Description of the impact category (IC) A1 A2 B1 B2 B3

AIR 1 -1 2 3 2 -7 - A Slightly negative impact WATER 1 -1 2 3 2 -7 - A Slightly negative impact NOISE 1 -1 2 3 2 -7 - A Slightly negative impact

Table 9 Evaluation by the MERI method Marca quarry Environment component Evaluation criteria Environmental score Categories (Code) Description of the impact category (IC) A1 A2 B1 B2 B3

AIR 1 -1 2 3 1 -7 - A Slightly negative impact WATER 1 -1 2 3 1 -7 - A Slightly negative impact NOISE 1 -1 2 3 1 -7 - A Slightly negative impact

After calculating the assessment using the MERI method, it results that the exploitation activity in quarries has a slight negative impact for all environmental factors WATER, AIR and NOISE, 4.2. Assessment of the impact of the risk produced on the environmental components air, water and noise

The environmental impact and risk assessment process is an important tool in the decision-making process [25], in this case for the studied quarries Prodănești, Moigrad and Marca using a method of evaluation MERI method (Rapid Impact Assessment Matrix) [24]

In the first step, the degree of GI importance is established, for the environmental components air, water and noise in order to be able to assess the impact and the environmental risk to which it is granted on a scale from 0 to 1, where the value 1 represents the highest importance [23], then the units of importance of the UI are calculated for each environmental component example Table 10 [24]

Table 10 Calculation of the importance of each environmental component CM environmental component GIi degree of importance

Units of importance UI =1000*GIi/GI

Air 1,00 333 Water 1,00 333 Noise 1,00 333 Total GI= ∑GIi=3 GI= ∑GIi=1000

In order to assess the environmental impact and risk, it is necessary to analyse the three water, air and noise environmental components described in Table 12, where the quality of the assessed environmental component (Q) is determined as the ratio of the maximum permissible concentration (AQC), according to the legislation in force, to the concentration determined in the environment (Cdet) at a given time for a given pollutant [23]

Q = CMA/ Cdet (2) The induced impact on each assessed environmental component (IM) is given by the product between the quality of the environmental component (Q) and the units of importance (UI) obtained by each environmental component according to the relationship: [23]

IM=Q×UI (3) IM= ∑ IM/n (4) n – total number of quality indicators analysed.

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For each environmental component, an environmental risk is associated and is calculated by the relationship: RM=IM ×P (5)

P- the calculated probability that the impact will occur on the environmental component The probability of an impact on the environmental components analysed is described in Table 11 [23] and correlated with the values in Table 10

Table 11 Description of probability Probability Description Units of probability

For sure is carried out in 99% of cases 0,91-1,0 Almost certainly it could be done in 90% of cases 0,61-0,9 Probable it can happen in 50% of cases 0,31-0,6 Unlikely it happens sometimes in 10% of cases 0,05-0,3 Rar it can happen in exceptional cases,1% <0,05

Table 12 Calculation of environmental impacts and risks Environment component The objective under analysis Quality Indicators CMA1 Cdet2 Q3 UI4 IM5 P6 RM7

Moigrad quarry powder in suspension 0.5 0.2 2.5 333 832.5 0.3 249.8

Air

Prodănești quarry sedimentable powder 17 7.8 2.2 724.8 217.5 Marca quarry powder in suspension 0.5 0.1 4.5 1513.6 454.1 Induced environmental impact and risk ∑ IM/n 1023.7 307.1

Prodănești quarry

Water

Marca quarry

Noise

Prodănești quarry

PH 6.5-8.5 7.0 0.9 333

309.2 0.3

92.8 suspended matter 60 16.2 3.7 1233.3 370.0 fixed residue 2000 118 16.9 5644.1 1693.2 extra-attainable substances 20 8.8 2.3 756.8 227.0

PH 6.5-8.5 7.8 0.8 277.5 83.3 suspended matter 60 50.0 1.2 399.6 119.9 fixed residue 2000 113.0 17.7 5893.8 1768.1 Induced environmental impact and risk ∑ IM/n 2073.5 622.0

crushing activity 65

Marca quarry the southern boundary of the access perimeter to the quarry 65

Moigrad quarry

to the north towards the dwelling houses 65

52.7 1.2 333

123.2 the main gate of the factory 56.0 1.2 386.5 116.0 boundary 54.2 1.2 399.4 119.8 40.0 1.6 541.1 162.3

59.1 1.1 366.5 109.9 46.5 1.4 465.5 139.6 51.8 1.3 417.6 125.3 58.3 1.1 371.3 111.4

410.7 0.3

58.4 1.1 370.6 111.2 to east at career entry, treadmill 59.7 1.1 362.6 108.8 to south of entry into the quarry 63.6 1.0 340.3 102.1 to the west stage of the exploitation quarry 57.6 1.1 375.8 112.7

Induced environmental impact and risk ∑ IM/n 400.7 120.2

1– maximum permissible concentration under the national legislation in force, 2 – concentration determined, 3 – quality of the environmental component, depending on indicator "i" from "n" quality indicators; 4 – the unit of importance obtained by the environmental component; 5 – the environmental impact calculated according to the parameter "environmental quality", 6 – the calculated probability that the impact will occur on the environmental component; 7 – the environmental risk associated with each impact.

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Calculate simultaneously the impact as well as the associated environmental risk for each environmental component air, water and noise for the oebictives analysed after the relationship: [24]

IMmed=∑IMj /m și RMmed =∑RMj/m (6) m- number of environmental components j- analyzed

The quantification of the environmental impact and risk for each environmental component analyzed water, air and noise is classified according to the Table 12 [23]

Table 13 Classification of environmental impact and risk Environmental

impact

Description Environmental risk Description

<100 degraded environment, unsuitable for life forms <200 major risks, preventive measures are needed 100-250 environment severely affected by human activities

250-350 environment subject to the effects of activities human causing disorders of life forms 200-350 medium risks, preventive measures are needed 350-500 environment exposed to the effects of human activities causing discomfort 350-700 average risks at an acceptable level, must be monitored 500-1000 environment subject to the effects of activities human within permissible limits 700-1000 risks, but must be considered/monitored >1000 unaffected by activities human/natural quality >1000 negligible/insignificant risks

By calculating the average value for the three environmental components air, water and noise, an average impact IM=1166 is obtained, which is classified in the environment unaffected by human activities/natural quality and an average risk RM=350 is classified into average risks at an acceptable level, prevention and monitoring measures.

After calculating the IM and RM at the activities carried out at the Prodănești quarries. Moigrad and Marca draw the following conclusions regarding the environmental components air, water and noise after the classification in Table 13. - by air environment component = > an environment unaffected by human activities/natural quality - by water environment component = > an environment unaffected by human activities/natural quality - after the environmental component noise = > medium exposed to the effects of human activities causing discomfort

4.3. Remedial measures for environmental factors and the way the quarries are operated

• Maintenance of guard ditches by unclogging in order to ensure their optimal functionality.

• Slope of the berms at the fertile soil dump and tailings dump in order to prevent the appearance of ravines on their slope.

• Maintenance of the existing decanters in the quarries in order to operate at the designed parameters.

• Permanent spraying of access roads to minimize the entrainment of suspended dust.

5. Conclusions

The activity of the quarries analyzed has both local and national economic importance. Analyzing only the environmental components affected by these exploitations, namely air, water and noise using the MERI method and based on the data provided by the verified operators, resulted in a slightly negative impact for the three environmental components analyzed.

Periodic monitoring of the affected environmental components is required, as well as the implementation of the works provided for in the environmental restoration plan and the approved exploitation technology, respectively the geometric elements of the quarries (surface, slope angles, berm width).

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References

[1] Fodor D., Baican G., 2001

The impact of the mining industry on the environment, Infomin Publishing House

[2] Fodor D., 2011

Ballasts and quarries A.G.I.R. Publishing House, Deva: Corvin Publishing House

[3] ***, 2005

Emergency Ordinance no. 195 of December 22 2005 regarding environmental protection

[4] Radu M ., 2014

Integrated environmental monitoring Cluj-Napoca 2014

[5] Greek. A, Balint G., 2012

The Sălaj Environmental Protection Agency environmental authorization No. 19/2012

[6] Greek. A, Balint G., 2012

The Sălaj Environmental Protection Agency environmental authorization No. 94/2012,

[7] Greek. A, Balint G., 2012

The Sălaj Environmental Protection Agency environmental authorization No. 30/2012,

[8] ICIA Cluj-Napoca, 2016 R.I No 938/2016

[9] ICIA Cluj-Napoca, 2017 R.I No. 2423/2017,

[10] ICIA Cluj-Napoca, 2018 R.I No. 662/2018, R.I No 663/2018

[11] ICIA Cluj-Napoca, 2019 R.I. No. R 1106/2019

[12] Agency for Environmental Protection Sălaj, 2016 R.I N.R. 45/2016, R.I N.R. 137/2016, R.I N.R. 4/2016, R.I N.R. 1/RZ/2016

[13] Someș-Tisa Water Basin Administration Sălaj Water Management System, 2017 R.I N.R. 206 /2017, R.I N.R. 120 /2017,

[14] Agency for Environmental Protection Sălaj, 2017 R.I N.R. 6/2017

[15] Someș-Tisa Water Basin Administration Brackish Water Management System, 2018 R.I N.R. 93 /2018, R.I N.R. 2015 /2018,

[16] Agency for Environmental Protection Sălaj, 2018 R.I N.R. 1/RZ/2018,

[17] Someș-Tisa Water Basin Administration Sălaj Water Management System, 2019 R.I N.R. 174 /2019, R.I N.R. 81 /2019,

[18] Agency for Environmental Protection Sălaj, 2019 R.I N.R. 4 R.P/2019, R.I N.R. 1/RZ/2019,

[19] S.C. Minesa - Institute of Research and Design Minesa S.A., 2016 R.I No. M 145/.2016, No. M 151/.2016, NO. M 156/2016

[20] S.C. Minesa - Institute of Research and Design Minesa S.A., 2017 R.I No R164/2017 .I No. M 197/.2017, No. M 190/.2017, No. M 156/2017

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[21] S.C. Minesa - Institute of Research and Design Minesa S.A., 2018 R.I No. M 223/.2018, R.I No. M 225/.2018, RI No.157/2017,

[22] S.C. Minesa - Institute of Research and Design Minesa S.A., 2019 RI No. M 376/.2019, RI No. M 377/.2019 , RI No. M 154/.2019 ,

[23] Georgescu M., 2015 The impact of the mining industry on the environment Lecture I-doctorate year, Mining, Oil and Gas Field

[24] Georgescu M., 2020

Evaluation of the environmental impact and risk at the Praid salt mine pan and measures to reduce the negative effects on the environment. Mining Revue ISSN-L 1220-2053/ ISSN 2247-85920 University of Petroșani, Vol.26, No3 p19/2020, Petroșani

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

Revista Minelor – Mining Revue

ISSN-L 1220-2053 / ISSN 2247-8590 vol. 28, issue 4 / 2022, pp. 33-41

EXPLOITATION OF THE POLYMETALLIC ANTONIO ORE BODY, FROM BĂIȚA PLAI MINE

Dacian-Paul MARIAN 1 * , Ilie ONICA2

1 University of Petroșani, Petroșani, Romania, dacianmarian@upet.ro

2 University of Petroșani, Petroșani, Romania, onicai2004@yahoo.com

DOI: 10.2478/minrv-2022-0028

Abstract: The Antonio polymetallic ore body is part of the Baița Plai ore deposit. Below the XVIII horizon, it has a medium slope, a height of approx. 81 m, an average extension of 200 m and a thickness varying from 4 to 36 m. Above this horizon, the orebody was mined in horizontal slices with integral backfill and the first 9 m high sublevel with rooms and pillars. In depth, below this sublevel, 6 more sublevels with a height of 12 m are mined with sublevel caving mining method. The design of the opening, preparation and exploitation of the deposit was carried out for a production capacity of 100 k tonne/year.

Keywords: polymetallic ore, mine, underground mining, opening workings, sublevel gallery, sublevel caving mining

1. Geology of the ore deposit

The exploitation perimeter of the Baița Bihor deposit is located in the southeastern part of Bihor county, 4 km from the village of Baița, in the upper basin of the Crișul Baiței stream and is recognized as the oldest mining center in the region.

From a morphological point of view, the exploitation perimeter is located in the Bihor Mountains, in the upper hydrographic basin of Crișul Negru, on the slopes of Criș Băița, upstream approx. 2.5 km northeast of its confluence with the Valea Plaiului.

The geological structure of the Băița-Bihor deposit reflects, on a smaller scale, the structure of the Northern Apuseni mountains with the Bihor Unit at the base of the structure, with a paraautochthonous role, over which they follow each other the Codru Unit, the Arieșeni Nappe and the Highiș-Poiana Nappe [1].

The perimeter of the Baița Mine is located in an extremely complicated area from a tectonic point of view. The entire structural ensemble is part of the Northern Apuseni Mountains region. From the structural analysis of the current tectonic configuration, it is very clear that the discontinuities arose at different moments of tectonization, being rejuvenated several times following the resumption of movements.

Laramic magmatism played an important tectonic role, being accompanied by tectonic phenomena, generating rupture structures with faults showing a preferential orientation NW-SE, but also NE-SW.

The entire nappes system present in the Baița Mine area was affected by the Upper Cretaceous magmatism processes that materialized by placing a granitic/granodioritic-dioritic batholith, as well as its vein derivatives. Thus, metamosaic products were generated (calcic, magnesian, chalco-magnesian skarn). The main metasomatic columns in the Carnian dolomites are Antonio, Sturzu, Baia Roșie, Marta, Bolfu -Toni and Hoanca Moțului, often accompanied by satellite bodies (small columns, lenses, metasomatic veins).

The spatial distribution of the columns is controlled by the rift systems N60o -70°E and N50o - 60°W, the metasomatites being located along the fractures (Sturzu, Marta, Bolfu - Toni, Hoanca Moțului) or at their intersection (Antonio, Baia Roșie). The height of the columns varies between 100 and 530 m, and the thickness is limited to a few tens of meters.

* Corresponding author: Dacian-Paul Marian, Assoc.Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania dacianmarian@upet.ro)

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One of the main metasomatic bodies within the deposit is represented by the Antonio ore body. This body is located in close proximity to the fault that separates the Carnian dolomites from the Norian limestones. He has a height of approx. 200 m and a diameter of 60-80 m; the vertical position is maintained for approx. 130 m, after which it curves towards the SW, to connect to the skarn mass on the contact of the dolomites with the hornets at their base. For the Antonio body, the location at the intersection of two fracture systems (N50-60W; N60E) is extremely characteristic; this aspect is evident in its median part, between elevations 520-560 m.

2. Opening of the deposit

The basic object of the Baița Plai mine is the mining and processing of polymetallic ore. Due to the geomorphological configuration of the area, above horizon VI (approx. +576 m), the access to the mineralized structures was made through adits, and below this level the opening of the deposit was made through 3 shafts (including 2 blind ones) that serve horizons VI – XVIII, between levels +576 m and + 224 m.

In general, up to approximately the level of the XIII horizon (approx. +417.7 ÷ 422 m), all the main mineralized areas are known. Below this level, the XV - XVI horizons also open the bodies of Terezia, Baia Roșie, Pregna and to a small extent or even not at all structural Marta, Nepomuk and Bolfu.

These, basically, below the +317.4 m level are not explored, although according to the specialized literature they would have chances of expansion in depth, given the important metallogenetic potential they have.

The exploitable reserves of the Antonio ore body are located below the XVIII horizon, at a depth estimated, from geological research drilling, of a maximum of 81 m (respectively, at the lower limit of the XVIII-81 horizon). The average extension per direction of the ore body is approx. 200 m, and the horizontal thickness is variable, from 4-16 m, in the western part, to 36 m, towards the west (measured at the level of the XVIII-9 horizon). The deposit has a lower thickness, in the first two thirds from the west, which becomes maximum in the southeast area, changing its orientation from the NE, to the NW-SE, with a narrowing towards the southeast limit.

Horizon XVIII (located at +224 m above sea level) is the maximum level reached with the mine opening scheme, which requires the completion of opening and preparation mining workings to make it possible to exploit the Antonio ore body ”in eye-pit” , thus making up for the lack of the horizon XIX. Thus, during the exploitation of this ore body, horizon XVIII must function both as the main transport horizon and as a ventilation horizon, which complicates the configuration of the opening and preparation scheme.

Below the XVIII horizon, the ore body is divided into 7 sublevels: the first sublevel (related to horizon XVIII-9) has a vertical height of 9 m, and the following 6 sublevels (related to horizons XVIII-21 XVIII-81) have a height of 12 m [2, 3, 4].

The sublevel caving mining method raises a series of problems regarding the location of the mining workings, which must be kept in a good condition for a longer period of time, as are some opening or preparation workings executed in the barren roof rocks, outside the mining area of influence.

So, based on the calculation scheme of rock displacements on the sliding surface in fig.1, the condition for the location of the mining workings that must remain stable during the exploitation of a sublevel is obtained.

From fig.1 it follows that the safety limit distance of mining workings from the roof of the deposit is: ( δ) α ctg ctg h D + ⋅ = (1) where:

h is the height of a sublevel, in m (for the XVIII-9 sublevel, h=9m, and for the other sublevels, h=12m); α-average inclination of the Antonio ore body; δ - the inclination of the weakened sliding surface / the caving angle (for the conditions of the Baița Plai deposit o 70 = δ ).

Therefore: - for the first sublevel, with h = 9 m, results D9 > 13 m; - for the lower sublevels, with h = 12 m, results D12 > 16 m.

Taking into account the relative value of the angles α and δ, these safety distances, which adopted, they can grow properly.

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Figure 1. Calculation scheme for the safety distance of mine opening and preparation workings [2]

The opening of the deposit in the perimeter of the Antonio ore body can be achieved through several opening schemes, which ensure: the operation of the production process at the sublevels; transport of the mined ore to the horizon XVIII; access/transfer of loading, transport and drilling equipment to/from the faces; staff movement; introduction of materials; ventilation of underground mining workings of opening, preparation and exploitation, etc.

For the opening and preparation of the Antonio ore body, an opening scheme was approved for the entire height of the level (fig.2). In principle, this opening scheme develops over the entire level height of 81 m [2].

Figure 2. Antonio ore body opening and preparation scheme [2]

For the gravity transport of the ore, an ore chute is executed at the eastern extremity of the ore body, with an inclination of 70o -80o, with a length of 90-95 m, 8 m below the level of the XVIII-81 horizon (respectively at the -89 m level). The connection of the ore chute with the directional transport galleries, from each sublevel in operation, is made through a short cross sublevel gallery.

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The transport of the blasted ore to the XVIII horizon, starting from the XVIII-33 sublevel and ending with the XVIII-57 sublevel, is done on the belt conveyor inclined transport plane, with an inclination of 12o and a length of 274 m. The section of the inclined plane can be 7.5 m2 (with dimensions of 2.5 x 3 m), being furnished with a single rubber belt conveyor. The connection between the inclined transport plane, by means of a short 8m ore chute and the main transport ore chute (from level XVIII-49, to level XVIII -89) will be made with a new inclined plane equipped with a belt conveyor, with an inclination of 11o and a length of 210 m.

The access of the loading and transport equipment to the sublevel galleries is achieved with a spiral inclined plane, located at the western limit of the ore body, which will be excavated at least up to the level of the XVIII-33 sublevel, when the belt conveyor inclined plane will be realized.

The main disadvantage of this scheme results from not knowing the depth of the Antonio ore body. More precisely, the execution of the opening mining workings along their entire length is risky because, with the descent into the depth of the exploitation, the ore reserves may not justify the exploitation of the deposit, and the investment in these workings may be ineffective.

In order to eliminate this risk and optimize the scheme of opening, preparation and exploitation of the deposit, the degree of knowledge of the Antonio body should be increased through geological research drilling and through geophysical research methods, such as the Georadar or GPR (Ground Penetrating Radar) method.

This method can be considered effective, in the geological conditions of the Antonio ore body, because the deposit is clearly delimited from the surrounding rocks (dolomite, in the roof and limestone, in the floor), and the ore and the rocks have very different qualitative characteristics, which facilitates the spatial representation of the ore body by geophysical methods.

3. Exploitation of the Antonio ore body, under the XVIII horizon

In order to choose an appropriate mining method for the Antonio ore body, within the Baița Plai deposit, the influencing factors were taken into account: geological, technical-mining and economic [2, 3, 4]. Thus, the mining method and technology with sublevel galleries and the caving of the ore and the surrounding rocks was proposed. This method is part of the class of methods with the caving ore and surrounding rocks, the variant with forced caving of the ore in sublevel galleries.

The principle of the method consists in dividing the level with a vertical height of 81 m (related to the Antonio ore body), below the XVIII horizon, into 7 sublevels. The first sublevel from oriz. XVIII-9 has a height of 9 m, and the next 6 levels have a height of 12 m.

The sublevels are delimited in two areas: the lower area with a height of 3 m, in which the sublevel galleries are executed, in the first phase and the upper area (the ore bank), which is exploited in retreat, in the second phase, with long drillholes of fan blast, by surfacing the ore and the surrounding rocks (with a height of 6 m - for horizon XVIII-9 and with a height of 9 m - for horizons XVIII-21 ÷ XVIII-81).

It should be noted that the total estimated reserve of ore related to the XVIII-21 sublevel (fig. 3) is approximately 75,200 tonnes (8,200 tonnes – in the underground galleries dug in the deposit; 67,000 tonnestotal reserve in the pillars and the caved bank).

Figure 3. Spatial scheme of the sublevel galleries at oriz. XVIII-21 [2]

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The two phases of exploitation of sublevels can be applied simultaneously, in the same sublevel or in different sublevels. Practically, the two phases of exploitation, in the same sublevel, is recommended for the case of thick ore bodies with a large extension, which is not the case of the Antonio ore body [2].

That is why, in the case of the Antonio ore body, it is recommended to apply the two phases simultaneously, in two different sublevels. Moreover, the first sublevel, XVIII-9, will be exploited in the second phase, by caving the ore and the surrounding rocks, simultaneously with the execution of the sublevel galleries at level XVIII-21. Then, the XVIII-21 horizon will be in the 2nd phase of exploitation with the caving of the ore and the surrounding rocks and the XVIII-33 horizon, in the phase of digging the sublevel galleries.

In the 1st phase (sublevel „n”), the sublevel galleries are executed using the following mining equipment: the mobile drilling rig Conax Mantis CMR-4; loading and transporting machine Diesel LHD WJ-0.6; Barford Hydrostatic SX3000 dump truck (fig.4.b).

In the 2nd phase („n -1”), mining is carried out with long holes, drilling in the fan and surfacing of the ore and the surrounding rocks, equipped with the following equipment: the mobile drilling rig Conax Mantis CMR-4; loading and transporting machine Diesel LHD WJ-0.6 and WJ-1 (fig.4.a); Thwaites Mach 340 dump truck.

a) b)

Figure 4. Loading and transporting machines a) Diesel LHD WJ-1 b) Dumper Barford Hidrostatic SX3000

For the exploitation of the ore reserves related to the XVIII-9 sublevel, the mining method in sublevels, with caving of the ore and the surrounding rocks, adapted to the mining rooms from this horizon, was proposed, being the only mining method that can ensure the recovery of the ore from the sublevel horizon XVIII-9, with reduced costs.

At the mining level of horizon XVIII-9, with a total area of about 2,400 m2, the deposit was already exploited with rooms (on an area of 1,400 m2) and abandoned pillars (1,000 m2), under an ore ceiling with an average thickness of 6.5 m, disposed below the backfill and broken rocks, from the upper levels. Both the mining rooms and the pillars have an irregular layout in the horizon plane, with different sizes. In general, the rooms have an average height of approx. 2.5 m, there being local situations where the rooms can exceed this height, reaching 3 m and even 4 - 5 m high. The width of the rooms is 3-4 m, the shape of the pillars is irregular and their horizontal dimensions are approx. 4 ÷ 6 x 9 m, in the eastern part, reaching 5 ÷ 7 x 16-19 m, in the western part. The layout of the rooms and pillars and their shape was influenced by the irregular configuration of the deposit, in a horizontal plane.

The geological reserve related to the XVIII-9 level is approx. 59,200 tonnes, of which approx. (11,100 tonnes, leaving an abandoned reserve in the ceiling and in the pillars of 48,100 tonnes). Which means an extraction of the deposit of 18.79% and a total ore loss of 81.21%, values that are unacceptable for the exploitation of a polymetallic deposit of this type, such as the one in the Antonio body, at the Baița Plai mine. That is why the Baița Plai mine set out to design a mining method and technology that would ensure the most important recovery of the abandoned ore in the ceiling and pillars in the level of the XVIII-9 horizon, with as much economic efficiency as possible.

At a production capacity of 100,000 t/year, the geological reserve of 134,400 tonnes, contained in the two sublevels (XVIII-9 and XVIII-21), at an extraction of about 85%, these sublevels cover the production capacity of the mine for about a year.

The cross-section of the sublevel galleries of 3 x 4 m (12 m2) was determined taking into account their stability, the optimal evacuation of the crushed ore and the sizes of the drilling rigs and the loading and transport machinery.

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Also, the width of the pillars between the sublevel galleries was set at 6 m (correlated with the sublevel height of 12 m and the sublevel galleries width and height of 3 x 4 m), which is an optimal size to ensure an ore extraction of more than 90%, ore losses below 10% and a maximum dilution of 20%. These technicaleconomic indicators are influenced by the geometric parameters of the mining method, which were established according to the laws of the flow of the broken ore caved in the mining stope [4, 5, 6, 7].

From various experiments carried out in the laboratory and in situ, it is known that when the ratio between the height of the caved ore bank and the maximum size of the extraction opening (in this case, the width of the sublevel gallery) is between 2 and 30 or even more (in in the case of the XVIII-9 horizon it is 6.5 m /3 m=2.166 and in the case of the XVIII-21 m horizon and those from the depth it is 9 m / 4 m=2.25), and the caved ore bank was broken into non-cohesive pieces and inhomogeneous, the geometry of the broken ore, in motion, will approximately take the shape of an ellipsoid of revolution.

Between the sublevel galleries there is a passive zone where the crushed ore can be recovered at the level of the lower sublevel (fig. 5). The thickness of the passive zone can be thinner or thicker, depending on the inclination of the outflow funnels formed in the massif, the width lg of the gallery, the distance Sg between the sublevel galleries and the characteristics of the flow parameters of the granular material, which control the shape of the passive zone [6].

Figure 5. The vertical location of the sublevel gallery, according to the gravity flow model [4, 6]

Knowing the values of ht and Lt, it is possible to determine, with approximation, the distance Sg between the axis of the underground mining workings, at the end of which the broken ore evacuation operation is carried out. It is assumed that the loosening ellipsoid is 2.5 times larger than the extraction ellipsoid, and the width of the extraction ellipsoid is 40% of the width of the movement ellipsoid. In the design of the mining method with sublevel caving of the ore and the surrounding rocks, it is necessary to determine the width La of the loosening ellipsoid in horizontal section, right at the level where the extraction ellipsoid has the maximum size Lt (see fig.5).

Assuming that the principles of idealized gravity flow can be applied under mining conditions with sublevel caving of the ore and surrounding rocks, the total width Lt of the extraction ellipsoid is approximately 60-65% of the width of the loosening ellipsoid, (at the level where the extraction ellipsoid has its maximum width Lt). Therefore, the approximate horizontal distance between the outlets Sg is [6]: - for an extraction height 18 ≤ ht m: .60 t g L S < (2) - for an extraction height 18 > ht m: .650 t g L S < (3)

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The parameters Lt and dt can be approximately calculated with the relations: .81 + ≅ a h L t t (4) 2 / t t L d ≤ (5)

Where a represents the effective width of the sublevel gallery into which the caved ore is discharged, which depends on the shape of the gallery ceiling. An approximate value of this parameter, for the sublevel galleries is: g l a = .70 (6)

Regarding the design of the advance step (the thickness of blasted space or burden space), in order to reduce ore losses, it is recommended that this parameter be determined with the relationship: 2 t d W ≤ (7)

Taking into account the above relations, following calculations obtained the following values (Table 1): Table 1. Calculated geometric parameters of the mining method

Horizon a, [m] Lt, [m] dt, [m] Sg, [m] W, [m]

XVIII-9 2.1 9.3 ≤ 4.65 <15.50 ≤ 2.23 XVIII-21 2.8 13.0 ≤ 6.50 <21.66 ≤ 3.25

In order to determine the drilling, loading and transport equipment, in the endowment of the mine, meets the conditions imposed by the annual production capacity of 100,000 t/year, in the context of an opening and preparation scheme and the proposed mining technology, they have their productivities, which satisfy these conditions, have been calculated.

The CONAX MANTIS CMR-4 drilling rig executes a fan of 25 drillholes, with a total length of 140 m, in 3 shifts of 6 hours each. The productivity of the drilling rig, for a 6 hour shift and an average drillhole length Lg, was calculated with the relation [3]: 451, 18 ) 1860, exp( 1 5040, 266 + + ⋅

= g g

g L L L P , [m/shift] (8)

Figure 6. Conax Mantis CMR-4 drilling rig

Also, the calculated productivities of the LHD WJ-0.6, LHD WJ-1 and LHD WJD-1 loading and transporting machines are 30, 38 and 47 t/h.

Drilling-blasting parameters (number and length of drillholes, total and specific explosive consumption, etc.) were calculated for the execution of sublevel galleries and fan drillholes layout schemes [3, 8, 9], for the representative situations from horizons XVIII-9 and XVIII-21 (fig. 5).

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Figure 7. Schemes for the placement of the long drillholes in the fans, sublevel XVIII-21, for some representative sections through the ore deposit [2]

As an example, table 2 summarizes the drilling-blasting parameters related to the fans A, B and C, in fig.7.c. The type of explosive used is Riomax HE 38/400 (MAXAM).

Table 2. The value of the drilling-blasting parameters for the fans A, B and C - fig.7.c

Specification UM Value

Fan A Fan B Fan C

Total number of drillholes 25,000 24,000 21,000

Total drillhole length m 147,210 141,390 126,210

Specific hole consumption m/m3 0,953 0,887 0,860 m/t 0,352 0,327 0,317

Total stemming length m 48,410 46,590 42,210

Total volume of stemming m3 0,067 0,065 0,058

Total number of cartridges 247,000 237,000 210,000 Total amount of explosive kg 129,922 124,662 110,460

Explosive consumption kg/m3 0,841 0,782 0,753 kg/t 0,310 0,289 0,278

Detonators consumption staples / m3 0,162 0,151 0,143 staples / t 0,060 0,056 0,053

Burden space m 1,400 1,400 1,400

Mining face surface m2 110,310 113,860 104,800

Volume of ore m3 154,434 159,404 146,720

Quantity of ore t 418,516 431,985 397,611

In order to optimize the parameters of the mining method and technology, which are the basis of the organization of the production system, the design of the production process in the mining faces with the sublevel caving of the ore from the XVIII-9 and XVIII-21 horizons and the digging of the sublevel galleries was carried out. In the same context, the calculation of the labor productivity in the mining face (15.5 t/manshift - at horizon XVIII-9; 17.5t/man-shift – at horizon XVIII-21) and the consumption of materials, fuel and energy was carried out.

The calculation of the unit cost of the tonne of ore extracted from the mining face included: electricity and fuel consumption; depreciation of machinery and means of transport; other consumables; maintenance and repair works of machinery and means of transport; personnel expenses, etc.

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4. Conclusions

• The Antonio polymetallic ore body is one of the main metasomatic bodies within the Baița Plai deposit. This ore body contains Carnian dolomites in the roof and Norian limestones in the floor.

• Starting from the upper limit, the ore body was opened with shafts and adits and was exploited in horizontal slices with the integral backfilling of the stopes, up to the XVIII horizon.

• The opening and preparation of the deposit below the last horizon was carried out ”in eye-pit”, with a spiral inclined plane and a belt conveyor inclined plane, which connect with the directional sublevel galleries, through short cross galleries, raises and ore chutes.

• Exploitation continued with rooms and pillars, at the XVIII-9 horizon and then with sublevel caving of the ore and the surrounding rocks, on the following 6 lower sublevels, with a height of 12 m.

• The endowment with drilling machines and loading and transport equipment and the organization of the production process was carried out to ensure an ore production capacity of about 100 k tonnes/year, with minimal costs.

References

[1] Stoici S.D., 1983

The metalogenetic Băița Bihorului district (in romanian), Academic Publishing București.

[2] Onica I., Cozma E., Georgescu M., Marian D., Cozma B., 2022 Study on the efficient exploitation of the polymetalic Antonio ore body, horizon XVIII, Băița Plai Mine, for the production capacity of 100 000 tonnes/year (in romanian), Contract no. 112/26.01.2022

[3] Georgescu M., 1986

The optimization of the underground exploitation methods for metal ore deposits (in romanian), Technical Publishing, București

[4] Onica I., 2016 Mining exploitation (in romanian), Universitas Publishing, Petroșani.

[5] Richardson M.P., 1981 Area of draw influence and drawpoint spacing for block caving mines.

[6] Kvapil R., 1982

The Mechanics and Design of Sublevel Caving Systems, Underground Mining Methods Handbook, W.A.Hustruild editor, A.I.M.M.P.E.I., New York.

[7] Brady B.G.H., Brown E.T., 2005 Rock Mechanics for underground mining, Third edition, Kluwer Academic Publishers, New York, Springer Science + Business Media, Inc.

[8] Fodor D., 2000 Industrial explosives (in romanian), Infomin Publishing, Deva

[9] Fodor D., 2007 Blasting engineering (in romanian), Namaste Publishing, Timişoara.

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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ANALYSIS OF THE INFLUENCE OF THE VERTICAL COAXIALITY OF THE PILLARS ON THE STABILITY OF THE RESISTANCE STRUCTURES, FROM THE OCNELE MARI SALINE

Dacian-Paul MARIAN 1 * , Ilie ONICA2, Ovidiu MARINA3

1 University of Petroșani, Petroșani, Romania, dacianmarian@upet.ro

2 University of Petroșani, Petroșani, Romania, onicai2004@yahoo.com

3 University of Petroșani, Petroșani, Romania, marina.ovidiu1970@yahoo.com

DOI: 10.2478/minrv-2022-0029

Abstract: The Ocnele Mari rock salt deposit is exploited with small rooms and square pillars, on the horizons +226 m and 210 m. Following the exploitation of the lower horizon +210 m, the floor between the two horizons suffered instability phenomena, marked by fractures and cracks and local degradation of the pillars.Since the pillars at the two horizons have certain deviations from the coaxiality, the question was raised whether the instability phenomena were generated by the deviations from the coaxiality.This article presents the stability analysis of bearing structures, taking into account the actual geometry of pillars, 3D finite element analysis and analysis of safety factors at the ceiling level, calculated from 2D finite element models. The final conclusion is that the instability phenomena that occurred at the Ocnele Mari Saline were generated by the state of stresses and strains, produced by the spatial distribution of the underground voids and the geomechanical characteristics of the rock salt and insignificantly, by the deviation from the coaxiality of the pillars.

Keywords: rock salt, rooms and pillars mining, pillar, ceiling, stability analysis, finite element, stress, strain, safety factor

1. Geology of the Ocnele Mari-Cocenești deposit

The Ocnele Mari salt deposit can be found in the area of the subcarpathian hills of Oltenia, stretching from the East of the Olt river to the West of the Govora stream, passing through the territory of the Ocnele Mari locality in Vâlcea county.

The Coceneşti perimeter is located in the eastern area of the Ocnele Mari deposit. Access to the deposit is on the road that goes to the town of Ocnele Mari, Vâlcea county. The morphology of the region has a hilly aspect, with heights between 250 - 450 m.

The Ocnele Mari region, where the deposit is located, belongs to the Getic Depression, which is the most external unit of the Southern Carpathians. It was formed as a result of the laramic movements, as a consequence of the uplift of the crystalline-Mesozoic zone, in front of which a premontane depression was formed, with the role of an ”avant-fossé” that functioned in this way during the Paleogene and Neogene.

From a stratigraphic point of view, the Ocnele Mari region includes Paleogene, Neogene and Quaternary geological formations.

The horizon with rock salt deposits is presented in a lagoonal facies, with local distribution, being formed by salt masses, gypsum and salty marls. The rock salt deposit from Ocnele Mari is included in this horizon, and the salt massif appears in the area of axial uplift from Ocniţa - Ocnele Mari. The age of the rock salt from Ocnele Mari - Coceneşti is middle Badenian [1, 2].

The Ocnele-Mari salt deposit has the shape of an elongated lens in the E-W direction, measuring approx. 7.5 km, and to the N-S approx. 3.5 km, presenting an axial uplift in the Ocniţei area, with slopes to the N. The

* Corresponding author: Dacian-Paul Marian, Assoc.Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania dacianmarian@upet.ro)

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thickness of the salt deposit is variable, reaching laminations in the northern and southern parts, the maximum thickness reaching 450 m in the central part of the lens.

The rock salt in the deposit has a macrogranular structure with well-developed crystals, grayish white or blackish in color, depending on the contribution of terrigenous impurities. Banks of white salt alternate with those of darker salt, and in the lower part of the deposit, a bank of black salt with thicknesses from 5 to 30 m, impurized with anhydrite, having a higher hardness and compactness than the rest of the salt, frequently appears from the deposit [1, 2].

2. Instability phenomena occurring at the Ocnele Mari saline

In the period 1993-1996, the mining workings to open the Ocnele Mari salt mine were carried out. The information obtained with the opening workings completed the picture of the deposit, and the underground drillings carried out starting in 1994 allowed a more accurate outline of the rock salt – barren rocks limit and the start of exploitation of the deposit at the level of the +226 m horizon.

The designed mining method, for the geo-mining conditions at this salt mine, is the method with small rooms and square pillars [3], arranged in a 30 x 30 m grid, with different sizes in the eastern and western wings (table 1). After mining the deposit at the +226 m level, mining continued under an 8 m thick rock salt ceiling, at the +210 m level.

Table 1. Geometric parameters of the mining method with small rooms and square pillars, for Ocnele Mari - Cocenești Saline [4, 5]

Horizon Starting year of exploitation Room Pillar Ceiling Level Width, W/ E [m] Height, [m] Width, W/E [m] Height, [m] Thickness, [m] Height, [m]

+226m 1996 16/15 8 14/15 8 8 16 +210m 2001 16/15 8 14/15 8 8 16

After the deposit was extracted, a tourist base was set up in the exploited spaces of the western wing, in accordance with the feasibility study developed in 2009 [6]. Following the exploitation of the +210 m horizon, in the western wing, related to the tourist base, a series of cracks and microcracks appeared in the ceiling between the two horizons (table 2), associated with cracks and detachments of pieces of rock salt at the +210 m horizon, from the ceiling and from the walls of the pillars, in the area of rooms 24-25, horizon +226/210W. Also, a series of instability phenomena could be observed in the area of ventilation shaft 5, between pillars H22 and H23, in the form of cracks in the ceiling, with displacements both in the horizontal and vertical planes.

Table 2. The situation of the cracks in the floor between horizontal +226m and +210m, in the area of rooms 24-25 [7] Fissure Room Between pillars Fissure length, m Fissure Room Between pillars Fissure length, m F1 H G25H25 8.80 F4 H H24G24 11.43

F2 24 H24H25 6.42 F5 H H23G23 8.45

F3 24 H24H25 8.86 F6 G G23F23 9.90

At the request of the salt mine, in 2014, SC MINESA SA [6] analyzed the causes that led to the appearance of these instability phenomena. In this study, based on the topographic measurements carried out on the resistance structures, it was concluded that, if the inter-rooms pillars do not overlap and have deviations from coaxiality, in the ”rooms-pillars-ceiling” system, the following instability phenomena may occur, among others [6]:

- horizontal and vertical deformations of the pillars at the level of both horizons, manifested by the rounding of the corners of the pillars and the detachment of pieces of rock salt from their surface;

- deformations of the floor at the border with the inter-rooms pillars, local shear fractures may occur in the respective areas;

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- at a short distance from the pillars, both at the floors and at the ceilings, cracks may appear, due to the increase in tensile stresses.

Phenomena of local instability of the ceiling and pillars were also found in the directional exploitation room G, from the eastern wing, horizon +210E, more precisely in rooms G31, G32 and G33. After 8 years since the completion of the exploitation of the rooms, areas with different degrees of stability have been identified, the working being placed in an area with a potential risk of long-term instability, namely: the southern wall of chamber G is more stable and without visible signs of degradation; the northern wall is inhomogeneous, being more pronounced; the ceiling is stable but exposed to damage due to the state of stresses and strains developed in this area. In this section, with a length of 105 m, consolidation works have already been carried out with 2.5 m long cemented anchors and reinforced shotcrete [8], completed in 2020, and following the monitoring of the ceiling movements, the measured values of the movements were insignificant.

In order to study the coaxiality of the pillars, the plan representations of the pillars from the horizons +226 m and +210 m were used. Following the overlapping of the outline of the pillars at the level of the two horizons (as in fig.1), for each separate pillar, were the following geometric characteristics were measured: the surface of the pillars from horizon +226 m and from horizon +210 m, in m2; the area of intersection between the pillars of the two horizons, in m2 and the center / axis of this area; the distance between the center / axis of the intersection surface and the axis of the designed pillar, in m. The measured values are summarized in the graphs in figures 2-4 which also contains the deviations, in %, from the geometric characteristics of the designed surfaces of the pillars.

Figure 1. Correlation between the designed and realized axis of the pillars at horizons +226 m and +210 m Ax.pr. – the projected axis of the pillars; Ax.sp.- the axis of the overlapping surface; Dax – deviation of projected surface axis-overlap surface axis; 226 S - the surface of the base of the pillar at the horizon +226 m; 210 S - the surface of the base of the pillar at the horizon +210 m; 226 210 S -the overlapped surface of the pillars from horizon +226 m and +210 m

Horizon +226

Pillar surface deviation, (%)

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Figure 3. The percentage of pillars from the +210 horizon, depending on the bearing surface deviation in relation to the projected one, in %

Figure 4. Percentage of overlapping pillars at the two horizons, +226 m and +210 m, function of the deviation of the actual axis from the projected axis, in m

As can be seen from fig.2, at the +226 m horizon, the percentage of pillars, out of the total number of existing pillars at the +226 m horizon, with a deviation of the real surface reduced by 10% compared to the projected one, is less than 13 %. It can also be seen that 87% of the pillars located at this horizon have an oversized surface (of which, more than 57% of the pillars have a bearing surface larger by up to 20%).

In the case of the +210 m horizon (fig. 3), the percentage of pillars with a surface area 12% smaller than the designed one is approximately 25%, and the pillars with positive deviations from the load-bearing surface (larger than the designed one) are in a percentage of approx. 75% of the total pillars from this horizon.

Regarding the deviation from coaxiality of the pillars located at the two horizons (fig. 4), it is as follows: 33% of the overlapping pillars have deviations below 0.4 m; 12% have deviations between 2 and 4 m, and most of the pillars, in proportion to 53%, have deviations between 0.4 m and 2.0 m. Although the values of deviations from the coaxiality of the pillars would seem quite important, we note that the deviation of the pillar axes is due to their over-dimensioning (sometimes, to the point of connecting two adjacent pillars together), which led to the increase of the safety coefficient and implicitly to the improvement stability of resistance structures.

As can be seen from the previous analyses, most of the existing pillars at Ocnele Mari Saline have loadbearing surfaces that are much larger than their designed values, which means an important reserve of stability, and the deviation from coaxiality of the pillars at horizons +226 m and + 210 m are only the result of the

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change in the geometry of the pillars. The negative values of the deviations from the load-bearing surfaces are insignificant, taking into account the fact that the pillars have been oversized since their design phase [4, 5].

Because we considered that the factors that contributed to the occurrence of the instability phenomena at the Ocnele Mari salt mine, at least the fractures that appeared in the ceiling between the horizons +226 m and +210 m, are much more complex, and the deviations from coaxiality are insignificant, in order to have a important influence on resistance structures, we tried to carry out a much more in-depth study on their stability. So a 3D finite element modeling was carried out, assuming the elasto-plastic behavior without hardening of the rock salt massif, calculated according to the Mohr-Coulomb criterion. The geometric model of the Ocnele Mari salt mine respected the geometry of the pillars and ceiling set by the project, without taking into account the deviations of the pillars and ceiling from reality (details are presented in [4, 5]).

As a result of the calculations carried out, it was found that the resistance structures entered plasticization, exactly in the areas where instability phenomena were observed (fissures, cracks in the ceiling and pillars), respectively in the area of pillars 24-25, related to the tourist base (fig.5 ) and in the area of directional chambers G31, G32 and G33, from the 210E horizon (fig.6), which were reinforced with cemented anchors and reinforced shotcrete.

Figure 6. Situation plan of horizon 210E, eastern wing of Ocnele Mari Saline [5]

The results obtained from the 3D finite element modeling demonstrated very clearly that it is not the deviation from the vertical coaxiality of the pillars the factor responsible for the occurrence of the instability phenomena at the Ocnele Mari Saline (as was concluded in the study [7]), but it is the condition of stresses and strains generated by the spatial geometric configuration of underground voids and surface relief [9] and the geomechanical characteristics of rock and rock salt.

3. Finite element analysis of the influence of the axial deviation of the pillars on the stability of the resistance structures

In order to quantify the influence that the deviation of the axis of the safety pillars has on the stability of the resistance structures, with the help of 2D finite element modeling, in elasto-plasticity without hardening, according to the Mohr-Coulomb criterion, several simulations were carried out under the conditions Ocnele

Figure 5. Situation plan of horizon +226W, from the western wing of the Ocnele Mari Saline [5]

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Mari Saline, for horizons +260 m and +210 m. In the numerical models, the behavior of the resistance structures was analyzed, in the case of the deviation of the pillars at the +210 m horizon, with increments of 1 m, from 0 to 8 m, in relation to the pillars at the +226 m horizon. A detailed analysis of the change in the state of stresses and strains, as the value of the deviation of the pillar axis increases, would have been very complicated to achieve (fig. 7). Therefore, to simplify the analysis, starting from the calculated values of the main stresses, from the models with finite elements, the values of the safety factor [4] were determined. a) b) c) d) Figure 7. Maximum main stresses: a) coaxial pillars, b) pillars deviated by 4m; Minimum main stresses: c) coaxial pillars, d) pillars deviated by 4m

The criterion for calculating the safety factor, for models with finite elements in 2D, starts from the intrinsic curve of the rock salt. In this sense, for a certain point, characterized by a certain stress state, the corresponding Mohr's circle is determined and related to the intrinsic curve of the rock salt. In this sense, the Mohr-Coulomb line is taken into account (defined by the relation: ϕστ tg C ⋅+= ) and the following conditions are established [4, 10]: a) If Rt < 2σ , for ( ) ϕ ϕ sin 1 ⋅−⋅= c S ctg CR , RRSF / 1 = ; b) If , Rt ≥ 2σ then SF=0. where: 2 21σσ + = c S represents the abscissa of the center of Mohr's circle; 2 21σσ = R - radius of Mohr's circle; R1 - the radius of Mohr's circle tangent to the Mohr-Coulomb right; SF - safety factor; Rt=1,200 kN/m2tensile strength of rock salt; C=4,000 kN/m2 - cohesion; ϕ =30o - the internal friction angle of rock salt; , 1σ , 2σ - maximum and minimum main stress, respectively (see fig.7). In the calculations, for rock salt, the following were also taken into account: the modulus of elasticity E=1.5 106 kN/m2, the Poisson's coefficient, ν =0.25 and the apparent specific gravity, a γ =21.5 kN/m3

As a function of the calculated value of the safety factor SF=R1/R, three cases of stability are defined [4, 10]:

a) SF = 1 - limit stability (Mohr's circle and the intrinsic curve of rock salt are tangent);

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b) SF < 1 - conditions for the appearance of failure phenomena (Mohr's circle and the intrinsic curve are secants);

c) SF > 1 – diferent degree of stability depending on the value of the safety factor (the state of stress is far from the failure phenomenon).

Since the state of stresses and strains at the level of the ceiling of the horizon +226m and at the level of the floor of the horizon +210 m is less affected by the deviation of the coaxiality of the pillars and rooms, the calculation of the safety factors was carried out through two horizontal sections, at the level of the floor +226 m (fig.8) and the ceiling +210 m (fig.9). This fact is evidenced by the distribution of principal stresses in figure 7, for the basic model, (a) and (c) and the model with the pillar axis deviated by 4 m, (b) and (d).

70.0

65.0

60.0

55.0

50.0

45.0

40.0

35.0

30.0

25.0

20.0

15.0

10.0

Section floor horizon +226m 0.0

SF Dev. 0m Dev. 1m Dev. 2m Dev. 3m Dev. 4m Dev. 5m Dev. 6m Dev. 7m Dev. 8m

5.0

75.0 0 15 30 45 60 75 90 105 120 135 Distance X , m

Figure 8. The variation of the safety factor in the floor of the horizon +226m, depending on the deviation from the coaxiality of the pillars by 0, 1, 2,...,8m

140.0

130.0

120.0

110.0

100.0

90.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

Section ceiling horizon +210m 0.0

SF Dev. 0m Dev. 1m Dev. 2m Dev. 3m Dev. 4m Dev. 5m Dev. 6m Dev. 7m Dev. 8m

150.0 0 15 30 45 60 75 90 105 120 135 Distance X , m

Figure 9. The variation of the safety factor in the horizon ceiling +210m, depending on the deviation from the coaxiality of the pillars by 0, 1, 2,...,8m

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Analyzing the variation of the values of the safety factors at the level of the ceiling between the two horizons, it can be found that there is a significant variation between the maximum values of the safety factors, while the minimum values are kept within the limits of the value of SF=2-3, for values of the coaxiality deviation up to 2-3 m. There is an important decrease in the safety factor, up to SF=1.4 -1.5, for higher values of the axis deviation, towards 7-8 m.

Considering the fact that the axis deviations, for most of the pillars, are below 2 m (see fig.4), the decrease in the safety factor is within acceptable limits. Moreover, in most cases, the deviation of the geometric axis occurred as a result of the increase of the load-bearing surface of the pillar, which makes this assumption have a certain degree of relativism.

Following the analysis of the calculated values of the safety factors, it can be concluded that the deviation of the axis of the pillars, under the mining conditions of the Ocnele Mari Saline, had an insignificant importance on the stability of the resistance structures, especially due to the large thickness of 8 m of the ceiling between the horizons +226 m and +210 m, which allowed a redistribution of stresses in its structure, without exceeding the tensile and shear resistance limits of the rock salt.

4. Conclusions

• The exploitation of the rock salt deposit from Ocnele Mari - Cocenești began in 1996, at the level of the horizon +226 m, by the mining method with small rooms and square pillars.

• After the continuation of exploitation at the next level +210 m, phenomena of instability appeared in the ceiling between the two horizons, marked by fissures and cracks and the local degradation of certain exploitation pillars. The affected structures were in the tourist base at +226W, in the area of pillars 24-25, especially the ceiling between the horizons, and in the area of directional rooms G31, G32 and G33, in the horizon 210E.

• In order to determine the causes that generated the occurrence of the instability phenomena of the resistance structures at the Ocnele Mari saline, the following were analyzed: the real geometry of the pillars and its deviations from the design; the results of the modeling with 3D finite elements, in elastoplasticity, of the stability of the resistance structures from the Ocnele Mari Salt Mine; safety factors calculated from the results of 2D finite element modeling, in elasto-plasticity, for several theoretical situations of pillars deviation, with values of 1,2,..,8 m.

• From the stability analysis with finite elements in 3D it resulted that the regions in the models affected by plasticization, respectively instability, are located in the area of pillars 24-25, horizontal 226W and in the directional rooms G31, G32 and G33, horizon 210E. Since the models were made according to the designed geometry of the resistance structures (rooms, pillars, ceiling), without deviation from coaxiality, it follows that the instability phenomena occurring in the resistance structures are influenced by the state of stresses and strains produced by the geometry and spatial distribution of underground voids, the variation of land surface relief and the geomechanical characteristics of rock salt.

• Following the comparative analysis of the safety factors, calculated by 2D finite element modeling, in elasto-plasticity, for different deviations from the coaxiality of the pillars, in relation to the real situation in the field, it resulted that the deviations from the coaxiality of the pillars from Ocnele Mari Saline did not significantly influence the instability phenomena that appeared in this saline.

References

[1]. Hirian C., Georgescu M., 2012

The stability of old Romanian salt mines – conditions for their use in various domains (in Romanian), 2nd edition, Universitas Publishing.

[2]. Marica D., 2011

Stability study of mining excavations from Ocnele Mari salt mine to increase the work safety degree (in Romanian), Ph.D thesis, University of Petroșani

[3]. Covaci Ş., e.a., 1999

Mining exploitations (in Romanian), Corvin Publishing, Deva

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[4]. Marian D.P, Onica I., 2021

Analysis of the stability of the rooms and resistance structures at the Ocnele Mari – Cocenești salt mine, based on safety factor, Annals of the University of Petroşani, Mining Engineering, Vol.22 (XLIX), pag.99-112.

[5]. Marian D.P, Onica I., 2021

Numerical modeling of the stability of the resistance structures from Ocnele Mari salt mine using the finite element method, Annals of the University of Petroşani, Mining Engineering, Vol.22 (XLIX), pag.113-126.

[6]. *** , 2009

Opportunity study for arranging the underground tourist site from Ocnele Mari-Cocenești Salt Mine, Vâlcea County (in romanian), symbol 34-661-01/2009, S.C.MINESA-ICPM S.A. Cluj-Napoca.

[7]. Pușcaș G. e.a., 2014

The ceiling support of chambers 24-25, horizon +210W, from Ocnele Mari Salt Mine, Stage I Study, (in romanian) Contract 693/21.01.2014, symbol 34-876, SC MINESA – ICPM SA Cluj-Napoca.

[8]. Kovacs F., 2012

Minimal flux for rock salt grinding in underground Ocnele Mari Salt Mine, Râmnicu Vâlcea Mining Exploitation Branch, Volume II – Strenghtening the placement area for the grinding flux (in romanian). Technical project phase and task books, symbol 3/4/2012, S.C.DACITROM SRL Cluj-Napoca.

[9]. Herget G., 1988 Stresses in rock, Balkema

[10]. Jifang Lin, 1990

Modélisation des milieux anisotropes. Application du logiciel CESAR-LCPC à l’étude des ardoisiers d’Angers, DEA de Génie civil et minier, Laboratoire de Mécanique des Terrains, ENSM Nancy.

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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MONITORING OF THE DEPOSIT DISPLACEMENTS AND THE SETTLEMENT BEHAVIOR IN SIMIONEȘTI VILLAGE LOCATION, CORDUN COMMUNE, NEAMŢ COUNTY

Klaus-Gerhart FISSGUS 1 * , Nelu ȘTEFAN2

1 University of Petroșani, Petroșani, Romania, klausfissgus@upet.ro

2 University of Petroșani, Petroșani, Romania, mihacon73@yahoo.com

DOI: 10.2478/minrv-2022-0030

Abstract: Monitoring the displacements and settlements of tailings deposits is necessary due to stability problems that may arise over time. The paper deals with the monitoring by means of topographical measurements of two tailings deposits located on a site in Simionești village, Cordun commune in Neamț county. Topographic measurements are used to monitor the movement of landmarks located on these deposits and the settlement behavior of the deposit, so that any stability problems can be detected in time.

Keywords: deposit stability monitoring, surveying of settlement and displacement

1. General information

Monitoring the movements and settlements of tailings deposits is necessary due to problems that may arise over time.

Problems and hazards associated with tailings deposits include the following [1, 2]:

• slope instability;

• the generation of acidic waters and the discharge of toxic substances, leading to the contamination of surface and underground waters downstream;

• dust pollution and erosion;

• land degradation.

In view of these environmental hazards, rehabilitation measures aim to [1, 2]:

• improving the stability of landfills;

• ensuring stability against erosion;

• minimizing the degree of infiltration;

• reducing the effects generated by acidic waters and reducing the flow of exfiltrates.

The present paper deals with the monitoring by means of topographical measurements of two tailings deposits located on a site in Simionești village, Cordun commune in Neamț county.

An aerial view of the studied site from Simionești village is presented below. The two deposits taken into the study are represented with a red outline. On the site, there are still two areas in preparation where other deposits will be created in the future.

2. Preparing and carrying out topographic measurements

Landmarks were placed on the tailings deposits to track the behavior over time, materialized through Feno landmarks, one marker in the corner areas of the deposits, and one marker in the center of the deposits. We note that the upper part of the deposits is a flat and almost horizontal surface, covered with topsoil and grass, so that there is good visibility between the monitoring landmarks.

* Corresponding author: Klaus-Gerhart Fissgus, Lect. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania klausfissgus@upet.ro)

Also, to ensure a unique and stable reference system from one stage to another of measurements, a topographic support base was placed outside the area of influence of the deposits, consisting of two points that were determined by GNSS measurements [3], marked on plan with GPS-1 and GPS-2. Their coordinates were transcalculated in the Stereografic 1970 projection system with the TransDatRO application [4], and the elevations in the Black Sea 1975 altimetric system. The Stonex S9 GNSS receiver was used with the TransDatRO application implemented.

At each stage of measurements it started from the two stable points. The initial stage of measurements was carried out in October 2016 (also called "zero measurement"), denoted T0 Subsequently, each year during the month of October, a measurement session was carried out, respectively in 2017 stage T1, in 2018 stage T2, in 2019 stage T3, in 2020 stage T4, in 2021 stage T5 and in 2022 stage T6

Equipment used: A Leica TCR 407 power total station was used for the topographic measurements and the construction of the polygonal network.

In each measurement session, a closed polygonal network [5] was carried out on the two stable landmarks, GPS-1 and GPS-2, at the same time determining the coordinates and elevations of the 10 monitoring landmarks.

The processing of conventional measurements was carried out using spreadsheet programs [6], and the drawing up of the situation plan and other graphic representations was done using computer-aided design programs [6].

3. Calculation of displacement and settlement elements and preparation of the situation plan

To exemplify the calculations performed at each measurement stage, we will calculate the displacement and settlement elements for the October 2022 (T6) measurement, relative to the October 2016 (T0) zero measurement.

The plane coordinates and elevations of the landmark points from the T0 measurement stage carried out in 2016, used for reference, are presented in table 1.

The plane coordinates and elevations of the landmark points from the T6 measurement stage carried out in 2022 are presented in table 2.

Following the comparison of the plan (2D) and altimetric (H) coordinates of the monitoring landmarks from the 2022 stage compared to the 2016 stage, the displacements in the directions of the East and North coordinate axes (ΔE and ΔN) as well as the vertical displacements (settlements ΔH) are presented in table 3.

Figure 1. The location of the studied deposits, in Simionești village, Cordun commune (source: Google Earth)

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Table 1. „Zero” Measurement 2016 (t0)

Landmark Easting [m] Northing [m] Elevation H [m]

GPS-1 642136.593 609148.189 200.652 GPS-2 642113.052 609093.049 199.430 PM-1 642036.524 609050.114 199.826 PM-2 642155.842 609016.791 200.431 PM-3 642068.999 609053.181 200.169 PM-4 642097.398 609069.310 199.841

PM-5 642118.876 609064.154 199.742 PM-6 642029.405 609070.120 199.496 PM-7 642092.476 609034.051 199.953 PM-8 642098.306 608971.477 198.631 PM-9 642203.122 608950.758 198.610 PM-10 642231.561 609053.389 199.416

Table 2. Measurement 2022 (t6)

Landmark Easting [m] Northing [m] Elevation H [m]

GPS-1 642136.593 609148.189 200.652 GPS-2 642113.052 609093.049 199.430 PM-1 642036.533 609050.111 199.821 PM-2 642155.853 609016.802 200.417 PM-3 642069.006 609053.183 200.167 PM-4 642097.403 609069.310 199.837 PM-5 642118.881 609064.159 199.735 PM-6 642029.408 609070.113 199.494 PM-7 642092.480 609034.053 199.946 PM-8 642098.316 608971.480 198.624 PM-9 642203.145 608950.772 198.601 PM-10 642231.565 609053.414 199.360

Table 3. Differences 2022 stage compared to the 2016 stage Landmark ΔE (t6-t0) [m] ΔN (t6-t0) [m] ΔH (t6-t0) [m] (dif. Easting) (dif. Northing) (Settlement)

PM-1 0.009 -0.003 -0.005 PM-2 0.011 0.011 -0.014 PM-3 0.007 0.002 -0.002 PM-4 0.005 0.000 -0.004 PM-5 0.005 0.005 -0.007 PM-6 0.003 -0.007 -0.002 PM-7 0.004 0.002 -0.007 PM-8 0.010 0.003 -0.007 PM-9 0.023 0.014 -0.009 PM-10 0.004 0.025 -0.056

where: t0 represents the stage of measurements carried out in 2016; t6 represents the stage of measurements carried out in 2022; ΔE, ΔN, ΔH represent the differences in coordinates and elevations between the stages of measurements.

Based on these differences in coordinates and elevations, the displacement vectors of the monitoring points were calculated in the horizontal plane, and the direction (azimuth) in which the displacement was made. Also, for the complete characterization of the displacements, the size of the spatial displacement vectors (3D) and their inclination with respect to the horizontal was calculated, as shown in the following table [5, 6]:

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Table 4. Displacement vectors of landmarks

Landmark Horizontal Displacement Displacement Azimuth Vertical Displacement

3D Total Displacement Displacement Tilt [m] [°] [m] [m] [°]

PM-1 0.010 105.50 -0.005 0.011 -27.91

PM-2 0.015 44.08 -0.014 0.021 -43.09

PM-3 0.007 77.51 -0.002 0.008 -11.53

PM-4 0.005 93.97 -0.004 0.007 -37.11

PM-5 0.007 45.63 -0.007 0.010 -42.77

PM-6 0.007 156.98 -0.002 0.007 -13.90

PM-7 0.005 66.33 -0.007 0.009 -57.33

PM-8 0.011 75.31 -0.007 0.013 -34.61

PM-9 0.027 57.34 -0.009 0.028 -19.23

PM-10 0.025 9.00 -0.056 0.061 -65.98

The horizontal displacements of each landmark were figured on the situation plan according to the direction of displacement, with a red line, to scale. This resulted in the following situation plan, presented only partially:

Figure 2. Situation plan with monitoring landmarks and measured displacements.

4. Landmark study of measured displacements in all stages

In order to better characterize the evolution over time of the movement of landmarks, we performed a study on each landmark separately, including all measurement stages. In this way one can see the "trajectory" traveled by the monitoring landmark over time. For example, two landmarks were chosen for each deposit that will be analyzed within the scope of this study.

On the first deposit we chose the landmarks PM-1 and PM-7. Their coordinates in all stages of measurement are presented in the following tables.

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Table 5. Landmark PM-1

PM-1 Easting [m] Northing [m] Elevation H [m]

T0 642036.524 609050.114 199.826

T1 642036.526 609050.107 199.827

T2 642036.528 609050.108 199.827

T3 642036.527 609050.108 199.824

T4 642036.532 609050.100 199.823

T5 642036.531 609050.097 199.823

T6 642036.533 609050.111 199.821

The graphical representation of the travel path is illustrated in the following figure, both as a planar representation and as an isometric representation.

Figure 3. The movement trajectory of the PM-1 landmark over time

Table 6. Landmark PM-7

PM-7 Easting [m] Northing [m] Elevation H [m]

T0 642092.476 609034.051 199.953

T1 642092.481 609034.048 199.952

T2 642092.478 609034.051 199.952

T3 642092.481 609034.050 199.951 T4 642092.490 609034.047 199.950

T5 642092.483 609034.044 199.948 T6 642092.480 609034.053 199.946

Below there is the representation of the movement trajectory of the PM-7 landmark in the two variants.

Figure 4. The movement trajectory of the PM-7 landmark over time

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On the second deposit we chose the PM-2 and PM-8 landmarks. Their coordinates in all stages of measurement are presented in the following tables.

Table 7. Landmark PM-2 PM-2 Easting [m] Northing [m] Elevation H [m]

T0 642155.842 609016.791 200.431

T1 642155.849 609016.794 200.427 T2 642155.849 609016.793 200.427

T3 642155.849 609016.798 200.423 T4 642155.857 609016.796 200.421 T5 642155.866 609016.798 200.420 T6 642155.853 609016.802 200.417

The graphical representation of the travel path is illustrated in the following figure, both as a planar representation and as an isometric representation.

Figure 5. The movement trajectory of the PM-2 landmark over time

Table 8. Landmark PM-8 PM-8 Easting [m] Northing [m] Elevation H [m]

T0 642098.306 608971.477 198.631 T1 642098.314 608971.479 198.627 T2 642098.314 608971.479 198.629 T3 642098.316 608971.479 198.626 T4 642098.326 608971.476 198.624 T5 642098.332 608971.472 198.624 T6 642098.316 608971.480 198.624

Below there is the representation of the movement trajectory of the PM-8 landmark in the two variants.

Fig. 6. The movement trajectory of the PM-8 landmark over time

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5. Conclusions

Following the results obtained through precision topographic measurements in the October 2022 stage and their comparison with the values obtained in the October 2016 measurement stage, a centimetric subsidence (settlement) is found, with values in the range of [0.2 – 5.6] cm for the landmarks materialized in the field. Horizontal displacements with values ranging between 0.5 cm and 2.7 cm were also found for the landmarks materialized in the field. It can be concluded that the landmarks are stable over time, and it is recommended to continue monitoring in annual measurement stages, in order to be able to detect potential stability problems in time.

References

[1] Ministry of Economy, Romania

The rehabilitation of waste dumps and settling ponds

https://www.economie.gov.ro/images/legislatie/Resurse%20Minerale/Mine_Anexa_9.pdf

[2] European Commission, Directorate General JRC Joint Research Center, 2004

Best Available Techniques for Management of Tailings and Waste-Rock in Mining Activities, Institute for Prospective Technological Studies, Technologies for Sustainable Development, European IPPC Bureau, Final Report, July 2004

[3] Neuner J., 2000

Global positioning systems (in romanian), Matrix Rom Publishing, Bucureşti 2000

[4] National Agency for Cadastre and Real Estate Advertising, Romania (ANCPI)

TransDatRO application. https://www.ancpi.ro/wp-content/plugins/download-attachments/includes/download.php?id=7710

[5] Rusu A., Boş B., 1982

Topography – Geodesy (in romanian), EDP, Bucureşti

[6] Vereş I., 2006

The automatization of topographic-geodesic works (in romanian), Universitas Publishing, Petroșani

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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CONCEPTUALIZATION AND QUANTITATIVE ASSESSMENT OF RISK ASSOCIATED WITH EXPLOSIVES

Victor Gabriel VASILESCU 1, Roland Iosif MORARU2 *

1 University of Petroșani, Petroșani, Romania

2 University of Petroșani, Petroșani, Romania, roland_moraru@yahoo.com

DOI: 10.2478/minrv-2022-0031

Abstract: The management of explosion risk at explosives warehouses allows ensuring the necessary premises for the development, in objective and specific conditions, of the necessary documents for these types of technical infrastructures, right from their design phase and the quantification of the degree of impact on the sites analyzed as well as the areas that are located in their vicinity. In the case of the quantitative evaluation of the explosion risk generated following the detonation of explosive materials, the estimation of the manifestation of hazards identified through the associated risk factors should be carried out based on scientific calculation algorithms and established grapho-analytical models. The paper summarizes part of the results obtained regarding the development of a methodological approach and specific application tools that allow the assessment of the major accident risks generated by explosive materials, the identification, formalization and structuring of the applicable safety requirements to reduce or eliminate the risks in explosive material storage sites.

Keywords: major accident, explosives, risk assessment, overpressure, structural response, individual and group risk

1. Introduction

On July 10, 1976, the city of Seveso, Italy, became the survivor of a major industrial accident that occurred within a chemical plant. This accident occurred when a disk from a chemical reactor ruptured, resulting in the release of a dense and white cloud, which contained a small "storage" of the highly toxic substance known as 2,3,7,8-tetrachlorodibenzop-dioxin (TCDD) [1].

This led to drafting the first Seveso Directive aimed both at prevention of major accidents occurrence and to protection of workers /citizens [2]. Following other major industrial accidents around the world - in Bhopal (India), Mexico City (Mexico), Toulouse (France) and Enschede (Netherlands) - the original version of SEVESO was reformulated in the Council by the Directive called Seveso II [3]. One of the main objectives in this "iteration" of the directive was to address the hazard that arises when hazardous facilities/sites and neighboring targets are located in close proximity to each other, the land use planning issues when new facilities/sites are authorized and when urban development takes place around existing facilities [4]. In 2012, a third iteration of the legislation was passed, entitled Directive 2012/18/EU of the European Union Parliament (Seveso III), introducing two different classes of sites and revising the list of hazardous substances [5].

At the present time, it is increasingly admitted and recognized that the vast majority of industrial accidents have as their fundamental cause the faulty way in which management is carried out at the level of economic operators [6].

Explosives warehouses can be considered as critical infrastructures, especially taking into account the criterion of extent, the amplitude of the effects of an explosion produced in a warehouse, but also the possible severity on economic activity, the public and the environment [7, 8]. It is recommended, more and more, that the processes of identification, evaluation and control of risks are carried out proactively rather than reactively [9].

* Corresponding author: Roland Iosif Moraru, Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania roland_moraru@yahoo.com)

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The implementation of technical means of protection can increase costs, if these means are implemented after the design of an explosives storage site is completed or after its construction [10, 11]. In general, changes made at the design stage are less expensive and more effective than those made later, which fully justifies starting the risk analysis and assessment process from this stage [12, 13].

Risk, understood as a statistical value, is usually quantified mathematically as the product of probability and consequences. However, the definition of risk (or conversely, safety) is not universal, unambiguous and objective [14]. Therefore, a comprehensive risk-based safety assessment must consider the following types of risks at the same time [15]:

• Individual risk - risk to the exposed person, which focuses mainly on his own hazards, regardless of the number of people who are also exposed;

• Real collective risk (also known as group risk) - the total risk of the group of exposed persons, which represents the entire hazard of the activity, in which society is primarily interested;

• Perceived collective risk - the actual collective risk increased by a factor, depending on how the parties responsible for the hazardous activity and who are interested in limiting the hazard in such a way that the public will not oppose this activity and which predicts the proportional response of society to accidents with high consequences due to the specific field of hazardous activity.

The methodologies for analysis, evaluation and classification of major accident (explosion) hazards, in the case of explosives warehouses, allow the quantification of the possible effects on the neighborhood and on human health, including the delimitation of emergency planning areas [16].

A viable solution to the problem of major risks specific to the technical infrastructures intended for the storage of explosive materials must help to carry out a quick analysis of the site, to impose conditions prior to the construction of the objective from its design phase.

This paper summarizes some of the results obtained regarding the definition of a methodological approach and specific application tools that allow the assessment of the risks of a major accident generated by explosive materials, the identification, formalization and structuring of the safety requirements applicable to reduce or eliminating risks in explosives storage sites.

2. Material and method

2.1. Conceptualization of the notion of risk specific to industrial sites where operations with explosive materials are carried out

The methodology of quantitative risk assessment, addressed in this paper, is based on the concept of risk developed since 1662 by the French mathematician Blaise Pascal, who argued that: „Our fear of harm should be proportional, not only with the extent of the affect, but also with the probability of the occurrence of the event that generated it”.

In the occupational sense, the risk can be expressed mathematically by the following basic relationship: R=P x G, (1) where: R - professional risk (of occupational injury and/or illness); P -probability of occurrence of the unwanted event; G - severity of the maximum foreseeable consequence.

If the occurrence of an „explosion” type event (generated during specific operations with explosive materials carried out in a year) is expressed in terms of probability, and the undesirable consequences in terms of probability of death or injury by producing major/minor injuries (PdlM,m) (taking into account the presence of the human operator), then relation (1), in the case of individual risk, becomes: R

=P

P

,

E

, (2) where: PdlM,m - annual probability of death or injury from major / minor injuries;

Pexplosion - the annual probability of an explosion-type event occurring on a site intended for specific operations with explosive materials;

PdlM,m/explosion - probability of death or major/minor injury following an explosion-type event, given the human operator's exposure to the event;

Epersonal - personal human exposure to the occurrence of an explosion-type event on a site intended for specific operations with explosive materials „hours/year”.

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In the case of collective risk, applied to a group of people exposed to an explosion-type event, relation (2) becomes:

(3) where: Rgroup - collective risk when an explosion-type event occurs on a site intended for specific operations with explosive materials. Following the explanation of the term

(taking into account the theoretical aspects in the Note), relation (2), becomes:

where: Pd,lM,m 1/explosion - risk of death or injury from major/minor injury caused by overpressure and impulse; Pd,lM,m 2/explosion - risk of death from broken windows and destruction of buildings; Pd,lM,m 3/explosion - risk of death or injury through the production of major/minor injuries caused by the projection of fragments resulting from detonation;

Pd,lM,m 4/explosion - risk of death or injury through the production of major/minor injuries caused by the thermal effect.

Note: Applying the mathematical rule of adding 4 independent events (X1, X2, X3, X4) graphically visualized in figure 1, taking into account the occurrence probabilities of each one, it is obtained:

P(X1∪X2∪X3∪X4)=P(X1)+P(X1c∩X2)+P(X1c∩X2c∩X3)+P(X1c∩X2c∩X3c∩X4)=P(X1)+ P(X1c)P(X2)+P(X1c)P(X2c)P(X3)+P(X1c)P(X2c)P(X3c)P(X4)=P(X1)+(1-P(X1))P(X2)+(1-P(X1))

(1-P(X2))P(X3)+(1-P(X1))(1-P(X2))(1-P(X3))P(X4)

Figure 1. The grapho-analytical model for applying the mathematical rule of adding 4 independent events, taking into account the probabilities of each of them occurring

In the field of risk analyzes associated with explosion-type events caused by specific operations with explosive materials, the logarithmic scale is usually used to estimate the result indicator (see tables 1 and 2), because: the range of values specific to the area of interest for carrying out the risk estimation can include several orders of magnitude; lends itself very well to quantitative risk assessment; the principle of proportional logic is ensured, according to which multiplying the risk by a constant value leads to a constant separation (variation) of it.

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Table 1. Numerical scales used in quantitative risk assessment Numerical scale type

Hindi / Arabic

Roman

Logaritmic, version Percentage Decimal Scientific Engineering 0 0 % 0, 0000000001 10-10 1E-10

0,5 50 % 0, 000000001 10-9 1E-09

I 1 100 % 0, 00000001 10-8 1E-08

II 2 0, 0000001 10-7 1E-07 III 3 0, 000001 10-6 1E-06 IV 4 0, 00001 10-5 1E-05 V 5 0, 0001 10-4 1E-04 VI 6 0, 001 10-3 1E-03 VII 7 0, 01 10-2 1E-02 VIII 8 0, 1 10-1 1E-01 IX 9 1 100 1E+00 X 10 10 101 1E+01 100 102 1E+02 1.000 103 1E+03 10.000 104 1E+04

Table 2. Numerical scale configured based on logarithmic scale Fraction Scientific version Engineering version

Fraction

2/3

6,67 x 10-1 6,67E-01 1/10 1,00 x 10-1 1,00E-01

Small fraction 1/3.000 3,33 x 10-4 3,33E-04 7/100.000 7,00 x 10-5 7,00E-05

Extremely small fraction 1/100.000.000 1,00 x 10-8 1,00E-08 5/10.000.000.000 5,00 x 10-10 5,00E-10

2.2. Quantitative evaluation of the explosion risk generated following specific operations with explosive materials

Considering the previously mentioned technical aspects, in table 3 we highlight the risk assessment matrix that is based on the concept of compliance with the principle of logical proportionality, respectively. Risk assessment is a sequential process that involves both the quantitative risk estimation based on available data and information (accident history and statistics, test and trial results, technical-scientific information, safety data sheets, technical product specifications, experience and the technical expertise in the field of the experts), as well as the qualitative evaluation regarding the risk assessment taking into account the subjective aspects and the perception of the way of manifestation and generation of specific effects, according to table 4. Table 3.

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Table 4. Risk assessment matrix: direction of reducing P and G

Risk assessment

Qualitative Severity class, G Likelihood class, P Frequent Probable Ocasional Rare Unlikely Catastrophic M M M M Me Critical M M M Me Mi Average M Me Me Mi Mi Negligible Me Mi Mi Mi Mi

Quantitative 1 x 10-6 – estimation of annual probability of death value of the, Pdeces

Legend: M-high risk; Me-average risk; Mi-low risk Direction of reducing P and G

The exposure of people is a measure of the probability (0 < P < 1) that they will be present at the time of the explosion-type event, being expressed in the number of hours per year (in the case of the exposure of a single person), and in the case of several exposed persons, the number of hours in a year is multiplied by the number of these persons.

Table 5 shows the main mechanisms of damage through death or injuries (major or minor), as well as through material destruction, following the occurrence of an explosion-type event when carrying out specific operations with explosive materials, which can be grouped as follows:

- Overpressure and impulse (overpressure from the shock wave front);

- Structural response (destruction of buildings and shattering of windows with projecting resulting fragments);

- Debris (fragments resulting from the detonation of explosive materials, originating from: explosive products – primary fragments; construction materials of spaces intended for operations with explosive materials – secondary fragments; pieces of rock from formed craters – auxiliary debris);

- Thermal radiation (specific to explosives included in the division HD 1.3 - explosives that cause massive fires).

Between the explosives area and the office building

Next to the office building

Pressure and impulse Destruction of windows and building Debris

Thermal radiation

Inside the office building

Table 5. Highlighting the effects of the main damage mechanisms generated by the detonation of explosive materials Inside the space intended for operations with explosives

The effects and consequences of each previously mentioned impact mechanism occur successively, respectively, the danger that generates an explosion-type event inside the space intended for operations with explosive materials affects the structure of its building which is located at a certain distance from the building of offices, potentially affecting its structure, and consequently the human component present inside it.

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2.3. Criteria for the acceptability of the explosion risk generated during specific operations with explosive materials

In 1999, the DoD (Department of Defense in U.S.A) sponsored the development of risk criteria for use in the risk-based management of explosives. Initially, these criteria were to be used based on objective scientific evidence for decisions related to the disposition of explosives facilities within dedicated industrial sites. To support the development of these criteria, various data and information on risk acceptability have been collected from a wide variety of credible sources made available by authorities with powers and responsibilities in this regard.

Likewise, the answer to the question: „How safe is safe enough?” is an essential ingredient in establishing any risk criterion. Although the question is fundamental to achieving the practical goal of establishing risk criteria, it is also a somewhat philosophical question, in the sense that it requires and challenges decisionmakers to make subjective interpretations of the legal aspects that establish the applicable limit values, as well as of value limits specific to protected areas, also taking into account the practical experience in the field of solving the risk problem. Thus, a set of four risk criteria was developed for the management of explosion risk specific to operations with explosive materials (table 6), respectively:

Table 6. Risk limitation/reduction criteria depending on the human dimension and professional or civil affiliation of the exposure Risk for: Risk limitation/reduction criteria

Any worker (in the case of a single worker) (Pfanual) Limiting the maximum risk to the value of 1x10-4

All workers (in the case of a group of workers) (Efanual)

Risk reduction to 1x10-3 Acceptance of exceeding the value of 1x10-2 only for significant national needs

Any person (in the case of a single person) (Pfanual) Limiting the maximum risk to the value of 1x10-6

Public (in the case of a group of people) (Efanual)

Risk reduction to 1x10-5 Acceptance of exceeding the value of 1x10-3 only for significant national needs

Establishing the main scenarios for the disposition of explosive structures (PES) and exposure (ES) at the level of industrial sites intended for specific operations with explosive materials

The risk analysis must be carried out in a way that recognizes the mechanism of compliance with the mathematical legitimacy of „adding” the risk values taking into account its nature. In this sense, the risk-based disposition of explosive structures (PES) and exposure structures (ES) within an industrial site intended for carrying out specific operations with explosive materials, is done by ensuring that all PES-type structures that expose a structure of ES type at a significant „individual risk – Rindividual” are taken into account in the analysis and by evaluating the „group risk”. Thus, the „group” for a PES is considered to be made up of all persons exposed to a significant risk from that PES, and the „group risk – Rgroup” is the total risk for all individuals in the group. In order to determine the „group risk”, the „individual risks” for all individuals in the group must be determined first (in addition to these individual risks, the specific risks of people from other PESs will also be taken into account). „Group risk” is determined by adding up all „individual risks”.

Conducting risk-based siting is a complex process, and adding a single PES or ES to an area with multiple such structures can cause a multiplicative effect on the overall risk profile, requiring determination of the effect the new PES or ES has on the general situation existing at a given time.

For the complete definition of event scenarios within the framework of risk analyses, which are subject to the involvement of explosive materials, specific data and relevant information necessary for the full characterization of explosive structures (PES) and exposure structures (ES) must be used, respectively: size, shape, type and construction category, orientation, type of explosive, classification in the hazard class and compatibility group of the explosive, the net amount of explosive stored/used, the type of activity carried out at the level of the exposed structure, the number of people present and the annual exposure (in hours) at the level of the exposure structure.

Taking into account the above, below we highlight the main scenarios for the disposition of explosion structures (PES) and exposure structures (ES), at the level of an industrial site intended for specific operations with explosive materials, respectively:

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I. Scenario no. 1 of the arrangement of two distinct structures (ES and PES)

Figure 2. The risk-based disposition of two distinct structures of type PES and ES

In order to safely place an ES-type structure in the case shown in figure 2, the following work process algorithm must be followed:

aI If the ES is procedurally dependent on the PES, then the following procedural steps are followed:

Step 1aI: The individual risk (Rindividual) generated by the PES is calculated for each person in the ES;

Step 2aI: If the maximum Rindividual calculated in step 1aI does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aI: The summation of the values related to all the individual risks calculated in step 1aI to determine the group risk (Rgrup);

Step 4aI: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

bI. If the ES is procedurally independent from the PES, then the following procedural steps are followed:

Step 1bI: The individual risk (R individual) generated by the PES is calculated for each person in the ES;

Step 2bI: If the maximum Rindividual calculated in step 1bI does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bI: The summation of the values related to all the individual risks calculated in step 1bI to determine the group risk (Rgrup);

Step 4bI: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

For the safe placement of a PES type structure, the same work algorithm is applied, respecting the process reasoning.

II. Scenario no. 2 of arranging several exposure structures in relation to a single explosion structure (ES 1, ES 2, ES 3 and PES)

Figure 3. Risk-based layout of four distinct structures (ES1, ES2, ES3 and PES)

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In order to safely place several ES-type structures in the case shown in figure 3, the following work process algorithm must be followed:

aII. If the three ES structures are procedurally dependent on the PES, then the following procedural steps are followed:

Step 1aII: Calculate the individual risks (R1,2,3individual) generated by PES for each person in ES1, ES2 and ES3;

Step 2aII: If the maximum R 1,2,3 individual calculated in step 1a does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aII: The summation of the values related to all the individual risks calculated in step 1aII to determine the group risk (Rgrup);

Step 4aII: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

bII. If the three ES structures are procedurally independent of the PES, then the following procedural steps are followed:

Step 1bII: Calculate the individual risk (R1,2,3individual) generated by PES for each person in ES1, ES2 and ES3;

Step 2bII: If the maximum Rindividual calculated in step 1bII does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bII: The summation of the values related to all the individual risks calculated in step 1bII to determine the group risk (Rgrup);

Step 4bII: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

For the safe placement of a PES type structure, the same work algorithm is applied, respecting the process reasoning.

III. Scenario no. 3 of the arrangement of several explosive structures in relation to a single exposure structure (PES1, PES2 and ES)

Figure 4. Risk-based layout of the three distinct structures (PES1, PES2 and ES)

In order to safely place an ES-type structure in the case shown in figure 4, each PES will be evaluated individually following the following work process algorithm:

aIII 1. If the ES is procedurally dependent on PES1, then the following procedural steps are followed: PES1

Step 1aIII1: The individual risks (Rindividual1,2) generated by PES1 and PES2 for each person in the ES are calculated;

Step 2aIII1: If the maximum Rindividual1.2 calculated in step 1aIII 1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aIII1: The summation of the values related to all the individual risks calculated in step 1aIII 1 to determine the group risk (Rgrup);

Step 4aIII1: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

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bIII 1. If the ES is procedurally independent of PES1, then the following procedural steps are followed:

Step 1bIII1: The individual risks (Rindividual1,2) generated by PES1 and PES2 for each person in the ES are calculated;

Step 2bIII1: If the maximum Rindividual 1.2 calculated in step 1bIII1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bIII1: The summation of the values related to all the individual risks calculated in step 1bIII1 to determine the group risk (Rgrup);

Step 4bIII1: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

aIII 2. If the ES is procedurally dependent on PES2, then the following procedural steps are followed: PES2

Step 1aIII2: The individual risks (Rindividual1,2) generated by PES1 and PES2 for each person in the ES are calculated;

Step 2aIII2: If the maximum Rindividual1.2 calculated in step 1aIII2 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aIII2: The summation of the values related to all the individual risks calculated in step 1aIII 2 to determine the group risk (Rgrup);

Step 4aIII2: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

bIII 2. If the ES is procedurally independent of PES2, then the following procedural steps are followed:

Step 1bIII2: The individual risks (Rindividual1,2) generated by PES1 and PES2 for each person in the ES are calculated;

Step 2bIII2: If the maximum Rindividual1.2 calculated in step 1bIII1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bIII2: The summation of the values related to all the individual risks calculated in step 1bIII1 to determine the group risk (Rgrup);

Step 4bIII2: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

For the safe placement of a PES type structure, the same work algorithm is applied, respecting the process reasoning.

IV. Scenario no. 4 of the arrangement of several explosive structures in relation to several exposure structures (PES1, PES2, ES1, ES2 and ES3)

In order to safely place several ES-type structures in the case shown in figure 5, each PES will be evaluated individually in relation to these (ES-type) structures following the following work process algorithm:

Figure 5. Risk-based layout of the five distinct structures (PES1, PES2, ES1, ES2 and ES3)

aIV 1 . If ES1, ES2 and ES3 are procedurally dependent on PES1, then the following procedural steps are followed:

PES1

Step 1aIV1: Both the individual risk (Rindividual1) generated by PES1 for each person in ES1 and ES2 and the individual risk (Rindividual2) generated by PES2 for each person in ES2 and ES3 are calculated;

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Step 2aIV1: If the maximum Rindividual1.2 calculated in step 1aIV1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aIV1: The summation of the values related to all the individual risks calculated in step 1aIV1 to determine the group risk (Rgrup);

Step 4aIV1: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

bIII 1 . If ES1, ES2 and ES3 are procedurally independent of PES1, then the following procedural steps are followed:

Step 1bIV1: Both the individual risk (Rindividual1) generated by PES1 for each person in ES1 and ES2 and the individual risk (Rindividual2) generated by PES2 for each person in ES2 and ES3 are calculated;

Step 2bIV1: If the maximum Rindividual1.2 calculated in step 1bIV1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bIV1: The summation of the values related to all the individual risks calculated in step 1bIV1 to determine the group risk (Rgrup);

Step 4bIV1: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

aIV 2 If ES1, ES2 and ES3 are procedurally dependent on PES1, then the following procedural steps are followed: PES2

Step 1aIV2: Both the individual risk (Rindividual1) generated by PES1 for each person in ES1 and ES2 and the individual risk (Rindividual2) generated by PES2 for each person in ES2 and ES3 are calculated;

Step 2aIV2: If the maximum Rindividual1.2 calculated in step 1aIV2 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-4, then the risk is acceptable;

Step 3aIV2: The summation of the values related to all the individual risks calculated in step 1aIV2 to determine the group risk (Rgrup);

Step 4aIV2: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-3, then the risk is acceptable.

bIV 2. If the ES is procedurally independent of PES2, then the following procedural steps are followed:

Step 1bIV2: Both the individual risk (Rindividual1) generated by PES1 for each person in ES1 and ES2 and the individual risk (Rindividual2) generated by PES2 for each person in ES2 and ES3 are calculated ;

Step 2bIV2: If the maximum Rindividual1.2 calculated in step 1bIV1 does not exceed the risk limitation/reduction criteria Pf (table 6) of 1x10-6, then the risk is acceptable;

Step 3bIV2: Însumarea valorilor aferente tuturor riscurilor individuale calculate la pasul 1bIV1 pentru determinarea riscului de grup (Rgrup);

Step 4bIV2: If Rgrup does not exceed the risk limitation/reduction criteria Ef (table 6) of 1x10-5, then the risk is acceptable.

For the safe placement of several PES structures, the same work algorithm is applied, respecting the process reasoning.

3. Discussion and conclusion

In this paper, a methodology for quantitative assessment of explosion risk was presented, which is based on the specialized use of the concept of risk specific to industrial sites intended for operations with explosive materials.

In the field of risk analyzes associated with explosion-type events caused by specific operations with explosive materials, the logarithmic scale is usually used to estimate the result indicator, because: the range of values specific to the area of interest for carrying out the risk estimation can include several orders of size; lends itself very well to quantitative risk assessment; the principle of proportional logic is ensured, according to which multiplying the risk by a constant value leads to a constant separation (variation) of it.

The concept of risk assessment is a sequential process that involves both the quantitative assessment of risk based on available data and information (accident history and statistics, test and trial results, technicalscientific information, safety data sheets, technical product specifications, the experience and technical expertise in the field of the experts), as well as the qualitative evaluation regarding the risk assessment taking into account the subjective aspects and the perception of the way of manifestation and generation of specific effects.

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The main mechanisms of damage through death or injuries (major or minor), as well as through material destruction, following the production of an explosion-type event when carrying out specific operations with explosive materials, which can be grouped as follows: Overpressure and impulse (overpressure from shock wave front); Structural response (destruction of buildings and shattering of windows with projecting resulting fragments); Debris (fragments resulting from the detonation of explosive materials, originating from: explosive products - primary fragments; construction materials of spaces intended for operations with explosive materials - secondary fragments; pieces of rock from formed craters - auxiliary debris); Thermal radiation (specific to explosives included in the division HD 1.3 - explosives that cause mass fires).

The risk analysis should be carried out in a way that recognizes the mechanism of compliance with the mathematical legitimacy of „adding” the risk values taking into account its nature. In this sense, the risk-based disposition of explosive structures (PES) and exposure structures (ES) within an industrial site intended for carrying out specific operations with explosive materials, is done by ensuring that all PES-type structures that expose a structure of ES type at a significant „individual risk – Rindividual” are taken into account in the analysis and by evaluating the „group risk”.

For the complete definition of event scenarios within the framework of risk analyses, which are subject to the involvement of explosive materials, specific data and relevant information necessary for the full characterization of explosive structures (PES) and exposure structures (ES) must be used, respectively: size, shape, type and construction category, orientation, type of explosive, classification in the hazard class and compatibility group of the explosive, the net amount of explosive stored/used, the type of activity carried out at the level of the exposed structure, the number of people present and the annual exposure (in hours) at the level of the exposure structure.

In the case of the quantitative evaluation of the explosion risk generated following the detonation of explosive materials, the estimation of the manifestation of hazards identified through the associated risk factors, is carried out on the basis of established scientific calculation algorithms and grapho-analytical models, taking into account databases substantiated data from the results of experimental research regarding the characterization of the effects and consequences related to typical event scenarios with different exposures at predefined distances, in accordance with standard safety criteria, using the technique of extrapolating the effects of the far field to the area near the epicenter of the explosion (near field), while of course retaining the size of the proportion of the modeled effect, characteristic of the simplified fatality mechanism caused by an explosion-type event.

References

[1] Băbuţ M.C., Băbuţ G., Moraru R., 2010

An expeditious methodology for gravity index detemination in the case of major accidents, Proceedings of the 10th International Multidisciplinary Scientific GeoConference - SGEM 2010, Volume II, pp. 395-403, Albena, Bulgaria, 2026.06.2010.

[2] * * *, 2003

Gouvernment decision no. 95/2003 regarding the control of activities presenting risks of major accidents which involve dangerous substances (in romanian), Official Gazette of Romania, Part I, no. 120 / 25.02.2003

[3] * * *, 2007

Gouvernment decision no. 804/2007 regarding the control of major accident risks which involve dangerous substances (in romanian), Official Gazette of Romania, Part I, no. 539/08.08.2007

[4] * * *, 2016

The Law 126/1995 on the control of major accident risks which involve dangerous substances (in romanian), Official Gazette of Romania, 18 April 2016.

[5] European Parliament and Council, 2012

The 2012/18/UE Directive from 4th July 2012 regarding the control of major accident risks which involve dangerous substances, which modifies and later repeals the Directive 96/82/CE of the Council.

[6] Băbuţ G., Moraru R., Cioca L.I., Băbuţ M.C., 2009

Behavioural safety and major accident hazards, Proceedings of the 15th International Scientific Conference „The Knowledge Based Organization”, section: Management, pp. 38-42, Land Forces Academy Sibiu, Romania, 2628.11.2009

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[7] * * *, 2009

Decision 519 / 2009 regarding the establishment of an unique identification and traceability system for civil explosives (in romanian)

[8] * * *, 2016

Decision 197 / 2016 regarding the establisment of regulations for commercialization and control of civil explozives (in romanian)

[9] General Inspectorate for Emergency Situations Bucharest

Methodology for analyzing the industrial risks which involve dangerous substances (in romanian), www.igsu.ro/seveso.htm

[10] Joy J., Griffiths D., 2008

National minerals industry safety and health risk assessment guideline, version 3, March 2008, MCA and MISHC, Australia, www.planning.nsw.gov.au

[11] * * *, 1995

The Law 126/1995 on the regime of explosive substances with subsequent amendments and additions and Norms T of application (in romanian)

[12] Moraru R.I, Băbuţ G.B., Cioca L.I., 2009

Knowledge Based Hazard Analysis Guidelines for Operational Transportation Projects, Proceedings of the 15th International Conference the Knowledge Based Organization: Management, Volume 2, pp. 117-122, Sibiu, Romania, 2628.11.2009.

[13] Romanian Parliament, 2006

Occupational safety and health law no. 319/2006, Official Gazette of Romania, Part I, no. 646 / 26.07.2006

[14] Vasilescu G.D., 2008

Unconventional methods of occupational risk analysis and assessment (in Romanian), ISBN 978-973-88590-0-5, INSEMEX Publishing House, 2008.

[15] Băbuţ M.C., 2010

Structural elements of the conceptual framework of risk evaluation for the emplacements under the onsight of Seveso II Directives (in romanian), Journal „Calitatea - acces la succes”, no. 7-8/2010, pag. 81-87.

[16] Băbuţ M.C., 2011

European and national legislation framework on control of major accidents risks which involve dangerous substances (in romanian), Journal „Calitatea - acces la succes”, vol. 12, nr. 5(124)/2011, pag. 66-74.

This article is an open access article distributed under the Creative Commons BY SA 4.0 license. Authors retain all copyrights and agree to the terms of the above-mentioned CC BY SA 4.0 license.

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ANALYTICAL TOOL FOR MODELING THE DISPERSION OF MATERIAL FRAGMENTS GENERATED BY EXPLOSIVES BLASTING

Victor Gabriel VASILESCU 1 , Roland Iosif MORARU2 *

1 University of Petroșani, Petroșani, Romania

2 University of Petroșani, Petroșani, Romania, roland_moraru@yahoo.com

DOI: 10.2478/minrv-2022-0032

Abstract: The unprecedented increase, in the last decades, of risks, hazards and threats to the vital objectives of states and international bodies, simultaneously with the increase in their number and vulnerability, led to the sedimentation and establishment of the new concept generically called critical infrastructure. The sites where explosives are manufactured, stored and used can be considered as critical infrastructures, especially taking into account the criterion of the extent, the amplitude of the effects of an explosion produced but also the possible severity on the economic activity, the public and the environment. From this perspective, this article presents an analytical tool for modeling the dispersion of material fragments generated by the detonation of explosives based on the quantification of the impact of the throwing speed and the mass of the material fragments, taking into account the type of material and the loading conditions of the resulting debris. The developed tool resorts to the use of a statistical function, namely the probability density function for modeling different types of fragments resulting from explosion-type events

Keywords: explosives, blasting, fragment dispersion, debris, probability density, kinetic energy

1. Introduction

Research efforts in the field of explosion risk protection, especially for strategic buildings and infrastructures, are not new in the last decades, with several studies being carried out by various research teams with the support of field experiments and/or numerical methods , studies based on different approaches [1, 2, 3].

The approach based on the study of blast-resistant structures is of interest for various types of engineering applications. Several researches have been carried out especially on the structural design and mechanical analysis [4] of blast-resistant and protective structures that could properly withstand blast waves [5].

In general, mitigation measures that can be adopted for explosion protection can be categorized as "nonstructural" as well as "structural". In the first case, "non-structural" mitigation measures can be either passive or active. Their purpose is to address the reduction of the probability of occurrence of a certain accidental scenario and thus to minimize the intensity of a possible hazardous event that may occur. An overview of blast mitigation measures for coastal structures was presented in the paper “Characterization of accidental scenarios for offshore structures”. Thus, in this work, reference is made to different types of explosion-resistant protective walls. It has been shown that, for example, blast-resistant walls are usually made of steel and/or reinforced concrete, or can be made of prefabricated slabs. Furthermore, explosion-proof walls isolate nonhazardous areas and therefore minimize the effects of explosive charges [6].

The explosion severity approach to the consequence gravity of an explosion is represented by the socalled "Targets", which in this context represent the targets vulnerable to potential explosive events and indicate places that can be selected by terrorist attacks in their effort to maximize the effects, [7] including here the effects of the mass media [8]. These may include critical infrastructure, key resources or key assets that are typically without adequate protection and are open to the public by their purpose. However, explosion scenarios are well known to represent unexpected events that can lead to catastrophic consequences [9].

* Corresponding author: Roland Iosif Moraru, Prof. PhD. Eng., University of Petroșani, Petroșani, Romania, contact details (University st. no. 20, Petroșani, Romania roland_moraru@yahoo.com)

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The approach based on numerical models: in the paper „Numerical Analysis of the BlastWave Propagation due to Various Explosive Charges", Figuli et al. presents a numerical model for the analysis of the blast wave propagation mode [10]. Based on the research carried out in the last decades, different analytical solutions can be found in the specialized literature [11]. Many other influencing parameters are then involved in the empirical description of an expected blast wave, which is confirmed and may further interact with the soil or affected surfaces [12].

Also in the same approach, in the paper "Characterizing Explosive Effects on Underground Structures", A. H. Chowdhury, T. E. Wilt, present numerical analyzes to characterize the effects that explosions close to the ground surface and in contact with the ground surface have on underground structures, with emphasis on tampered improvised explosive devices [13].

Empirical and experimental information are aided by various numerical analysis techniques with appropriate assumptions, idealizations and simplifications that have been implemented in various restricteduse codes (e.g. defense-related and commercially available computer codes such as ABAQUS and LS-DYNA). Bangash, (2001) considers that attempting to quantify or predict damage modes by analytical methods is extremely difficult [14] and McVay (1988) carried out theoretical and experimental studies on the damage of concrete structures subjected to air blast from hollow and cased explosive charges. Empirical and experimental data were used to estimate whether local damage would occur. It was found, however, that the damage results from the small-scale tests were difficult to scale up to the actual damage states observed in the large-scale tests. Furthermore, damage predictions based on empirical equations did not always predict well small-scale test observations [15].

2. General aspects regarding explosion risk modeling

Explosive substances, in the sense of the law, mean explosives themselves, simple explosive mixtures and pyrotechnic mixtures, means of initiation, ignition aids, as well as any other substances or mixtures of substances intended to give rise to instantaneous chemical reactions, with release of heat and gases at high temperature [16, 17, 18].

The modeling of the risk of projecting material fragments following the detonation of explosive materials with a harmful effect on the human component and/or on nearby industrial/civilian objectives is based on the quantification of the impact of the throwing speed and the mass of the material fragments, taking into account the type of material (steel or concrete) and loading conditions of the resulting debris. Models developed to generate trajectory calculations for ranges of mass, launch angles, and launch velocity based on Monte-Carlo simulations are sensitive to the predetermined ranges assigned to each trajectory variable, requiring long intervals of time and IT resources as appropriate, and in the end a detailed result is obtained, based only on assumptions.

If results of explosives testing programs, relevant information on accident history involving hazardous substances such as explosives, and data validated through various simulations are available, fast-running risk analysis models can be created specific, without the need to use physical-mathematical tools (trajectories, resistance equations) in real time for each fragment. In this sense, the paper highlights an analytical tool for using a statistical function, namely the probability density function for modeling different types of fragments resulting from explosion-type events.

Following the occurrence of an explosion-type event, thousands of individual fragments characterized by their own mass and velocity parameters can be generated, resulting in individual energy values that can be taken into account in a quantitative risk assessment, by grouping them into ten distinct classes, so: Class 1 represents fragments with the highest kinetic energy and/or mass, and class 10 represents fragments with the lowest kinetic energy and/or mass. This class system was first developed for the kinetic energy ranges, and the average size masses for steel and concrete fragments were calculated for each class taking into account terminal velocity. Each class has a range of about half an order of magnitude expressed in terms of kinetic energy, the same approximation being valid for the mass parameter.

Table 1 represents the ten distinct classes of the kinetic energy parameter, with the maximum, mean, and minimum values for each class, as well as the average mass for each detached fragment (depending on material type) associated with the energy classes.

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Table 1. The distinct classes of the kinetic energy parameter corresponding to each material fragment associated with the energy classes Energy class

Class 1 Class 2 Class 3 Class 4 Clasa 5 Class 6 Class 7 Class 8 Class 9 Class 10

Kinetic energy Minimal 100k 30k 10k 3k 1k 300 100 30 10 3

Kinetic energy Average 173k 54k 17k 5k 1,7k 547 173 54 17 5

Kinetic energy Maximal ≥ 300k 100k 30k 10k 3k 1k 300 100 30 10

Medium fragments from steel (kg) 16.19 6.75 2.87 1.20 0.51 0.214 0.09 0.038 0.017 0.006

Concrete medium fragments (kg) 34.20 14.28 6.07 2.54 1.07 0.45 0.19 0.08 0.03 0.016

3.

The modeling of the design effect of debris that can affect the human component and/or the resistance structure of installations and buildings located on a site intended for specific operations with explosive materials is based on the quantification of the impact characterized by the throwing speed and the mass of material fragments resulting in following the detonation of explosive substances, taking into account the type of material (steel or concrete) and the loading conditions of the resulting debris.

Models developed to generate trajectory calculations for ranges of mass, launch angles, and launch velocity based on Monte-Carlo simulations are sensitive to the predetermined ranges assigned to each trajectory variable, requiring long intervals of time and IT resources as appropriate, and in the end a detailed result is obtained, based only on assumptions. If results of explosives testing programs, relevant information on the history of accidents involving hazardous substances such as explosives, and data validated by various simulations are available, fast-running models for risk analyzes can be created specific, without the need to use physical-mathematical tools (trajectories, resistance equations) in real time for each formed fragment.

To represent different types of patterns of material fragments resulting from detonation, the probability density functions (fig. 1) can be designed with different levels of complexity, considering the need to faithfully reproduce the patterns of fragments resulting during testing, being described of appropriate mathematical expressions that determine the specific components of variation, respectively:

• Component 1- f1,2(r) which reproduces the shape of the trajectory from the origin of the explosion outwards in any radial direction (this essential component determines how far from the origin the fragments are thrown as well as the peak density range);

• Crossed omponent 2 – f3(θ) produces the shape of a function when moved radially at a constant interval from the origin (called the cross or azimuth direction).

Normal probability distributions (uniform in all directions from the origin i.e. without azimuthal variation) are commonly used to model the design effect uniformly or randomly distributed in all directions around the epicenter of an explosion, such as fragments of material detached from a roof, which are thrown up and scattered, or the debris from the walls of a building structure (Gaussian - Bivariate Normal distribution), according to figure 1. a. The BVN type probability density function is useful for normal scenarios where little data is available, assuming that the larger hazardous debris is close to the explosion epicenter (origin).

However, there are also situations where, following tests with explosives, multiple fragments of material resulting from detonation (primary from explosives and secondary from structural walls) are projected outwards outside the area the epicenter of the explosion. In this case, a BVN-type distribution model used in such scenarios is characterized by a probability density function that tends both to overestimate the level of prediction of fragments located near the epicenter of the explosion (near the origin) and to underestimate the density of fragments within the same class intervals.

Thus, for modeling the throwing effect, in the case of material fragments that are mostly located outside the area in the vicinity of the explosion epicenter, the total amount of these fragments is kept constant, and the peak of component 1 (which reproduces the shape of the trajectory from the origin of the explosion to outward in any radial direction) of the distribution function is forced outward according to the throw tendency, resulting in a new function component having a toroidal shape (if azimuthal variation is not taken into account), according to Figure 1.b.

Modeling the dispersion of material fragments resulting from the detonation of explosive materials. types of density functions

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a. Gaussian distribution model –Bivariate Normal (BVN)

b. Toroidal distribution model without azimuthal variation

c. Distribution model with nonzero azimuthal variation

Figure 1. Typology of probability distribution models used to model the design effect of fragments of material resulting from the detonation of explosives

The outward forcing of the maximum density range of the projected fragments generates a „volcano” looking variation shape, with the density of fragments in the vicinity of the epicenter being maintained at a non-zero value.

For the most truthful modeling of the design effect of material fragments resulting from the detonation of explosive materials, the new resulting model is used, with non-zero azimuthal variation, according to which the amplitude along the central direction varies according to the class interval of the fragments, and the standard deviation is a constant angle at all these intervals (fig. 1.c).

From a comparative point of view, the two types of curves, respectively BVN and the toroidal type, are characterized by the fact that the areas around them are the same, which means that from a graphical point of view, the same total mass of material fragments resulting from the detonation is represented (fig. 2).

The new function component (fig. 3.a) that generates the toroidal shape model is controlled by three parameters a, b and c that can be modified to represent the variation in the size of the fragments, the type of material of the fragments and their provenance (fragments from structural walls or roof), respectively:

a - is the ratio between the position in the horizontal plane of the peak of the probability curve (Xmax) and the maximum distance in the same horizontal plane (maximum throw) of the density of the material fragments to be modeled (XMT); b - is the ratio between the probability value of the probability density at the point of origin (Y0) and the maximum value of the probability density (Ymax); c - represents the percentage of the area under the probability curve, delimited between the origin and the peak.

Bi-Variant Normal distribution curve

Y, Probability density

Toroidal distribution curve

X, Throw distance

Figure 2. The two types of curves related to the probability distributions used, (BVN and the toroidal type)

In the case of explosive charges located in the central area in parallelepiped buildings, the density of the fragments generated by the detonation is strongly influenced by the azimuth (the fragments coming from the walls of the structure tend to go straight out and not in the corners), according to figure 3. b. This effect is so pronounced in some event scenarios that using a probability distribution with zero azimuthal (cross) variance can result in severe underestimation of fragment density and maximum throw distances along the normal direction.

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This effect is encountered both in parallelepiped buildings and in blast event scenarios involving vehicles, reinforced structures, and explosive stacking and storage configurations. When using the distribution function model, the value of the standard deviation, σ is a measure of the radial dispersion of the material fragments under consideration, which can be determined using the limiting value of the maximum design distance. In the case of primary and secondary material fragments, the maximum dispersion is equal to 3σ, and for fragments from the crater formed as a result of the explosion, the maximum dispersion is 4σ. These values are based on empirical data and information from the analysis of explosives tests.

When using the distribution function model (e.g. Gaussian normal distribution) taking into account the azimuthal variation, the value of the standard deviation, σ is a measure of the angular dispersion of the analyzed material fragments, which can be determined using the limit value of this value.

a. Details of the new function component

b. Shape and dispersion (fourfoil-shaped) of material fragments

Figure 3. Detailing the probability density function and the dispersion mode of fragments

4. Derivation of probability density functions

The probability density of material fragments resulting from the detonation of explosives is characterized as a function of the range of the throw distance (r) and the scatter angle (θ) along the direction normal to the wall of the structure. Both the distance r and the angle θ are treated independently according to the mathematical model associated with the fragment projection effect (1): ��������1,2 ����3 = ����1,2 (����) ∗ ����3 (����), (1)

Determining the function f1(r) ����1 (����) = A1 + A2 r + A3 ���� 2 + A4 ���� 3 , (2) where the coefficients are determined from the initial conditions: ����1 (0) = Y0 ; ����1 (R Y������������ ) = Ymax ; ����1, (0) = 0 ; ����1, �R Y������������ � = 0; unde X

= aXMT; Y0=bYmax; S1=cStotal (Stotal=0,9973, for a maximum throw distance of 3-σ). From the initial conditions it follows:

(3)

required area bounded by the f1(r) curve in the range unfolded from the origin to the peak is equal to 0.9973c, and to satisfy this requirement, the area under the distribution curve is first calculated using the values from A1, A2, A3 and A4 using the arbitrary value of Ymax, after which these values are then normalized using Eq. (4):

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With relation (4), the normalized values A1ʹ, A2ʹ, A3ʹ and A4ʹ are calculated, and S1 is determined by integrating the function f1(r), on the domain delimited by r=[ 0, R Y������������ ], respectively: S1 = ∫ ����1 (����)�������� = ∫ (A1 +A2 r+A3 ���� 2 +A4 ���� 3 )�������� =A1 R Y������������ + A2 2 R Y������������ 2 + A3 3 R Y������������ 3 + A4 4 R Y������������ 4 ����=RY������������ ����=0 ����=RY������������ ����=0 (5)

To prevent slope discontinuity at the peak of the distribution, using the fitting polynomial described earlier is extended beyond the peak of the distribution by a percentage d(%), of the distance from the peak to the maximum throw interval, as set by user input, the value of d is currently set to 10%, in which case the adjusted range delimitation is done for r=[0, R Y������������ +d*(RMT- R Y������������ )] .

The second branch of the distribution function is explained by an exponential type model, of the form: ����2 (����) = ����1 ���� ����2�����−RY������������ +0,1�RMT −RY������������ �� , (6)

The determination of the two coefficients k1 and k2 is done respecting the following conditions: f1(r) = f2(r), for r = [ 0, R Y������������ +0,1*(RMT-R Y������������ )]; the area under the curve f2(r), for r = [R Y������������ +0,1*(RMT- R Y������������ ), RMT] represents the true density of fragments projected at distance RMT. From the first condition it follows that k1=Ymax, for r = [0, R Y������������ +0,1*(RMT- R Y������������ )] To apply the second condition and to determine k2, the area under the f1(r) curve from the center to r = [R Y������������ +0,1*(RMT-R Y������������ ), RMT] . Taking into account both coefficient scaling and domain expansion, this area is expressed as: S����1 = ∫ ����1 (����)�������� = ∫ (A1 +A2 r+A3 ���� 2 +A4 ���� 3 )�������� ����=RY������������ +0,1∗(RMT RY������������ ) ����=0 ����=RY������������ +0,1∗(RMT RY������������ ) ����=0 (7) S����1 = A1 �R Y������������ +0,1 ∗�R MT R Y������������ �� + A2 2 �R Y������������ +0,1 ∗�R MT R Y������������ ��2 + A3 3 �R Y������������ +0,1 ∗ (R MT R Y������������ )�3 + A4 4 �R Y������������ +0,1 ∗ (R MT R Y������������ )�4 (8)

The area under the curve f2(r), for r = [R Y������������ , RMT] is given by the expression : S����2 =0,9973 S����1 , (9) The coefficient k2 is determined so that: ∫ ����2 (���� )�������� =S����2 RMT ����=RY������������ +0,1∗(RMT RY������������ ) , (10) S����2 = �R Y������������ +0,1 ∗ (R MT R Y������������ ) ����2 ����� ����2 �RMT −RY������������ −0,1�RMT−RY������������ ��

Finally, the probability density function f1,2(r) is of the form: ����1,2 (����) = � ����1 , ������������ ���� = �0,R Y������������ � ����2 , ������������ ���� = �R Y������������ ,R MT �, (11)

Determining the function f3(

θ)

The variation of the probability density as a function of the angle θ to the wall normal direction of the structure is modeled using a normal distribution with the center located on the wall normal direction and the standard deviation σθ. The value of σθ is determined from the results of tests carried out on different amounts of explosives and types of material specific to resistance structures (concrete or steel). Also, the distance along the transverse arc is Rθ, and the standard deviation expressed as a distance is Rσθ Thus, the function f3(θ) has the form: , (12)

To preserve the relative amplitudes of the downward variation of the probability density along the central direction, it is desirable that the angular variation of the probability density be a function of the variable θ. This is done by using a constant, characteristic value of R in the function expression f3(θ). Thus, the centroid of the

Revista Minelor – Mining Revue vol. 28, issue 4 / 2022 ISSN-L 1220-2053 / ISSN 2247-8590 pp. 70-78

facing distribution Rc, is selected as the constant range to use in the angular calculation and f3(θ), becomes:

Figure 4 shows the results of an example of modeling the design effect of fragments of material resulting from the detonation of explosive materials, using the previously defined probability distributions, characterized by the following data: a=0,33; b=0,038; c=50%; d=10%; XMT=579m; σ=200. In each figure, the zero point located on the direction normal to the wall of the structure is identified by a circle.

Figure 4. Results of modeling the throw effect of material fragments in the wake detonation of explosive materials

The results of the computer modeling presented graphically in figure 4 confirm the principles underlying the configuration of probability density functions, respecting the conditions imposed by mathematical laws, in close correlation with the most faithful reproduction of reality regarding the analysis of event scenarios when explosive materials are involved, from the perspective of evaluating the design effect of fragments of material resulting from the detonation of these types of products.

5. Assessment of the degree of injury following the impact with material fragments resulting from the detonation of explosive materials

The graph-analytical tool for assessing the degree of damage following the impact with material fragments resulting from the detonation of explosive materials is based on the use of the simplified mechanism of fatality caused by an event of the explosion type following the detonation of explosive materials (MSFEXP) whose particular mode of application is represented graphically in figure 5. Within the hazard mechanism generated by the dispersion of material fragments, highlighted in the MSFEXP model, customized for the case of this scenario (fig. 5), the parameter Pd/e, material fragments can reach a value of 1.0 if the manifestation of the explosiontype event takes place in the plateau area, the transition area being non-existent because X1= X2. Also, Pd/e, material fragments is equal to 1.0 if the ES-type exposure structure is located from the PES-type explosive structure at a distance less than twice the radius of the crater formed by the detonation of the explosive materials.

Within this model Pd/e, fragmente materiale represents the probability of lethal damage to a person, following the impact of hitting with a material fragment resulting from the detonation of explosive materials. Similarly, using the methodological reasoning of the model, the probabilities of occurrence of major injuries can be determined (Pmajl,material fragments) and of minor injuries (Pminl,material fragments) caused by projected material debris.

The number of fragments that can hit an ES exposure structure is quantified in the form of a density of material pieces, expressed in fragments/unit area, which together with their final velocity and mass, lead to the determination of the related kinetic energy value.

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P1d/e it is usually equal to 1.0 for material fragments

Zona MSFEXP

X1=X2 = 2 x radius of the crater from where material fragments resulted

In practice P2d/e=1 for distances greater than X1

Logic-standard Zone

Scaled distance

Figure 5. The simplified fatality mechanism customized for the effect of dispersion of material fragments

6. Conclusions

The fractional damage to the structure that remains intact after an explosive event is a function of the equivalent net explosive weight and the type of building. In this regard, the fractional damage (characterized by a value between 0 and 1) of each component (roof, front wall, side walls and rear wall) is determined by comparing the net explosive weight equivalent to the damage limits at the lower and upper limits for different types of structures.

The analytical tool for modeling the dispersion of material fragments from explosions was configured based on the explosion risk model, using established probability density functions for evaluating the design effect of material fragments following the detonation of explosive materials (Gaussian distribution, toroidal distribution without variation azimuthal, distribution with non-zero azimuthal variation).

The number of fragments that can hit an exposure structure is quantified in the form of a density of material pieces, expressed in fragments/unit of area, which together with their final velocity and mass, lead to the determination of the value of the related kinetic energy.

The material fragments that have different angles (large and small) of dispersion, as well as those that make a side impact, have their own final velocities at the moment of hitting the exposure structure, while for the concrete material fragments and those from the crater formed after explosion, the kinetic energy class is determined according to their mass, and in the case of steel fragments, a higher energy class is chosen due to their increased speed from the moment of impact.

References

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[4] Ngo T., Mendis P., Gupta A., Ramsay J., 2007

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