Sound and light in school environments development of a preliminary parametric design approach

SOUND AND LIGHT IN SCHOOL ENVIRONMENTS

Development of a preliminary parametric design approach Politecnico di Torino - Facoltà di Architettura Master’s degree course in Architettura Costruzioni e Città Gianmarco Paglierani s217956 Supervisor: Prof. A. Astolfi Advisors: Prof. A. Pellegrino - Dr. M. Turrin Dr. G. E. Puglisi - Dr. L. Shtrepi - Dr. L. Giovannini Company Tutors: Eng. G. Bonfante - Arch. A. Griginis

Master’s Thesis, July 2017

Preface This thesis is the final project submitted for completion of a Master’s degree in Architecture “Costruzione e Città” at the Politecnico di Torino. The search path started last September 2016 at the TU Delft where I spent about three months at the department of Design Informatics . In those months under the direction of Michela Turrin I have improved my knowledge about the programs necessary for carry out my research. Have been the key months of my research because in addition to learning new programs they were useful to manage and organize all the next work. After the Dutch period I came back to Italy where I was followed by my Prof. Arianna Astolfi and by the ONLECO S.r.l. company who chose me to develop this kind of topic. Various subjects have been involved in this thesis, my supervisors Prof. Arianna Astolfi and Prof. Anna Pellegrino with the staff of the Department of Energy of the Politecnico di Torino, Michela Turrin with the staff of the department of Design Informatics of TU Delft and the ONLECO S.r.l. company . This research project, dubbed “Development of a preliminary parametric design approach”, brings together the topics of architectural acoustics, lighting, parametric modelling and optimization. This work was an important and interesting challenge because I had the opportunity to apply my work to a real case study concerning a classroom.

The goal of research is to get a perfect learning environment and comfortable for those who enjoy it.

I

II

Acknowledgments This thesis is the final chapter of a two-year long journey at the Politecnico di Torino and before concluding it I would like to thank some people who have accompanied me in these years. I would like to start by those who have followed me during these long months of work, starting with Prof. Arianna Astolfi, Prof. Anna Pellegrino and their PhD students who followed me with passion and a lot of enthusiasm. Special thanks go to Studio ONLECO that has supported me in an extraordinary way, allowing me to enjoy a pleasant experience abroad. I would also like to thank the Department of Design Informatics of TU Delf and especially Michela Turrin, who followed me during my period in Delft. It was one of the most beautiful university experiences I have done. Another person who I would not have been able to do this without his help is Arthur van de Harten who was very kind and helpful to guide me during acoustic analysis. Special thanks go to my friends of Lucca and to all the new friends I have done during this university course with which I shared beautiful moments, thanks to: Gabriele Pellegrini, Daniele Apice, Filippo Aglietti, Francesco Carini and Edoardo Ferrante. I would also like to thank some of the people I met during the months spent in Netherlands and made my stay special: Gabriele Bufalari, Lorenzo Dolente, Marta Scali, Michael Mengolini and Gianluca Orasi. And last but certainly not least, I especially want to thank mom and dad, and my brother Gianmaria for all their love and support.

III

IV

Abstract The proposal is to consider a model of an existing classroom of a primary school in Turin, Scuola Elementare Leonardo Fontana (Via Michele Buniva, 19, 10124 Torino). It is part of an old school building of the eighteenth century, characterised by high vaulted ceilings and big volumes, with reflective surfaces at the boundaries.

Classroom acoustic measurements have been performed in this classroom by the staff of the Department of Energy of the Politecnico di Torino and used to administer speech intelligibility tests in auralized environment. Using the geometry of the room and the optimal reverberation time obtained according to the DIN standard as inputs for the optimizing algorithm will be useful to obtain the best solution that guarantee the highest standards in terms of Reverberation Time (RT), Definition (D50), Signal to Noise Ratio (SNR) and that takes into account the cost of acoustic treatment. This will be achieved by varying the ceiling and walls sound absorption and scattering values, location and extension. Hence, the acoustic optimization starts by the data obtained by the study of the staff of the Department of Energy and goes on in the classroom design through the use of Grasshopper to calculate the best configuration in terms of treatment of the ceiling surfaces and possibly the walls. In parallel to this, it will be used the plug-in Pachyderm to obtain the results of acoustic analysis of various configurations. Lighting conditions in classrooms are a key feature for students performance and well being. The lighting optimization will take into account both daylight availability and glare phenomena. The study will start from the analysis of the classroom features with respect to daylight and sunlight penetration. In particular, the present openings and shading devices will be assessed with respect to the classroom dimension, proportion and to the external context.

The aim of the research is to obtain the greatest comfort, maximising the daylight quantity while preserving the quality of the luminous environment in terms of daylight distribution and glare prevention. The study will be carried out through a Climate Based Daylight Modelling approach, which is based upon a detailed analysis of the interaction between the internal space, the external context, the daylighting condition of the specific site and the behaviour of the average users on an annual base. To do so, the most relevant parameters that we’ll be taken into account are: Daylight Autonomy, Continuous Daylight Autonomy, Maximum Daylight Autonomy, spatial Daylight Autonomy, Useful Daylight Illuminances and Unified Glare Rating.

Going deeper in detail, the study starts with a set of input data provided to the softwar Grasshopper. A possible set of input might be: environment geometry and material’s optical properties, an index of the window surface of the ambient (defiV

ned as the window-to-wall ratio and the glazing visual transmittance), an index of the shading devices, considering also the orientation of the windows with respect to sunlight. Not being able to intervene with external shields the variable that should be considered in the algorithm definition is the reflection factor of the curtains. While the target will be to get maximum comfort satisfying the indexes of the analysis CBDM. Afterwards, the lighting analysis will be performed using the plug-in DIVA of the software Rhinoceros. The consequent output will be the values of the previously defined parameters, with respect to classroom configuration. Through a comparison of these results, the optimal set, in terms of lighting comfort, could be achieved.

The aim of the research is to carry out simultaneously a lighting and acoustic optimization, being focused on the best trade-off of these two studies, which are influenced by a similar set of parameters. In conclusion, the solution is to define a configuration able to satisfy the requirements imposed on both the studies I am interested in attending the Grasshopper software courses, in order to better understand the potentiality and capabilities of the program. This research would also be extremely useful for my learning outcome because working on a realistic case study would allow me to enhance both my theoretical and practical background.

VI

VII

Contents Preface

I

Acknowledgments

III

Abstarct

V

Contents

VII

1. Introduction

1

1.1 Research objectives............................................................................ 3 1.2 Structure of the thesis......................................................................... 2 1.3 Case study........................................................................................ 3 2. Acoustic

7

2.1 Parameters target............................................................................... 8 2.1.1 Reverberation Time.................................................................... 9 2.1.2 Clarity..................................................................................... 10 2.1.3 Definition................................................................................ 11 2.1.4 Early Decay Time..................................................................... 12 2.1.5 Signal-To-Noise Ratio............................................................... 12 2.1.6 Speech Transmission Index........................................................ 12 2.1.7 Equivalent Noise Level.............................................................. 14 VII

2.2 The effects of noise on learning.......................................................... 15 2.2.1 Consequences of a high vocal effort........................................... 17 2.3 Acoustics requirements..................................................................... 19 2.4 Design solutions to control noise........................................................ 24 2.4.1 Control of external noise levels.................................................. 25 2.4.2 Control of internal noise levels................................................... 29 2.4.3 Acoustics bridges and installations............................................. 33 2.5 Design solutions to control reverberation............................................ 35 2.5.1 Solutions and materials for sound absorption.............................. 35 2.6 Classroom B current situation............................................................ 38 2.6.1 Acoustics simulations process.................................................... 40 2.6.2 Digital model of the real classroom B......................................... 40 2.6.3 Surfaces’ properties and analysis settings.................................... 42 2.6.4 Model calibration.................................................................... 44 2.7 Acoustic design................................................................................ 46 2.7.1 Parametric model and analysis specifications.............................. 48 2.7.2 Preliminary acoustic design study................................................ 53 IX

2.7.2.1 The diffusing panel on the lower front wall..................... 53 2.7.2.2 The last raw of seats.................................................... 56 2.7.2.3 Other consfigurations with particular ceilings................. 58 2.8 Acoustic multi-objective optimization................................................. 62 2.8.1 Simulation setup...................................................................... 64 2.8.2 Types of ceilings....................................................................... 66 2.9 Multi-objective optimization results.................................................... 67 2.9.1 Ceiling type n° 1 optimization.................................................... 67 2.9.1.1 Best acoustic treatment obtained.................................. 69 2.9.2 Ceiling type n° 2 optimization.................................................... 72 2.9.2.1 Best acoustic treatment obtained.................................. 73 2.9.3 Final multi-objective optimization.............................................. 75 2.9.3.1 Best acoustic treatment obtained.................................. 77 2.10 Conclusion................................................................................... 79

3. Lighting

83

3.1 Lighting design................................................................................ 84 X

3.1.1 Task/Activity lighting................................................................ 85 3.1.2 Lighting for visual amenity......................................................... 86 3.1.3 Lighting and architectural integration......................................... 86 3.1.4 Lighting and energy efficiency.................................................... 87 3.1.5 Lighting maintenance............................................................... 88 3.1.6 Lighting costs.......................................................................... 88 3.2 Lighting Design standards................................................................. 89 3.2.1 UNI EN 12464........................................................................ 89 3.2.2 UNI 10840............................................................................. 91 3.3 Design parameters of Natural lighting................................................ 94 3.3.1 Daylight factor (FLDm)............................................................. 95 3.3.2 Climate-based daylight modelling (CBDM)................................. 97 3.4 Case studies current situation............................................................ 98 3.4.1 Classroom B............................................................................ 99 3.4.1.1 3D Model................................................................ 101 3.4.1.2 Traditional parameters analysis - DF............................ 102 3.4.1.3 Dynamic parameters analysis - CBDM........................ 105 XI

3.4.1.4 Dynamic parameters analysis - Glare.......................... 121 3.4.2 Classroom Y.......................................................................... 122 3.4.2.1 3D Model................................................................ 123 3.4.2.2 Traditional parameters analysis - DF............................ 125 3.4.2.3 Dynamic parameters analysis - CBDM........................ 126 3.4.2.4 Dynamic parameters analysis - Glare.......................... 131 3.5 Case studies comparison................................................................ 147 3.6 Lighting design.............................................................................. 148 3.6.1 Classroom Y study model........................................................ 149 3.6.1.1 Test n° 1................................................................... 151 3.6.1.2 Test n° 2................................................................... 153 3.6.1.3 Test n° 3................................................................... 155 3.7 Conclusion.................................................................................... 157

XII

Appendix A

165

Appendix B

173

Appendix C

182

Bibliography

189

1. Introduction This research is focused around two main subjects that are related to two basic themes of classrooms and what to do in order to obtain good comfort within school environments. The study starts with a chapter devoted to the acoustics of the classroom. For some years now, a lot of studies have been done on acoustic welfare in a classroom. Failure to achieve a certain acoustic comfort generates problems with the learning process and attention to the task performed is lower. Various studies have shown that school environments with low acoustic quality are harmful towards the comprehension process for students and also to teachers because it puts a bigger strain on their voice and the whole process becomes more demanding. The part of the acoustics literature review presents a careful analysis of various international studies and research in an effort to understand the benefits of good acoustics in schools and how to obtain it. Starting from this analysis, the research moves on to our case study and tries to apply various solutions within it, trying to understand and analyse the various solutions. Our case study called Classroom B is a classroom that really exists and is situated in Turin. In this classroom, a three-dimensional parametric model was developed to perform an in-depth analysis of various acoustic solutions for the classroom. The study on acoustics concludes with several considerations regarding the placement and selection of different acoustic materials inside the environment. These considerations were made based on various parameters considered as fundamental to obtaining good acoustics. In addition, various multi-objective optimizations will be made to understand which configurations (generated by pre-set variables) are the best applicable to the classroom to ensure certain acoustical standards. Afterwards, research moves on to another very important subject in the learning environment, the lighting study. This part begins with an analysis of the current situation of the classroom trying to understand and analyse the major issues within it. Another classroom was taken as a case study for the lighting study, a classroom placed in a more exposed light position. This second classroom was called Classroom Y and was analysed in the same way as Classroom B. The goal of the thesis is to find through the analysis of various types of curtains the best tent that guarantees a good entrance of natural light but also a good shield to avoid having a light discomfort at the back of the two classrooms.

The result of this study will be to have a very accurate idea of our case study through an extensive analysis but also a solution of how to improve the interior comfort of both the acoustic and lighting of the environment.

1

1.1 Research objectives

1.1 Research objectives This project has the following stated research objectives that we can divide into three fundamental points: 1. Investigate the current situation of the classrooms that are being studied through an accurate analysis to understand the acoustic and lighting challenges; 2. After the preliminary study, our case study was reproduced in Rhinoceros as a parametric model with the help of Grasshopper. This allows us to get all the preliminary analysis of the current situation and prepare for the subsequent multi-objective optimizations; 3. The ultimate goal is to handle the large amount of data obtained from multi-objective optimizations and to figure out which solutions are optimal to find the best scenario that ensures a good environment for children’s learning. The results will also show how this type of preliminary design approach is useful to a designer.

1.2 Structure of the thesis The thesis is subdivide in two macro chapter concerning the two subjects with which we will be analyzing the case study. Each chapter examines various research, studies, and international standards to understand how to work best in our case study. It then follows an analysis of the state of facts highlighting the various critical features of the classroom, both for the acoustics and the lighting part. Subsequently, the two studies have two different paths, as for the acoustics section, the research involves a multi-objective optimization finishing while a number of cases are studied for the lighting part. These two different study themes find their union in the last chapter where the hall will be shown with its acoustic and lighting treatment and specifications, as opposed to the current situation.

2

1.1 Research objectives

1.3 Case study The case study taken into consideration regard a classroom of primary school in Turin, Scuola Elementare Leonardo Fontana located in Via Michele Buniva, 19, 10124 Torino.

View taken via google maps highlights the Scuola Leonardo Fontana.

The school building has an “L” shape and is facing two main streets: Via Michele Buniva and Via Cesare Balbo. Our case study is located in the part of the school which facing Via Michele Buniva.

Classroom B has typical plan dimensions for a classroom but in section, in the highest point of the curved ceiling, it reaches 5.1m. This is one of the reasons why the acoustic is very bad inside this classroom, which is now used as a “music room”.

It has never been treated and the acoustics can be compared to the one of churches. All walls are covered by plaster which has very low absorption coefficients and on the floor there are ceramic tiles. The volume of the room is 285m3. The orientation in reference to the windows is southeast and the students are located in the east while the professor in the south. Plan shows the configuration of twenty-four students inside the classroom, divided in four raws and arranged two by desk.

3

1.1 Research objectives

Classroom B plan

The Classroom B has been reproduced using the Rhinoceros program, this has allowed to create a parametric model of the classroom in order to carry out the research results. The following chapters explain which variable parameters have been considered in the acoustics section and in the lighting part, to obtain a perfect case study model for pre-set optimizations. The next image shows the created 3D model and its related specifications.

4

1.1 Research objectives

View taken by Rhinoceros, shows part of urban context, school and classroom B.

After creating the model on Rhinceros it was imported to Grasshopper. Through this operation it was possible to obtain a parametric model, which will be analyzed in the following paragraphs. The previous image shows the model created on the Rhinoceros. It is also possible to see our case study Classroom B and the other case study considered only in the part that concerns the lighting study, the Classroom Y, this classroom is placed two floors higher than the first one. In the three-dimensional model, some of the neighboring buildings were built so that they could have a more realistic model and therefore have more accurate results.

5

6

2. Acoustics Acoustics in school environments play a key role in ensuring those who enjoy a learning environment. The main feature of school environments is their vocation to communication, which is the basis of student learning processes. Natural speech, with its phonemes expressing great variations in the fundamental frequency of talkers that alternate quickly with unexpressed phonemes, is not the best signal for communication and severely examines our brain capabilities in blocking information across interference. That is why good acoustics, in environments where speech is particularly important, must be properly delivered. For many years international research has dealt with the effects of noise on children’s learning and on school performance. Research has shown that high exposure to noise involves long-lasting attention and attention, low auditory discrimination and perception of the word, poor memory for tasks that require the processing of semantic material and limited readability. In the acoustic chapter, will be presented a study on how to improve, through careful acoustic design, the acoustic classroom features and having as its purpose to get a perfect learning environment. To achieve this goal, a parametric design method will be proposed, starting with the creation of a parametric three-dimensional model that can analyze many cases of acoustic treatment and generate the most satisfactory solution. The study begins with a careful analysis of international standards and various useful researches to better understand acoustics in school environments and parameters to be considered for achieving a great acoustic comfort. Subsequently, the work involves the creation of our study case in a parametric three-dimensional model capable of generating many acoustic treatments by applying a range of variable parameters and obtaining the best acoustic treatment to be applied to the classroom. The goal is to get a parametric model of the classroom in which it is possible to have the preliminary design of the results using an optimizer. Using various guidelines as recent guidelines, we have fixed variables that in the parametric model can assume different values to obtain certain outputs that affect us. This method is very fast in terms of three-dimensional modeling, case studies, and acoustic results. In fact, any kind of modification of the geometry or materials within the 3D model will shorten acoustic results. For a designer it will be very useful to model your case study by getting a quick response. Additionally, this type of work can be modified according to the design and use of the environment.

As already mentioned in this case, our study case is a classroom and the purpose of the research is to find the best configuration in terms of positioning and type of acoustic material that can be applied to it. Prior to the construction of the definition, 7

2.1 Parameters target

a careful analysis of international research and standards has been conducted to better understand how to intervene in the classroom and thus get a more powerful model. The basic program used is Rhinoceros and its plug-in Grasshopper. In the Rhinoceros, the 3D classroom model was created and subsequently set up on Grasshopper. This step was essential for creating a model with variable parameters.

The analyzes were conducted using the Pachyderm Acoustic Simulation program.

Pachyderm is a plugin present in both Rhinoceros and Grasshopper. All analyzes were carried out through Pachyderm for Grasshopper and Octopus Optimizer. This optimizer allows you to set up to five outputs parameters and the best solution that will generate will be the one that balances and best meets our outputs. The purpose of the research is to obtain a useful definition in the preliminary stages of acoustic design, a method that can be applied in various environments with different uses. At the end of the search we will get the best configuration that will best suit our pre-set acoustic outputs.

2.1 Parameters target Among the various requirements to be met in the design of school buildings, acoustic ones are of particular importance because they are more directly and strongly linked to the intended use of environments.

The clarity of sound perception is closely related to the duration of the “sound queue” in the room, conventionally evaluated with the measure of reverberation time. In the case of listening to the word, the contribution of the sound reverberation must be such as to create a favorable compromise, which can contribute to direct sound reinforcement, without too long queuing of the tail, masking the signals that take time. Noise from the outside environment and noises generated in an environment cause background noise or residual noise. Noises can mask the sounds produced by a loudspeaker and can disturb listening, causing a disagreeable and annoying hearing and hence a general state of dissatisfaction with acoustic conditions. Excessive reverberation and high background noises reduce the intelligibility of the word, understood as a percentage of words or phrases properly perceived by a listener in relation to the totality of the words or phrases spoken by a speaker.

Depending on the environmental phenomena mentioned, it depends on the cha8

2.1 Parameters target

racteristics of the human voice, in particular the intensity of the emission, which varies with the speaker’s vocal strain.

2.1.1 Reverberation Time The norm ISO 3382 defines Reverberation Time as “the time, expressed in seconds, that would be required for the sound pressure level to decrease by 60 dB, at a rate of decay given by the linear least-squares regression of the measured decay curve from a level 5 dB below the initial level to 35 dB below”. In some cases, when an interval of 30 dB is not available, it is possible to refer to an interval between -5 and -25 dB of sound decay.

This sound decay can be measured on a spot in the room after the switching off of a sound source or by using a room impulse response and reproducing the decay curve that would be produced from a continuously operating source. According to norm ISO 3382, an impulse response is “the plot as a function of time of the sound pressure received in a room as result of an extremely short excitation”, ideally of zero duration having a completely flat frequency spectrum. Practically it is impossible to generate a zero-duration impulse, but very short sounds can represent a good approximation.

Graphic representation of Reverberation Time as the time needed for the sound pressure level to decrease by 60 dB.

Reverberation time can be calculated by using the Sabine formula shown below:

9

2.1 Parameters target

Depending on the volume and the use destination, each room has an optimal reverberation time, it can be mathematically calculated or empirically obtained from the following graphic:

Graphic beside: curves of optimal reverberation time depending on use destination of the room and its volume.

2.1.2 Clarity Clarity index (C50 for speech or C80 for music) is mentioned in the norm ISO 3382 and was defined by Reimer and Muller. It compares the sound energy in early sound reflexes with those that arrives later and represents the ratio between the energy coming to the listener’s ears during the first 50 ms and the energy coming to him from that moment to the end of signal decay. This relation is expressed in dB. Direct sound is defined as the sound that first reaches the listener and this is followed by early refl ections. The early reflections that reach the listener within 50 ms are integrated with the direct sound and thus have a positive effect on speech clarity.

10

2.1 Parameters target

The reflections that come later may be perceived as disturbing.

Clarity is related to the structure of sound reflexion end consequently to reverberation time but also to the distance between speaker and listener. Positive values of clarity (1,2 dB) denote a very clear sound field, too much clear after 2 dB; otherwise negativevalues (-1, -2 dB) suggest an unclear field, while less than -2 dB is a very poor condition. Therefore, the optimum range for this parameter is from -2 dB up to +2 dB.

2.1.3 Definition Definition (D50) is an index introduced by Thiele and it is reported on the norm ISO 3382. It is defined as the ratio of the energy coming to the listener’s ears during the first 50 ms and the whole energy of all the signal. Obviously if only direct sound is detected the ratio is 1, while in case of absence of direct sound and exclusively presence of reverberations, the value of the ratio tends to zero. In other terms it is the early to total sound energy ratio.

The index is commonly used in the characterization of rooms for speech and, for this kind of environments, optimal values are about 0.7 or 0.8. Definition can also be expressed in percentage using the following formula:

11

2.1 Parameters target

2.1.4 Early Decay Time Early decay time (EDT) is the reverberation time, measured over the first 10 dB of the decay. This gives a more subjective evaluation of the reverberation time. The user can also change the decay interval of this parameter. As Reverberation Time parameters, the Early Decay Time is computed for every octave band. It is expressed in ms.

2.1.5 Signal-To-Noise Ratio Signal-to-noise ratio (SNR) is a measure that compares the level of a desired signal to the level of background noise. It is defined as the ratio of signal power to the noise power, expressed in decibels. A ratio higher than 0 dB indicates more signal than noise and a negative ratio indicates more noise than signal power. It is also used as medium to define Speech Reception Threshold (SRT), the minimum intensity in decibels at which a determined percentage of spoken words can be understood.

2.1.6 Speech Transmission Index Although there have been many attempts to objectively quantify the speech intelligiblity, the most widely used parameter is the Speech Transmission Index (STI).

It represents a measure of speech transmission quality and is related to subjective intelligibility scales.

In measuring STI, the voice of speaker is considered as a modulated in depth signal, the full STI method is described in the IEC 60268-16 standard. When a sound source in a room is producing noise that is intensity modulated by a low frequency sinusoidal modulation of 100% depth, the modulation at the receiver position will be reduced due to room reflections and background noise. The Modulation Transfer Function m(F) describes to what extent the modulation is transferred from source to receiver, as a function of the modulation frequency. As a guide, an increase of STI 12

2.1 Parameters target

of 0.1 corresponds to 3 dB change in effective signal-to-noise ratio. Intelligibility values have to be adjusted for non-native subjects based on the following table:

Table 2.0 Adjusted intelligibility qualification table for non-native listeners. Non-native category I: experienced daily second language use; non-native category II: intermediate experience and level of second language use; non-native category III: new learner, infrequent second language use. Label categories refer to ISO 9921.

There are qualification bands for STI related to some typical applications:

13

2.2 The effects of noise on learning

Table 2.1 Examples between STI qualification bands and typical applications.

2.1.7 Equivalent Noise Level Noise levels often flow over a wide range over time. Taking as an example the night period, the level could drop to 30dB with occasional passenger vehicles of 70dB or more. With the arrival of dawn, followed by the general noises of the day before the return of peace in the late evening. This is where Leq noise or an equivalent continuous noise level occurs and this tester faithfully follows all the fluctuations, stores them in the memory and at the end of the measurement calculates average energy. It is not a simple arithmetic mean because we measure in decibels that are logarithmic values. Then the instrument converts the dB values to the sound pressure levels, adds them then divide by the number of samples, and then converts this equivalent to decibels.

It is common practice to measure noise levels using the A-weighting setting in all sound level counters. A good Leq sound level sampler captures noise levels 16 times per second, which means more than an hour calculations of 16 x 60 x 60 = 57600.

2.2 The effects of noise on learning The most obvious role of the school is to educate, to foster cognitive development, to transmit information about the subjects of the curriculum, and to communicate joy and excitement about education (Rivlin and Weinstein 1984).

School learning is a long and fragile process, the result of which is prevalently identified with the abilities of educators, yet close by these likewise the physical and natural conditions inside which it happens have a not irrelevant impact, that can occasionally have a critical weight. One of these conditions, to some degree ignored in our nation, is quality acoustics of the classrooms, whose insufficiency in this regard has for quite a long while been liable to precise checks and intercessions in numerous different nations. Additionally on the fact that the results of the analysis so 14

2.2 The effects of noise on learning

far done here are in accord: an awful acoustics of the classrooms can have exceptionally negative results for learners and educators: backing off or in worst cases impairing learning in a large number of the first ones; causing general exhaustion and disappointment in the seconds. In Italy, the vast majority of school situations don’t meet the base requirements to make them appropriate to their purpose and learners and educators are the ones who are influenced the most by insufficient acoustic conditions. We can state that environmental sound levels which are acceptable for grown-ups (who are people in their hight of hearing ability) amount to negative conditions for youngsters who require better surroundings for speech understanding. The sound children experience in the classrooms is both noise transmitted from outside through the building covering and sound created inside to the edifice itself. Kids in schools are in this way subject to sound from a wide range of sources with various results and impacts.

It is not normal to consider the noise pupils need to stand at school. If we had the chance to break down it in definite parts, we can find that sound sources lie both inside and outside the building shell: loud passageways, sounds through walls, levels and entryways, plumbing noises, plantroom vibration, doctborne noise, and furthermore outside play area noises, climate and rain sounds, circulation noises by means of open windows and vibration. Sound produced by air traffic is especially harming for kids who are in constant contact with this sort of noise[1]. From the results of the European RANCH, Aircraft and Road Traffic Noise and Children’s Cognition and Health project[2], earises that incessant contact to air traffic noise affects negatively comprehension and reading, related with intensifying the perceived level of childbearing disorder. Different investigations have likewise demonstrated that sound caused by rail activity additionally influences reading capacity. Bronzaft and McCarthy[3] called attention to the fact that kids on the calmer side of a school 1 Hygge S., Evans G.W. e Bullinger, M., “The Munich Airport noise study: Cognitive effects on children from before to after the change aver of airports”. Proceedings of lnternoise ‘96, pp.2189 - 2192, 1996; 2 3. Stansfeld S. A., Berglund B., Clark C., Lopez-Barrio I., Fischer P., Ohrstrom E., Haines M.M., Head J., Hygge S., van Kamp I. e Berry B. F., “Aircraft and road traffic noise and children’s cognition and health: a cross-nati on al study’’, Lancet 365, pp.1942-49, 2005; 3 Bronzaft A.L. e McCarthy D.P., “The effect of elevated train noise on reading ability’’, Environment and Behaviour, 7(4), pp. 517-527, 1975;

15

2.2 The effects of noise on learning

alongside a lifted rail would be better in reading activities than kids who faced the railroad side, with noise levels higher than 89 dB(A). Nonetheless, the quantity of schools close to airplane terminals or railroads is consistently low if compared with the high number of schools located in urban zones where the overwhelming noise is mostly caused by traffic circulation. Inside the classrooms of elementary schools, noise comes primarily from the conversations of pupils accomplishing ordinary teaching exercises. The closeness of pupils in a grade school expands environmental noise to a level of 56 dB(A) when they work on their own and to 77 db(A) if they are involved in some group activities. The average estimation of environmental noise level for common situations (where the kids work from their desk, sporadically cooperating with their fellows) is instead 65 dB(A).

Not proper acoustic situations not only impair learning exercises of usual hearing pupils, but influence more negatively the ones with hearing issues or speakers other languages. Furthermore, it was calculated that 40% of the kids in grade schools more often than not experience the ill effects of temporal or perpetual hearing harms caused by colds and ear infections. This implies that these subjects in particular require better acoustic conditions due to their specific vulnerability to noises and resonation. In some cases the right answer to better enhance acoustic conditions in the classrooms regards to disadvantaged pupils could be setting up sound speaker networks, which likewise bring advantages to ordinary hearing young learners as well. In any case such sound speaker systems work only when general acoustic conditions of the classrooms are properly harmonized and they can’t be considered as an option to a right acoustic planning of the space.

2.2.1 Consequences of a high vocal effort Bad acoustics is a true deterrent for education and it is an issue which concerns both players in the learning process: educators and learners. Educators correspond to the work force, the ones who very often accuse vocal illnesses and grumble mixed up spells. Amid the most recent decades, global research in the acoustics field has considerably concentrated more on the nature of the listening assignments of the classrooms, mostly related to the initial levels of learning. It is so assumed that this stage could have important effects on instruction of individuals and, in 16

2.2 The effects of noise on learning

this way, on society overall. Notwithstanding being destructive to young learners, lacking acoustics in the classroom cause troublesome learning conditions. Noises and the resonation take to a high vocal exertion for the instructors, whose effects result in signs for a real professional illness, which bring about non-attendance and interruptions of the instructional path. Some of these studies investigated voice problems[4]. An examination developed by “ Voice care network[5], accomplished in the United Kingdom on patients complaining with clinical voice issues, established that 12% of them are educators, despite the fact that they are just the 1,5% of the whole sample. Other investigations[6] carried out in America proved that instructors represent working class most concerned by vocal problems and, in particular, 20% of them need to hold up under a neurotic vocal exertion.

Lejska[7] found, through an exhaustive phoniatric exam of 772 educators, different vocal illnesses in 7,1% of them, which reaches 23,5% if one includes fonastenia cases as well (without a true pathology). Fihlo et al.[8] state that 9.7% of instructors show nodules in their vocal cords while Urritikoetxea et al.[9] assert that this condition is visible in 13% of cases. Different analysis[10] sketched out that around 10% of instructors experience the ill effects of vocal ropes nodules.

Instructors’ vocal exertion estimations layout how, frequently, such level is higher than 60dB (characterized as the ordinary exertion limit by standard measurements).

These standards additionally consider how the closeness of noises specifically impacts vocal exertion: the Lombard impact is the automatic propensity of speakers 4 Valdis lngibjorg Jonsdottir, ‘Teachers’ vacai symptoms related to their opinion regarding room acoustics”, EURONOISE 2006, Tampere, Finland; 5

Commins D., “Survey of UK voice clinics 2001/2 (2002)”. Voice Care Network UK (2002);

6 Titze I., Lemke J., Montequin D., “Populations in the U.S. Workforce who rely on Voice as a primary tool of Trade: a preliminary report.” The journal of voice 11 (1997); 7

Leijska V., “Occupational voice disorders in teachers”, Pracovini Lekarstvi 19 (1967);

8 Fihlo M., Gomez F.G. e Macedo C., “Videolaryngostroboscopy far pre-admissional examination of school teachers”, First World Congress of Voice, Oporto, Portugal, 1995; 9 Urrutikoetxea A., lspizua A., Mantellanes F. e Aurrekoetxea J., “Prevalence of vacai nodules in teachers”, First World Congress of Voice, Oporto, Portugal, 1995.

10

Leijska V., “Occupational voice disorders in teachers”, Pracovini Lekarstvi 19 (1967);

17

2.2 The effects of noise on learning

to build their vocal exertion when talking in noisy clamor in order to improve the discernibility of their voice. This normal reaction which acts as compensation could prompt negative outcomes. Kob et al. stressed the negative impact due overabundance of resonation on instructors’ voices in secondary schools and the positive change in vocal execution after sound-retaining acoustic structural interventions.

The control of clamor and resonation appear to be crucial to lessen vocal diseases.

Research cannot be considered as exhaustive yet; nevertheless the advantages of acoustic interventions in classrooms have already proved themselves as to be a pivotal element in order to ensure healthy conditions both for pupils and educators.

The norm ISO 9921 defines vocal strain as the voice sound pressure level, measured from a distance of 1 meter from the mouth of the speaker and defines 5 degrees for vocal effort:

Table 2.2 ISO 9921 vocal strain classification

The level above 60 dB, defined as the standard effort threshold in the standard, is considered to be damaging to the teacher. The norm also considers how the presence of noise directly influences vocal effort and the Lombard effect is the involuntary tendency of speakers to increase their vocal effort when speaking in loud noise to enhance the audibility of their voice. For this reason, natural compensation effect could lead to negative consequences.

Kob et al.[11] pointed out negative effects due to excess of reverberation on teachers’ voices in secondary schools and the improvement of vocal performance after sound-absorbing acoustic treatments. The control of noise and reverberation

11 LKob M., Behlery G., Kamprolfz A., Goldschmidtx O., Neuschaefer-Rube C., “Experimental investigations of the influence of room acoustics on teachers’ voice”, Acoust. Sci. & Tech. (2008);

18

2.3 Acoustics requirements

should not be underestimated, but it’s important to handle it correctly in order to reduce voice disorders. There are many ongoing researches but the benefits of acoustic treatment in the classrooms are a very important aspect, not only for students but also for teachers.

2.3 Acoustics requirements In recent years, many Acoustics studies have been carried out that have led to the creation of linear guidance, laws and standards to be used for acoustic design of various environments. There are many researches and norms to use in the acoustic design of school environments. In this section we will look at some of these standards. By respecting the requirements of the standards we will discuss in the next paragraphs, we will get environments with good acoustic comfort for both students and teachers.

One of the recommendations is to mention first the World Health Organization (WHO) booklet, the Regional Office for Europe, Noise in Schools, 2001[12]. Among the guidelines that define the limit values of acoustic parameters and indicate the constructive modalities to meet the requirements, the Building Bulletin 93 (8893) published in Great Britain. Another norm to consider is the the Swiss Standard SIA 181, which is based upon DIN Standard 1804, presents requirements for background noise and reverberation time. The recommended reverberation time for classrooms of 125 m3 - 250 m3 was set at approximately 0.4 - 0.6 seconds. The recommendations concerning background noise are given in DIN 18041 for noise stemming from outside of the room and technical noises.

Some international standards will be proposed in the next paragraphs and also the Italian rules will also be proposed.

12 Pamphlet WHO, Regional Office far Europe, n. 38, Noise in schools, 2001 ( www.who.dk/envi ron ment/ pa mph lets);

19

2.3 Acoustics requirements

2.3.1 World Health Organization (WHO) With the Noise in Schools publication, WHO reports on noise impacts in children’s and teacher’s classrooms, identifies minimum acoustic health requirements, and provides some useful tips for acoustic reclamation. These minimum requirements refer to a previous publication in 1999, Guidelines for Community Noise[13].

This pubblication sets at 35 dB (A), LAeq, the maximum admissible floor noise level in the classroom during the didactic activity. Outside, during play, in recreational areas, the sound level must not exceed 55 dB(A), LAeq. The reverberation time in the classes should be 0.6 s, and even lower in the presence of children with hearing problems.

Table 2.3 summarizes the information in the OMS Noise in Schools publication.

The WHO’s publication also proposes guidelines in the design of school environments. Specifying the importance of noise in learning and managing it within teaching activities. Among the project recommendations, some of the key points are summarized below: • the school building should be as far as possible from sources of noise due to transport and industries; • the interior spaces should be distributed in such a way as to isolate noisy zones from areas requiring more tranquility; • for each individual school environment, depending on its intended use, adequate sound insulation and optimum reverberation must be ensured; • the systems must minimize noise emission.

13 World Health Organisation. Guidelines far Community Noise. http://www.who.int/peh/, 1999.

20

2.3 Acoustics requirements

2.3.2 Building Bulletin 93 The appropriate solutions for noise reduction and sound reverberation are well described and illustrated on Building Bulletin 93[14]. In addition to presenting minimum requirements, the Building Bulletin 93 has a number of technological solutions to meet the required requirements.

Table 2.4 recommendations for the acoustics of classrooms, Building Bulletin 93, ACOUSTIC DESIGN OF SCHOOLS, a design guide.

Table 2.4 shows the requirements to get in the design of an unobserved classroom, comparing the recommendations of BATOD and ASHA. Also within this publication is explained the maximum levels of sound pressure level of background noise and reverberation time for some furnished and unused school environments. Background noise is indicated as the A-weighted equivalent level with a 30 minutes integration time (LAeq, 30 min), essentially due to continuous-running systems and external noise. In the background noise, the noise contribution caused by teaching activity, audio-video devices and the activity carried out in adjoining environments is excluded.

2.3.3 DIN 18041: 2004-05 The recommendations concerning background noise are given in DIN 18041 14 Department far Education and Skills, Building Bulletin 93, Acoustic Design of School. London: The Stationery Office, 2003 (www.teachernet.gov/acoustics).

21

2.3 Acoustics requirements

for noise stemming from outside of the room and technical noises. For both types of noises the permissible equivalent A-weighted sound pressure level ranges from 30 to 40 dB(A) and is a function of the distance between the speaker and listener as well as whether the room is to be used by the hard of hearing or for instruction in foreign languages. The DIN 18041 also states that the acoustic quality of a room, in the sense of this standard, is essentially determined by the location of the room in the building, the sound insulation of the components surrounding it, noise generated by building equipment, as well as the shape and size of the room (primary structure) and the surface properties of the boundary surfaces and furnishings (secondary structure). At the same time the dimensions and spatial distribution of sound absorptive and sound reflecting surfaces in the room concerned are also important influence factors. Regarding the time of reverberation the norm sets a target at average frequencies (Tsoll) is to be taken from figure 2.5, depending upon the mode of use and an effective room volume V between 30 m3 and 5000 m3.

The curves “music”, “speech” and “teaching” refer to occupied rooms. In figure 1 a dashed line represents room volumes which are atypical for the rooms covered by this standard, while a dot-dash line identifies room volumes greater than those within the scope of the standard.

Figure 2.5 — Target value, Tsoll, for the reverberation time for different modes of use

22

2.3 Acoustics requirements

2.3.4 National laws In Italy, the Ministerial Decrees of 18/12/1975 and 13/09/1977 are the legislative references that guided the design and construction of school buildings.

The Ministerial Decrees of DPCM 5/12 /1997 replacing them and is currently the main reference point for the construction of new school buildings. It refers, in part, to the old Circular 3150 of 1967. The DPCM 18/12/1975 and 13/9/1977 are about the insulation requirements in case of noise transmission through air and noise transmission caused by pounding, the optimum values for the reverberation time and the noise limit values from the installations are quoted. Going more specifically to the Decree 13/9/1977 appears to be an update of the first and inside it are explained guidelines for control during the construction of new buildings, such as acoustic isolation between adjoining and overlapping classrooms, noise level passing through overhanging environments, noise installation and reverberation time. The indications we find within the decrees must be respected during design for all teaching environments. The measurements must be carried out in empty spaces, with absorbent applied applied and with all furniture. Below are shown the accettability requirements:

Table 2.6 Accettability requirements to be satisfied with measurments in place according to D.M. 12/18/1975

The Ministerial Decrees of 18/12/1975[15] has a part devoted to the performance requirements for heating systems, ventilation, central air-conditioning, plumbing and water installations pipes, baths, hygienic services, faucets. The D.M. 13/9/1977 presents some changes that concern the limits established in the previous decree by setting the level of noise from services to values less than 50 db(A) for discontinuously-operating services and to less than 40 dB(A) for continuously-operating services.

15

D.M. 18/12/1975 Norme relative all’edilizia scolastica;

23

2.4 Design solutions to crontrol noise

The most recent Ministerial Decree is the D.M. 13/9/1977, this Decree defines the passive acoustic requirements of buildings based on the type of environment. The quantities introduced are the index of acoustic insulation of façade, ≥ 48 dB, index of soundproofing of partitions between spaces, ≥ 50 dB, index of noise level from bounding of floors, ≤ 58 dB.

2.4 Design solutions to control noise The Building Bulletin 93[16] is one of the most important guide to noise control inside the classrooms in relation to the design of schools. This guide explains how to reduce noise in the vicinity of school buildings and how to handle the sound inside them. Inside the Building Bullet 93 are shown many strategies in order to protect schools from external noises from infrastructures and other close noise sources.

Figure X.X shows typical external and internal sources of noise which can affect noise levels inside a school.

16 Department for Education and Skills, Building Bulletin 93, “Acoustic Design of School”. London: Stationery Office (2003)

24

2.4 Design solutions to crontrol noise

Figure 2.8: Typical noise sources inside and outside a school building. From Building Bulletin 93, “Acoustic design of school”.

2.4.1 Control of external noise levels The acoustic outline of a school begins with the choice of the site, a noise overview of the site and the arrangement of the school structures design. Earlier, schools have been based on locations which would not regularly have been considered appropriate for lodging. This has been partly because schools have generally not been considered as entities requiring special high environmental standards and to some degree also because there has been less formal control or directive of sound levels in schools compared to the ones applied for lodging. In case school locations are close to noisy streets they will require the utilization of smart plans, zoning, sound screening and, if needed, sound proof building insulation together with mechanical ventilation or acoustically designed passive ventilation. A significant number of the acoustic issues in existing schools come specifically from the fact that the school is placed in a loud area. When shielding an edifice from noise sources coming from outside is the aim, it can be valuable to take into consideration some details, for instance: • • • • • •

site localisation related to noise sources; building placement on the site; building orientation on the site; possibility to raise acoustic barriers; good soundproofing treatment on outer walls; good design of internal spaces: layout and distribution.

In a few nations, as for instance in Italy, spaces are partitioned into acoustic sectors taking into account the limit assessment of sound level emanation considered as the group of sounds produced from every one of the sources, spotted on a few receivers.

In Italy, five acoustic zones have been defined and schools must be situated in territories in Class I, this implies areas whose limit amounts to 50 dB(A). In the United 25

2.4 Design solutions to crontrol noise

Kingdom this sound toleration level is set to 60 dB(A). A 70 dB(A) sound tolerance limit still makes possible to achieve good results inside the school yet an appropriate soundproofing treatment on outer walls must be given or sound walls must be built.

The layout of spaces internally is of essential importance as well when one has to outline the plan of a school: when the site has been identified yet it is located near a single main source of sound, it is desirable to plan canteens and other administration spaces (equipment rooms, for instance) on that side of the building, while classrooms and spaces for exercises which require more focus have to be built instead on the quieter side. An earlier exam of the acoustic conditions of the site plays an essential role in the following process of planning and it can impact the shape and the volumetric dispersion of the edifice. The most sensible side of the building, in which didactic performances occur, must be situated beyond what many would consider as a possible sound source. In reality, when a point-source is identified, if the separation from that source doubles, sound levels drop of around 6 dB; while if we encounter linear sources (e.g streets) the decrease amounts to around 3 dB. Additionally, air decreases the levels of sound: this is absorbed via air while stretching long distances. Acoustic assimilation caused by air shifts depending on temperature and dampness. Finally, it can be useful to use acoustic obstructions: vegetal reefs of trees’ columns for example aren’t to consider as solution to suggest however can be employed as veiling, covering components playing as acoustic walls which allow at the same time a good visual effect. In order to work efficiently, sound barriers must be made of punctured metal, loaded with sound-absorbing stuff. Now and then walls can be filled with topsoil and covered with vegetation. It is critical to pick a correct sound wall relying upon the type of noise which is required to be blocked: the majority of acoustic hindrances function greatly at higher frequencies yet in some cases they are not completely efficient at the lower frequencies and the noise originating from motors can overcome the boundary and get to the opposite side in any case. Moreover, the surface of the walls facing the sound has to be provided with sound absorbing materials, this in order to avoid additional sound reflections that can magnify noise level if they head for other sensible receptors. Where it is important to portray an exceptionally complex sector close to numerous sound sources, the utilization of mimicked models can be extremely useful.

26

2.4 Design solutions to crontrol noise

Transport and infrastructures Vehicular circulation, railroads and air terminals speak to a standout amongst the most aggravating noise sources of regular day to day existence. Besides, they represent an additional aggravating factor if didactic activities take place close to them.

There are a few components which might represent negative adding elements in relation to the level of noise produced by traffic, for example: • traffic flow (it can considerably vary depending on the day of the week and on the time); • type of vehicles (heavy goods vehicles can be very noisy); • geomorphology of the site where the • road is on (uphill roads cause noise increasing); • road surface condition; • speed of vehicles (as a consequence of the type of road).

Figure 2.9 Traffic noise barriers. Department for Education and Skills, Building Bulletin 93, “Acoustic Design of School”. London: Stationery Office (2003)

Some technical solutions can be brought into shielding schools from this type of

27

2.4 Design solutions to crontrol noise

noise sources, beginning from the soil planning. In ordinary urban circumstances, where vehicles go at a normal speed of 60 km/h, sound levels is for the most part assembled at the lowest frequencies because of the noise coming out from exhaust pipes. At a speed of 80 km/h the greater part of such level is to be connected to higher frequencies due to the interaction between the road and the tires and the aerodynamic sound. All those diverse circumstances must be considered when sound control has to be realized. Railways activity produces a kind of sound whose vitality is high and consolidated at the most elevated frequencies yet goes on for a brief time. When we measure the level of the sound produced by a train 25 m far from it, sounds levels can reach around 90 dB(A).

There are cases in which the vibration emitted by heavy vehicles circulating near a building achieves the foundations through the ground and can be transmitted to a few components of the edifice as noise. An exam of the vibrations is to be done when railway lines are up to 30 m close or when a main road lays inside 20 m from the school. It is difficult to foresee the noise level coming from air activity in nearness to an air terminal. Main airplane terminals include maps with sound curves that are a useful instrument to evaluate the acoustic conditions of surrounding spaces. Before take-off and directly subsequent to landing, sound gravity level can achieve values higher than 90 dB[17]. Some typical noise levels can be measured at the distance of 1 m from the outer walls of an edifice located in urban zones: for instance 20 meters from a roadway gone by a few heavy vehicles 78 dB are to be measured; 20 meters from a road going through a private neighborhood 68 dB is the level attested; if there are different structures in between the road and the spot where measurement happens, a level of 58 dB can be identified.

2.4.2 Control of internal noise levels A precise position of inner spaces can be a valuable element for sound control.

The modern idea of education in primary schools includes the co-existence of an 17 British standard 8233:1999, “Sound insulation and noise reduction for buildings - code of practice” (1999)

28

2.4 Design solutions to crontrol noise

extremely wide range of different activities. Therefore, measures for acoustic shielding must be implemented to guarantee a strategic distance from the sound created by noisy activities which won’t reach in this way a classroom where lessons are taking place. Rooms dedicated to didactic activities are spaces with low resilience to noise and they must be isolated from sport halls or rooms meant for music, and recreational spaces through other little spaces whose purpose is shielding. Such spaces can consist for example of stores dedicated to musical instruments, for sport paraphernalia, aisles or silent pathways. On the off chance that it is conceivable, spaces as sport centers should be located dispersedly in various structures distant from the main one. Sound transmission may happen through entrances, as well.

This is the reason behind why a right position of the entryways is to be planned: recommended is for example not to design doors opposite to each other in rooms which face each other and neither entryways excessively close in restricted spaces.

With the specific end goal to decrease the noise in the background and, thusly, increment speech understandability, the most widely recognized treatment to realize sound protection from outer and inward noise implies appropriate works on walls and floors. The DPCM 12/5/1997 indicates a few steps to be taken after while developing new schools yet some issues still have to be resolved: directions indicated by the DPCM 12/5/1997 are quite generic and don’t specifically refer to the acoustic conditions related to the location in which the building is going to be constructed. Following these lines without taking into account the context, can take to an over the top treatment even when for example the acoustic background is overall quiet (with incredible financial waste) or to a proficient treatment in case the acoustic condition is instead exceptionally uproarious. A viable outline of soundproofing requires specific considerations to the sound transmission through every one of the components of the building without overlooking windows, entryways, vents, that can impair the function of the walls in which they are in. Important is the installation procedure: when it is not performed in a workmanlike way, it can cause “acoustic bridges”.

Facade External sound protection restriction is 48 dB (according to DPCM 12/5/1997) regardless of the possibility that it ought to be determined relying upon the actual outside noise levels, being the end goal of the interventions to make the breaking points for the interior noise fall into an acoustic comfort condition. As per some 29

2.4 Design solutions to crontrol noise

current researches, the background noise in a classroom ought to be lower than 30 dB, similar to a low-buzz that is accepted as tolerable regarding a condition of ideal speech comprehension. Acoustic sound protection of vertical barriers and floors relies on upon the material’s mass employed and on the implementation of stringy material in the interspaces that fills in as sound insulation stuff. Exceptionally thick dividers made of blocks, solid pieces or expanded clay consolidated with layers of encasings guarantee the fulfilment of the acoustic requirements. Additionally light walls made of wood boards or layered chalk when joined with insulating materials prompt great acoustic results. Soundproofing performances of acoustic barriers are regulated by the index Rw: it works in decibels and indicates the weighted sound reduction index for a partition or single element. This is a laboratory-only estimation, as regulated by standard UNI EN ISO 140-3. There are additionally some empirical principles to calculate Rw and on the empirical standard UNI TR 11175 there are a few cases of partitions with their index Rw. Windows Windows are the weakest piece of the building envelope. They are made of casing, glass, vents and furthermore box for rollerblind. There are breaking points to be fulfilled additionally under the thermic viewpoint and those lead the originator to the utilization of twofold coating, since single coating or overlaid glass can’t fulfill the prerequisites; this angle plays likewise into acoustics. Some broad rules can be taken after to better adventure twofold coating in acoustic: • the glass sheets must have different thicknesses to reduce losses due to phenomena of coincidence; • laminated double glazing improves acoustic performances; • in case of double glazing with only one laminated glass sheet, this one has to be interted on the internal side of the frame; • interspace dimensions from 6 to 16 mm doesn’t influence the soundproofing performances; • the best gas to be inlaid in the interspace is sulfur hexafluoride. It works better than Argon or normal air; • double glazing assembled on independent frames assure better performances than double glazing on the same frame.

30

2.4 Design solutions to crontrol noise

Single casing windows can achieve a sound decrease file (Rw) of 40-42 dB. In order to obtain a better efficiency it is expected to fall back on twofold casing windows. The material of the casing doesn’t impact altogether the acoustic execution of the window, expecially when the Rw of the glass is not high; on the other hand, if the glass is exceptionally well performing, elements of the edge can seriously impact the general output of the window. The nearness of a window on a divider for the most part prompts a decrease of Rw of 2dB, an entryway of 5 dB. A twofold edge without the focal upright prompts a lessening of 1 or 2 dB and if the casing is not noticeable we can consider an expanding of Rw of around 1 dB on windows with a typical Rw equivalent to 44 or 45 dB. The utilization of sheats in each point where diverse materials are in touch, it’s a reasonable approach to not decline the acoustic exhibitions of glass and edge.

Ventilation The type of ventilation plays an important role and needs to be chosen based on acoustic reasons. If the outside noise level exceeds 60 dB, the simple natural ventilation through opening the windows isn’t an appropriate choice. Before choosing a mechanical solution could be useful to analyze the opportunities offered by natural ventilation through the use of acoustic attenuation devices. But there are also commercially available vents that can be soundproofing.

INTERNAL PARTITIONS Vertical partitions To get a low floor noise in the classrooms, it is a particular cure in the use of highly-soundproofing partitions. The vertical walls between the classrooms are heavy walls, double walls with interspace, simple or double divisions and are made of high-mass clay blocks, fixed with mortar and generally plastered on both sides. When they are double, the inerspace is filled with sound absorbing material. There are several ways to achieve good double walls performance: • use of elastic sheaths to not couple the structures; • creation of an interspace of at least 5 - 10 cm; 31

2.4 Design solutions to crontrol noise

• realization of differently thick partitions; • use of sound absorbing material in the interspace.

Light partitions are usually built on supporting structures of folded sheet metal and their acoustic performance depends on the number of slabs, the interspace dimension, the type of fibrous material inside, the distance between the frames and the method of installation. The best performances can be achieved with double walls made of two independent frames. Sound transmission between two neighboring rooms occurs not only through the partition but also trough all the system of elements connected to the partition: floor, ceiling and vertical side walls.

To control this phenomenon is necessary: • increasing the mass of connected elements; • introducing interruptions on the direct way the sound can take; • putting a soundproofing counterwall on side walls to increase their sound reduction; • closing each opening in walls or in the system of ducts.

Doors Doors’ performance is the combination of the acoustic performance of the frame and the one of the door itself. Internal or external wooden doors with thickness of about 45 - 55 mm, sealed on the perimeter can achieve an Rw between 30 and 35 dB. When the door is located in very noisy envirinments the solution to be adopted is a double doors separated by a sound absorbing interspace filled with porous panels. This kind of doors generate a sound reduction index close to 45 - 60 dB. Floors The DPCM 12/5/1997 sets a noise from stamping using no more than 58 dB. Floating floors are the best solution but it is also possible to coat the floor with a resilient paving. These solutions avoid any rigid connection with the floor. The issue of flooring has to be thoroughly studied and it is essential to have a good realization of all junctions with the vertical elements of the structure. The most important thing in designing to get good acoustic requirements is to avoid any 32

2.4 Design solutions to crontrol noise

type of acoustic bridge through: good realization of the joints between vertical and horizontal elements, the laying of the screed or the resilient sheat, tiles and skirting.

2.4.3 Acoustics bridges and installations Acoustic bridges are a common defect caused by weaknesses or design errors but some adjustments can be applied while preventing interventions can reduce the risk of sound transmission in buildings.

Here are some tips for good acoustics: • doors, windows and vents will inevitably worsen the performance of the elements in which they are installed in; • impact noises will spread through rigid elements without being attenuated; • partitions between sensible environments should be higher than the countertop and reach the structural ceiling in order to avoid the sound to spread through the free space above the partition; • openings in walls should be carefully sealed; • ducts linking two different environments shoul be coated with soundproofing materials in order to avoid cross-talk effects; • it is better to avoid rigid connections between two layers of a double wall.

Noise from installations can be controlled from the very beginning of the project using some strategies directly related to the application type. Even if the installations are placed in the final stages of the construction process, their noise control must be planned in the early stages of the process. It is very important to think about the type of installations to be used and how to locate them. The design strategies to reduce the noise emitted by the machines and the distribution network are closely related to the type of system. A rational distribution of spaces can be useful: it is best to identify sensitive environments far from the machines. Cooling systems, whose noise also moves through the air, must be treated differently from other mechanical installations whose noises spread solid. In fact, among all system types, the cooling system produces levels of Higher sound pressure.

33

2.5 Design solutions to crontrol reverberation

Cooling systems Noise usually comes from fans that move the air, but they are the most disturbing source of noise. Terminals are specially critic: vents and diffusers irradiate directly in the rooms. To reduce noise generated by fans, it is advisable to use reduced speeds for fan blades. When the background noise is too high in the environment, it is necessary to plan the use of the silencers to be used on the duct walls. They are made of acoustic absorption material and work better near the fans. If the duct is rectangular, the best sound attenuation is achieved when the height is even greater than the width of the duct. Sometimes ducts can create acoustic bridges connecting two different rooms; In this case, it is recommended to carefully study the path of the ducts and to avoid crossing sequentially different environments. There are also anti-vibration supports to reduce sound transmission through solid elements.[18] Sanitary systems The hydraulic network produces noises from pumps. In this case the sound transmission mainly spreads through structural elements. Pipes’ noise can be reduced by using elastic supports and resilient coatings or properly sizing valves.

Elevators There are mainly two types of elevators: hydraulic and rope elevators. The hydraulic elevators are more silent. The only noise source is the compressor that can be easily placed in a special room isolated. While regarding the rope elevators, are more noisy, and produce a sound pressure level of about 70 dB. So it’s necessary the realization of thick walls and highly soundproofing doors are advisable.

2.5 Design solutions to control reverberation Not only does noise influence the intelligibility of speech, but also the reverberation. It must be controlled through a proper project: it is very harmful to the 18

34

Oliaro P., “Rumore degli impianti tecnologici”, in Manuale di acustica applicata (2007)

2.5 Design solutions to crontrol reverberation

intelligibility of language, it introduces the diffusion of noise sources and thus reduces the binaural benefit in language intelligibility because the ability to segregate the various sources is compromised. In addition, the reverberation also affects the voice signal itself. As a result of reflections in the edges of the room, the original vocal signal is mixed with late versions of itself from different directions, which can reduce intelligibility. Among the most common solutions to be adopted is the use of absorbent panels that contribute to the attenuation of sound in the environment where it is emitted.

2.5.1 Solutions and materials for sound absorption The acoustic correction starts with the measure of reverberation time. The parameter is related to the clarity of speech and therefore the quality of language perception. The application of sound absorbing materials in closed environments results in a reduction in reverberation time by absorbing the energy of late reflections and undesirable background noise. The aim of an acoustic absorption is to achieve an optimal value for reverberation time depending on the type of environment and the activities that take place inside. Each material, in acoustic terms, is characterized by an absorption coefficient representing the relationship between the absorbed energy and all the energy that influences the material. It varies from 0, when all energy is reflected, to 1, when all energy is absorbed. It depends also on the frequency and the angle of incidence. Taking into account UNI EN ISO 354 standard is measured in reverberating room using large sample material. The physical principle that controls the acoustic absorption process is the conversion of energy into heat. This phenomenon can take place in several ways, and depending on the materials it is effective in for some frequencies. There are three main categories of absorbent materials and they are: • fibrous materials; • vibrating panels; • acoustic resonators.

35

2.5 Design solutions to crontrol reverberation

Figure 2.10 Absorption curves for absorbent materials. 1: hard finish, plaster on solid backing; 2: porous absorber; 3: perforated panel; 4: panel absorber/vibrating panel. Taken from British Standard BS 8233:1999, “Sound insulation and noise reduction for buildings - Code of practice”.

The chart below shows the various absorption curves typical of absorbent materials: curve 1represents hard finish, plaster on solid backing; curve 2 are the coefficients for porous absorber, 50 mm mineral fibre 50 kg/m3, the performance is not significantly affected if protected by a perforated panel with at least 30% open area; curve number 3 is for perforated panel, 14% perforations, 25 mm cavity containing mineral fibre; the 4th curve is the one of a panel absorber, 9 mm ply, 50 mm cavity containing 25 mm mineral fibre.

Fibrous materials Fibrosis or porous materials, with open cells, such as rock foams or expanded polyurethane foams, are characterized by fibers less than 1 mm, which are connected to each other. The absorption takes place thanks to the action of the air in the cavities and the consequent loss of energy caused by the friction with the material. Porosity is defined as the ratio between the volume occupied by the pores and the total volume of the material itself. Absorption increases with increasing porosity: the best acoustic absorbing effect occurs when the porosity is between 90 and 95%.

The thickness of the material and the distance of the panel from the wall affect the absorption properties. All the performance of the fibrous panels is very low if their surfaces are painted or coated with non-porous materials. Fibrosis panels are re36

2.5 Design solutions to crontrol reverberation

commended when high frequencies are to be absorbed.

Vibrating panels The vibrating panels are made up of thin panels located not far from a rigid wall.

The system panel wall functions as a vibrating mass (the panel) connected to an elastic bond (air in the gap) to a rigid support (wall). Porous material can be inserted into the cavity to improve sound absorption. Using the resonance frequency, the maximum acoustic absorption is obtained and depends on the mass of the panel and the distance from the wall.

Acoustic resonators The Helmholtz acoustic resonators are made of a cavity with rigid edges connected to the outside through a narrow opening. The air in the device can be considered as a vibrating mass and the one in the cavity is the elastic element. When a wave strikes the resonator, the internal air starts to vibrate and periodically compressed.

This system has a resonant frequency that depends on the size of the narrow opening and the volume of the cavity. A resonator absorbs mostly at low frequencies, between 50 and 400 Hz, and generally works very well at the resonance frequency.

By filling the resonator with porous material, the absorption coefficient decreases to the resonance frequency but increases the range of frequencies involved in acoustic absorption.

Figure 2.11 Absorption of an acoustic resonator in the case of filling with absorbent material compared to the non filled one. From Benedetto, Spagnolo, “Assorbimento acustico di materiali e strutture”, in Manuale di Acustica applicata (2007).

37

2.6 Classroom B current situation

2.6 Classroom B current situation The classroom B has a typical plan dimensions with an area of 60.0 m2 but its particular feature is evident from its section, showing a curved ceiling with a maximum height of 5.1m.

Figure 2.12 Pictures of Classroom B taken by G. Puglisi during measurement phase (DENERG, Energy Department, corso Duca degli Abruzzi, 24).

The environment consists mainly of plaster material on the entire wall and ceramic tiles for the floor. At a noise level these materials don’t guarantee good acoustic absorption. Furthermore, considering that the environment has a large volume of about 285 m3 and adding a poor sound absorption of the materials, the acoustic features of the current situation are very scarce for good acoustic comfort. These considerations are largely demonstrated in the measurements made in the classroom. The measured reverberation time is reported in the graphic below for each frequency. The mean value is 3.12 s with a standard deviation of 0.77 s.

38

2.6 Classroom B current situation

Measured T30 in Room A. Measures taken by G. Puglisi using an omnidirectional microphone. Mean value: 3.12 s , Standard deviation: 0.77 s.

2.6.1 Acoustics simulations process The classroom acoustical study was used as base program Rhinoceros, where the geometry of the classroom was built. Subsequently the geometry was imported on a grasshopper, this step has been done as we will see later in order to have a parametric model in which some parts of the classroom geometry will change the type of material. The acoustic analyzes were conducted using Pachyderm, an open source plug-in for both Rhinoceros and Grasshopper.

“Pachyderm is a plugin largely used by Designers and Scientists alike to simulate acoustics in buildings, rooms, cities, and other settings.”

The opportunity to use Pachyderm also on Grasshopper will be crucial to create acoustic optimization for the classroom.

2.6.2 Digital model of the real classroom B The creation of the digital model has been made very accurately, as the fun39

2.6 Classroom B current situation

damental objective was to get a digital classroom model that behaved acoustic as the real one. On Rhinoceros, the geometry of the classroom was created and subsequently divided into different levels, where each level corresponds to each material present inside it. The figure below shows the three-dimensional model of the classroom and its division into layers. The model is divided into four main layers, respectively: plaster, door, glass and floor. The X.X image shows the work area on Rhinoceros and the presence of eight levels numbered from 0 to 7. Layers comprised from 0 to 3 are layers that include geometry without any material assignment, while layers 4 to 7 are layers that only contain acoustic properties in this case properties relative to the four materials listed above. The assignment of geometry to its material will be through the definition created on Grasshopper.

Figure 2.13 Shows the reproduction of the classroom on Rhinoceros and the division into geomtrie layers and layers with acoustic properties.

Subsequently work moves to Grasshopper, where a layer definition for Rhinoceros and geometry has been created. Using this definition, each material layer will be assigned a material layer. By doing so we will get the digital reproduction of our environment. Again on grasshopper then pachyderm was used to get the acoustic analysis and calibrate the model.

40

2.6 Classroom B current situation

Figure 2.14 mostra la riproduzione dell’aula su Rhinoceros e la suddivisione in layers geomtria e layers con proprietà acustiche.

The digital models for the classroom B had to mirror the real ones and, in specific, the main parameter taken into account were: Reverberation Time (T30). Simulated results were compared to the measures recorded on site (with no forniture, empty spaces).

2.6.3 Surfaces’ properties and analysis settings The classroom B has only four materials in its current situation: plaster, door, glass and ceramic tiles. The most present material is the plaster covering all the walls and the ceiling. Each surface is charachterized not only by absorption properties but also by scattering capacities. In this physical process, sound is forced to deviate from a straight trajectory by one or more paths due to the shape and the roughness of the surface that rays meet. Concerning scattering coefficients, they were not easy to be estimated mostly because it is difficoult to interprete the software’s algorithms and every software works differently from others. Here are the tables of coefficients of the classroom.

41

2.6 Classroom B current situation

Figure 2.15 Classroom B, absorption and scattering coefficients for surfaces.

Graphic of absorption and scattering coefficients (in frequency) and surface extension.

Regarding the source and receiver, figure x shows how speech-source position was fixed, as the receiver. The source, or rather the teacher, was placed at a height of 1.50m while the receiver was placed at 1.20m from the floor.

42

2.6 Classroom B current situation

Figure 2.16 This scheme shows the positioning of the source (red point) and receiver (blue point) used for calibration.

The noise level was set to 60 dB and the source was omnidirectional. The sound pressure level of the speaker at the beginning of the adaptive procedure was set to 60dB, which corresponds to a “normal vocal effort” according to norm ISO 9921.

The analysis settings in Pachyderm, are as follows: • Number of Rays = 50000 • Cut off time = 5000 • Image Source Order = 2

2.6.4 Model calibration Using the material properties and settings described in the paragraph before, 43

2.6 Classroom B current situation

the following results have been obtained: calibration is based on Reverberation Time, just one measurment spot because the parameter should be evenly distributed in the environment.

Classroom B

Figure 2.17 Classroom B, comparison between measured and predicted Reverberation Time.

The calibration of the model provides satisfactory results, measured and predicted values for the main parameters taken into account show a good matching. The calibration, however, shows that at the very low frequencies, there is always a considerable error. In order to find an explanation to this gap, Schroeder frequency has been calculated and it’s 216 Hz. That frequency denotes approximately the boundary between reverberant room behavior (above) and discrete room modes (below). This means that the calibration is valid above 216 Hz because, when below, the creation of acoustic modes can compromise the results. This phenomena usually happen in small reverberant rooms with parallel walls, where soundwaves hitting one side come back in the same direction and add up.

44

2.6 Classroom B current situation

Once the calibration was completed, the parameters that were subsequently used in the optimization of C50, D50 and SNR (A) were calculated. This analysis, unlike the calibration, has twenty-four students as receivers and the same source (teacher).

In addition, a background sound level has been added that represents the presence of istallations and has values for frequencies from 125 Hz to 8 k Hz of 35.2, 32.6, 27.4, 24.9, 2.6, 15.4 and 14.0 dB.

2.7 Acoustic design In this part of the acoustics study, various research will be explored to deepen the theme of diffusing surfaces to improve the acoustics of school environments. Various combinations of optimal absorbent and diffuse treatments will be analyzed to 45

2.7 Acoustic design

obtain good acoustic comfort in school environments. Many classroom intelligibility studies have investigated the effect of room reverberation, and some of them have come up with the optimum reverberation time to achieve high intelligibility[19]. While other studies[20] have shown that preferential acoustic conditions for voice communication are not only influenced by reverberation (RT) but also by signal-to-noise ratio (SNR(A)). A much-used solution in the Acoustical design of the classrooms is to apply absorbent material to the ceiling and in some cases to the walls. This type of treatment affects the reduction of reverberation time and noise level in a classroom, but it does not prove that this type of approach generates optimal acoustic quality, especially for the last classroom files. Taking as an example the classrooms with a very low reverberation time, speech intelligibility values diminish as the distance between the source and the receiver increases. As a result, pupils in the last files will have an unfavorable acoustics. The addition of large amounts of room absorption to obtain short reverberation times has also led to reduced SNR values and the intelligibility of degraded speech due to reduced sound levels in more distant places. The most common sound absorbing material in the classrooms is acoustic ceiling tiles that absorb high frequency sounds far better than low frequency sounds.

This ceiling treatment can generate an excessive reduction in high frequency ringing sounds and cause high-frequency consonants to be masked by low-frequency vocal sounds. The ceiling area is a very important part for generating useful early reflections to the rear area of the room. For these reasons later a very accurate study on the ceiling will be done on our case study. Many studies[21] have been conducted concerning early reflections, these studies have shown that these reflections are very important in voice communication in school environments. One of these is the one proposed by Barron[22] who emphasizes this importance and the results show that early reflections have made the strongest direct sound and were more important in increasing the intelligibility of the speech at the back of the rooms, where direct sounds were usually relatively weaker.

19

Bradley JS, “Speech intelligibility studies in classrooms”, J Acoust Soc Am (1986);

20 Bradley JS, “Reich R, Norcross SG. On the combined effects of signal-to-noise ratio and room acoustics on speech intelligibility”. J Acoust Soc Am (1999); 21 Bradley JS, Sato H, Picard M. “On the importance of early reflections for speech in rooms”, J Acoust Soc Am (2003); 22

46

Barron M. “Auditorium acoustics and architectural design”, 2nd ed. London: E &FN Spon (2009)

2.7 Acoustic design

The studies just underlined emphasized the importance of the role of the ceiling, but they also pointed out that an all-absorbing solution does not create the appropriate acoustic comfort for students in the latest files. A recent study led by Choi[23], which investigated the effects of periodic type diffusers in a classroom to determine if the diffusers were beneficial for obtaining preferred acoustical conditions for speech communication: periodic type diffusers were installed on either the front or the side walls of a model classroom. The results obtained by Choi show an important increase in the C50 values at the most distant places from the source. This is due to the insertion of diffusing material on the front wall around the class deck. This type of treatment is effective to improve speech acoustics in remote receiver positions.

A lower low frequency RT was obtained and produced a uniform RT in frequency when the speakers were added. This study was very useful for the next design phase. In fact, in this study, the principles of the Choi study will be applied and other recommendations of some international standards will be considered. The final results of the research will show how this preliminary study done on these researches will have a real application in the treatment of classroom B.

2.7.1 Parametric model and analysis specifications As already mentioned in paragraph 2.7.3, using Pachyderm on grasshopper allows us to have a different mode of assigning acoustic properties to geometric layers. This will be very useful for the optimization we are going to talk about in the near future. Following the various studies listed above, this research proposes to divide the geometry of the classroom into key points in different layers. This will allow us to create a list of acoustic materials that can be assigned to specific parts of the classroom. The following figure shows how the layers were first divided into Rhinoceros and then assigned to Grasshopper.

23

Choi. “Effects of periodic type diffusers on classroom acoustics”, Applied acoustics 74 (2013)

47

2.7 Acoustic design

Figure 2.18 It shows the work area on the rhinoceros, the pattern and the division of the layers.

The blue layers are the ones that form the classroom geometry and always have a fixed material while the red ones always concern the classroom geometry but we can assign them a list of materials. Gray-colored layers have only acoustic properties assigned by pachyderm.

The work done on Rhinoceros is imported on Grasshopper through Human, a plugin of Grasshopper. In this way the research has been moved on grasshopper, to achieve subsequent the acoustic analysis.

48

2.7 Acoustic design

Figure 2.19 shows the Grasshopper canvas and the use of the plug-in Human for the importation of the layers from Rhinoceros.

The previous image shows how various layer lists have been created on Grasshopper and divided in: geometry list layers, list material leyers, list layers material cost materials and list layer colors for a simpler identification of applied materials.

This process was necessary because the Pachyderm command “Polygon Scene” (Constructs a scene with the existing geometry in the model and/or geometry from Grasshopper definitions) requires as input data the geometry of the model and the materials to be assigned to the list geometries. In fact, some parts of the geometry as anticipated may have a list of materials that can be assigned with different acoustic characteristics.

The classroom geometry was then subdivided into several parts considered important in terms of acoustic results. The following figure X.X shows the subdivision and nomenclature we have given to them.

Figure 2.20 shows the classroom parts, and their nomenclature, in which different acoustic treatments will be applied.

49

2.7 Acoustic design

In the list of layers listed above, it will be possible to assign a variety of materials, with different acoustic properties, which will be shown in the next table. In this way we can quickly test various acoustic treatments inside the classroom.

Figure 2.21 Classroom B with acoustic treatment, absorption and scattering coefficients for surfaces.

50

2.7 Acoustic design

Graphic of absorption and scattering coefficients (in frequency) and surface extension.

51

2.7 Acoustic design

2.7.2 Preliminary acoustic design study In this section, certain configurations that are considered important will be individually analyzed to better understand the acoustic response of the classroom in certain acoustic configurations. The study will start following the guidelines outlined in the paragraph before where we have listed some studies concerning the location of the various acoustic materials inside the classroom. This allows us to have a general picture of the acoustic response but will also be useful in understanding what to expect in the subsequent optimization of acoustic results.

2.7.2.1 The diffusing panel on the lower front wall As a preliminary preliminary analysis, a classical acoustic treatment with a fully absorbent ceiling was taken into account. Next, with the same ceiling, two other analyzes were made to understand how the diffuse material differs in the lower side of the classroom and behind the teacher.

52

2.7 Acoustic design

Compared to the current situation, the application of a fully absorbing ceiling already generates a considerable improvement in acoustic sound. The reverberation time has a remarkable reduction from a value of about 3.0 s to a value of 0.6 s.

The C50 and D50 values also have a large increase, resulting in an improvement in acoustic comfort

53

2.7 Acoustic design

At first glance, the comparison of configurations AC100 and AC100 DLFW underline that the presence of the diffusive panel below the blackboard on the front wall, actually decreases RT values. Clarity, Definition and SNR(A) on the other hand, show a rise in value and consequently create a better environment than the first proposed. Even the Definition has an increase in value especially for the last two raws of students.

Proceeding with other tests, in the next one will be applied to the classroom diffusive panels on the lower side walls, to better understand what this kind of treatment entails.

54

2.7 Acoustic design

Using diffusive panels on side walls, T30 and EDT have lower values compared to the other two configurations previously studied. In this configuration, we also have higher Definition values and SNR(A) values. In fact, the analyzes show that the presence of the diffusive panels on the sides increases the values of the external files making the results more homogeneous.

2.7.2.2 The last raw of seats In previous analyzes it has been shown how the speaker panels placed on the lower limbs of the class enhance the acoustic quality within the school environment.

In fact, improving the amount of early reflections creates a space with better and well-distributed acoustic comfort.

55

2.7 Acoustic design

Analyzing the German standard DIN 18041, a standard regarding the acoustic quality in rooms, the last update in 2016 shows a careful study of the ceiling. The standard shows many indications of how to handle the ceiling and as mentioned above, the ceiling should not be absorbed 100% to prevent the teacher from being forced to use a too high level to be heard at the back of the class and Provide early reflection useful to student ears. This particular attention to the treatment of the ceiling is also found in the choi study, previously analyzed. In fact, the research showed better results when the ceiling was 75% covered with absorbent panel and 25% with speaker panels (preferably located above the teacher’s head). It should be considered that, by treating 25% of the ceiling with diffusive surfaces, it necessarily means eliminating the same amount of absorbent surface and this can negatively affect the T30 values and consequently some aspects of language perception.

The DIN 18041 standard shows a more accurate study of the ceiling design by proposing various configurations that do not divide the ceiling into two simple shades but offer a more elaborate geometry. The following figure shows some configuration taken from the text of the standard.

Figure 2.22 DIN 18041, 2016. Favorable and unfavorable ways to treat the ceiling.

This preliminary study of classroom behavior started with varius ceiling treatments which will be studied in a more detailed way, starting with a simple split into two parts, as Choice made, to arrive at more complex configurations, as the DIN 18041 offers.

56

2.7 Acoustic design

2.7.2.3 Other configurations with particular ceilings In the previous tests, configurations with a completely absorbent ceiling type were studied, while in this paragraph following the Choi study and the DIN 18041 standard, more elaborate ceilings with different acoustic characteristics are shown.

The configuration AC75 DC25 only has a ceiling treatment, dividing the ceiling into two parts an absorbent and a smaller one with sound diffusion characteristics.

The results show that unlike a fully absorbing ceiling the T30 values and EDT values are higher and the pameters C50, D50 and SNR(A) have lower values, consequently, it is not satisfactory as a treatment.

57

2.7 Acoustic design

Inserting a diffusive panel down behind the teacher, generates a lowering of the T30 and EDT and a small increase in the values of C50 and D50 values, in particular in the last two rows of students but there is no big difference with the previous configuration.

58

2.7 Acoustic design

This configuration appears to be very interesting in general of the results much more balanced than the others, with low values of T30 and EDT but without adversely affecting the values of C50, D50 and SNR(A).

Now it will be proposed a new type of ceiling, following the study conducted by Filippo Bolognesi that according to his research[24] a configuration with a baffle ceiling should ensure a better acoustic comfort. In fact what emerges from his study is that baffles can minimize noise pollution and reverberation but also provide useful early reflections. So this study will also consider the configuration of baffle ceiling and will study some configurations such as the next one, a configuration that integrates a baffle ceiling with other treatments previously studied.

24 Filippo Bolognesi “Prevision of optimal speech intelligibilit in primary school classrooms through simulation of optimal acoustic absorption and diffusion conditions” Politecnico di Torino (2016)..

59

2.7 Acoustic design

Analyzing the latest proposed configuration, we can state that the considerations made in the search for Filippo Bolognesi are confirmed. In fact, the results show lower T30 and EDT values than all the other configurations studied. We also get good results of C50, D50 and SNR(A). In particular the values are much more homogeneous and this means that there is no great discrimination of acoustic comfort for stundets.

So this preliminary study was useful to understand the classroom behavior following the various researches suggested in the previous paragraph. Has highlighted the very important role of the ceiling, which depending on its configuration significantly affects the results of the analyzes.

60

2.8 Acoustics multi-objective optimization

2.8 Acoustics multi-objective optimization The role of optimization in a design system is to find the configuration in the feasible design space that best matches desired performance goals. The key aspect of this research is the possibility to study a great deal of acoustic treatments through an optimizer. Grasshopper allows to create a definition that enables in short time period to obtain acoustics results by modifying characteristics of the case study.

Multi-objective optimization, which is the search for optimal values for two or more of such conflicting objectives, comes into play. The compromise between different performance aspects may be described with Pareto optimization, a state in which one thing can only improve at the expense of another. In fact, after finishing the optimization, all the data will be useful to understand as the room reacts acoustically to the application of different treatments. Negotiating the architectural implications associated with limiting sound propagation in open workspaces, by definition comprises a trade-off between diverse aesthetic and acoustic performance measures.

Multi-objective optimization, which is the search for optimal values for two or more of such conflicting objectives, comes into play. The compromise between different performance aspects may be described with Pareto optimization, a state in which one thing can only improve at the expense of another[25]. As a conclusion to the development phase of this study, multi-objective optimization is performed on a parametric model of the Classroom B case study. For this purpose the Octopus plugin (Vierlinger & Zimmel, 2015) for Grasshopper is used to assess this model across two main executions with different types of ceiling. The overall process is aimed at finding a set of configurations in which a improvement of room acoustic characteristics is balanced. The next figure shows the work done on grasshopper and explains its division part by part.

25

Burry & Burry, 2010, pp. 118, 262

61

2.8 Acoustics multi-objective optimization

Figure 2.23 Screenshot of the final Grasshopper model for the multi-objective optimization of classroom B

Legend of Figure 2.23: 1. import and manage layers through the use of the Human plug-in, the layers are divided into several lists of geometries, materials and cost per square meter; 2. section to calculate the cost of each acoustic analysis analyzed; 3. part of the definition dedicated to the optimization variables and materials assignment to geometries, blue colored layers packets are room parts with fixed material while red colored ones are room parts with variable materials; 4. switch to change ceiling configuration (from AC75 DC/AC25 to Baffles); 5. Pachyderm settings analysis; 6. receivers (students) and source (teacher) points; 7. Pachyderm acoustic analysis results; 8. formula to calculate SNR(A) values; 9. multi-objective optimization parameters; 10. optimizer and export results in excel files.

62

2.8 Acoustics multi-objective optimization

2.8.1 Simulation setup The optimization part is thus composed of variables, output parameters, and analysis settings. The various analyzes made during the optimization have the same setup set by Pachyderm used in the preliminary study of individual acoustic treatments, that is: • Number of Rays = 50000 • Cut off time = 5000 • Image Source Order = 2 The source used is omnidirectional and has a power of: 67 dB (250/1k Hz) and 50 dB (2k/8k Hz). Its location is located in the short wall at a distance of 1.00 m and its height from the floor is 1.50 m. There are also twenty-four receivers representing students within the school classroom placed at a height of 1.20 m.

The Grassopper definition provides an export part of the analysis to an excel file.

This file contains all the configurations studied in the optimization and will be useful to understand the classroom behavior depending on the treatments applied. Optimization variables, as explained in the previous paragraph (2.8.1), are some key part of the classroom (figure X.X). By convention, a series of initials was assigned to each part. Various materials with different acoustical properties will be assigned to the variables listed below during optimization. The following list shows which materials can be assigned to certain parts of the classroom: • Ceiling 25%: 18 Absorbing panel 19 Reflective panel • LSW - Lower Side Walls (variable material): 15 Plaster 16 Diffusing panel • HSW - Higher Side Walls (variable material): 15 Plaster 63

2.8 Acoustics multi-objective optimization

16 Diffusing panel 17 Absorbing panel • LRW - Lower Rear Walls (variable material): 15 Plaster 16 Diffusing panel 17 Absorbing panel • HRW - Higher Rear Walls (variable material): 15 Plaster 16 Diffusing panel 17 Absorbing panel • LFW - Lower Front Walls (variable material): 15 Plaster 16 Diffusing panel • HFW - Higher Front Walls (variable material): 15 Plaster 16 Diffusing panel These parts of geometry were chosen after a careful analysis of various researches carried out on acoustic treatments to be adopted in school environments. The goal is to obtain a good number of analysis and define the treatment that meets most of the parameters. Regarding the parameters, five parameters were chosen to find the best treatment configurations. These parameters are respectively:: Reverberation time (RT), Clarity (C50), Signal-to-noise-ratio (SNR(A)), Definition (D50) and the cost of the acoustic treatment applied. Octopus, the optimization program, by default, minimizes all assigned paraems. To maximize a parameter, it is therefore necessary to divide the value for one. In this case, SNR(A), C50 and D50 values have to be inversed to try to get maximum values. The goal of multi-objective optimization is to reduce the values of RT and the cost while trying to get the maximum values of SNR(A) and D50. The latest optimization that will be proposed only has four parameters to optimize and are just the acoustics first proposed. This choice is due to obtaining the best acoustic configuration by eliminating the cost parameter 64

2.8 Acoustics multi-objective optimization

that in any case has its influence on the final results.

2.8.2 Types of ceilings In the acoustic design study, the ceiling part was thoroughly investigated. In fact, this part plays a key role in terms of acoustic results. Consequently, a typical flat ceiling type was divided into a portion (75%) absorbent while the remaining 25% positioned above the teacher may become depending on the absorbing or diffusing configuration. The other type of ceiling has baffles and has a more complex configuration than the first but as already shown in the previous paragraph provides better acoustic quality. The following figure shows the two types of ceiling and their possible configurations.

Figure X.X shows the two types of ceilings and configurations they may have.

By analyzing in more detail the ceiling made up of baffles, the preceding figure 65

2.9 Multi-objective optimization results

shows that the perimeter of the ceiling is composed of absorbent material while a central part has a reflective material of 6.30x4.60m dimensions. In the latter part, the baffles are perpendicularly positioned. The baffles are made of absorbent material, have a dimension of 1.00x0.66m and are spaced 0.75m from each other. This particular ceiling configuration has been thoroughly analyzed in terms of analysis as the Pachyderm acoustic analysis program attributes by default the acoustic properties to both parts of the surface. As a result, our choice was to use the same absorbent material (absobent panel ceiling) but halving the absorption and scattering curve.

2.9 Multi-objective optimization results The following section shows the results and subsequent insights of the three optimizations made in class B. It has been chosen to make three types of different optimizations for a more accurate study of the room. Previously it was explained that in the treatments applied to the room two main types of ceilings were used, following this logic, in the first optimization was used the type of ceiling n° 1, in the second the type of ceiling n° 2 with the baffles while in lastly, the most complex optimization involves the study of both the ceilings. So in the last optimization, the choice of the two types of ceiling becomes a variable of the multi-objective optimization.

In addition, in the last optimization some settings will be changed, in particular the parameters to be optimized, considering only the acoustic parameters and not the price to get the best results in terms of acoustic comfort within the classroom. The best results of the various optimizations will then be studied in more detail by going to see also the classroom acoustic behavior with twenty-four students.

2.9.1 Ceiling type n° 1 optimization In the first optimization a flat ceiling type was used in two parts respectively in 75% and 25% respectively. The 75% part is located at the bottom of the classroom and is composed of absorbent material in all configurations studied. While the 25% ceiling section depending on the acoustic treatment configuration, two types 66

2.9 Multi-objective optimization results

of materials can be assigned through the parametric model: Absorbing panel or Reflective panel. As for the settings, variables, and parameters, the optimization assumes the setup described above and the settings used on Octopus are the default ones. In fact, this optimization have seven variables: Ceiling 25%, LSW, HSW, LRW, HRW, LFW and HFW. While the paramters are: RT, C50, SNR(A), D50 and Price.

The optimization has been set in such a way as to maximize the parameters of D50, C50 and SNR(A) while the RT and Price parameters will be minimized.

The figure below shows the Pareto fronts from the last generations of the optimizations based on the parameters: RT, C50, SNR(A), D50 and Price. Respectively the first axis regards RT values, the second C50 values, the third SNR(A) values while the color type is referred to D50 values and the size of each solution is related to the cost of each configuration.

Figure 2.24 shows the graph of the Pareto front.

Figure 2.24 highlights the configurations studied by showing the solutions in a graph with the five output parameters. To better understand which solution according to the optimization satisfies the five parameters, it is necessary to display the solutions as in figure 2.25. With the multi-axis view, the configurations studied are more readable and puts the most balanced configuration in terms of satisfying the set parameters.

67

2.9 Multi-objective optimization results

Figure 2.25 multi axis view from Octopus.

Before analyzing in depth the “best” solution was a study of how the parameters are influenced by each other. By using the TToolbox plug-in, all the configurations studied by Octopus (Appendix A) were exported to an excel file. This allowed a more elaborate study on the various treatments, and subsequent charts studied a single parameter at a time in relation to the other four. This was useful in understanding the tone response of the classroom sound by applying various treatments. Even simulations considered not good for acoustic comfort allow you to understand the relationship between the position of the materials and the subsequent acoustic results.

2.9.1.1. Best acoustic treatment obtained During the optimization, about thirty-six hours, six hundred acoustic treatment configurations were studied. Of these six hundred, the configuration that weighs and meets the acoustic requirements (parameters) and a balanced cost is the configuration shown below.

68

2.9 Multi-objective optimization results

The best acoustic treatment solution that best balances the five parameters set is the AC75 DC25 AHSW DLFW DLRW. This solution has a ceiling divided into two parts where the larger part is made of absorbent material while a smaller part near the label is diffused. In the upper part of the side walls, there is the absorbent material, while the diffusing material is in front of and behind the teacher at the bottom of the walls.

Analyzing the acoustic data of this configuration, show that in all parts of the classroom, for all twenty-four students, the acoustic parameters values are very homogeneous and there are no particular differences in values between the first and the last. The mean RT value is 0.63s, a very good value considering that the actual state provided a RT of 3.12s. Regarding the values of C50, D50 and SNR(A), the results show how they are enough balanced throughout the classroom and how to ensure good hearing comfort.

69

2.9 Multi-objective optimization results

The next acoustic treatment shown is the same configuration just analyzed but includes the presence of twenty-four students.

By making a comparison between the full and empty class, the results show that twenty-four students influence the final results but not so significantly. By increasing the acoustic absorption within the room, the values of RT and SNR(A) decrease as the values of D50 and C50 increase but in a minimum.

The best configuration confirms the previously proposed research and also the entire preliminary analysis part. The application of diffusing material improves early reflection and its application as well as being necessary in the lower part of the classroom is also useful in the ceiling, thus fueling reflection up to the last files.

70

2.9 Multi-objective optimization results

2.9.2 Ceiling type n° 2 optimization The second optimization performed takes into account a type of ceiling composed of baffles. Its composition has absorbent parts in the exterior of the ceiling while there is a central part diffusing with a series of baffles with absorbent material.

Regarding the settings, variables and parameters were used the same as the first optimization with the type of floor ceiling. Figure 2.26 shows the results obtained in the Pareto front chart.

Figure 2.26 shows the graph of the Pareto front.

While in Figure 2.27 the solutions are represented differently by five axes that correspond to our five parameters. This chart shows which solution best meets the target of each preset parameter.

71

2.9 Multi-objective optimization results

Figure 2.27 multi axis view from Octopus.

2.9.2.1 Best acoustic treatment obtained The best solution obtained from Octopus is the AHSW DRFW. Again in this case, about six hundred treatments have been studied and the one that weighs optimally all five parameters is a solution with absorbent panels on the sides of the students and a diffusing part in the bottom part of the classroom located at the bottom. The solution obtained is quite similar to that of the first optimization, there is always the absorbent material in the upper side parts and the diffused material in the lower end of the classroom.

72

2.9 Multi-objective optimization results

The classroom acoustic data shows that applying this kind of treatment to the classroom, with a much greater cost to a flat ceiling treatment, gives us an environment with a satisfactory acoustic comfort overall. By comparing with the best solution of the first optimization, the data claim that this configuration has a better RT but the other parameters are slightly worse though certainly more homogeneous considering all twenty-four students.

The study of the best configuration continues with classroom analysis with twenty-four students.

73

2.9 Multi-objective optimization results

Introducing students inside the classroom the acoustic absorption overall increases, and as it has already studied in previous analyzes, increasing the absorption decreases the value of RT and SNR(A) while the values of D50 and C50 increase.

By comparing the results with the first optimization we get a baffle ceiling with a lower reverberation time and higher C50, D50 and SNR(A) values. The solution with the baffles, as seen in the preliminary study, generates a better acoustic comfort and in particular makes the acoustic values more homogeneous for each student, since the last files do not have a big difference compared to the first ones.

2.9.3 Final multi-objective optimization The latest optimization in this acoustic study is different from the first two. In fact, 74

2.9 Multi-objective optimization results

only four acoustic parameters were studied and the fifth parameter, while the price was eliminated. This option allows to get the best configuration in terms of acoustic parameters without being influenced by too high a cost of configuration.

Figure 2.28 shows the graph of the Pareto front.

The Pareto front graph shows only four parameters that are respectively: RT Axis 1, C50 Axis 2, SNR Axis 3 and D50 is discretized with color.

Figure 2.29 multi axis view from Octopus.

75

2.9 Multi-objective optimization results

In the multi axis view, figure 2.29 shows the best configuration, the acoustic treatment that meets all four acoustic parameters according to the preset variables.

Eliminating the price as a parameter to minimize the configuration that is obtained from the optimization presents acoustic treatment in all parts of the classroom and consists of a floor ceiling AC75% DC25%. In this optimization, the best solution is more expensive and this is due to the elimination of the Price parameter.

2.9.3.1 Best acoustic treatment The acoustic treatment that best balances our four acoustic parameters is a configuration that has a flat ceiling divided into an absorbent part while a smaller reflective part of it is placed near the teacher. There is also diffusing material in all low part of the classroom while in the high parts as the side and bottom side there is the absorbent material. This result is partly found in previous optimizations, but having set the price as a parameter to minimize, not all parts of the classroom had materials with specific acoustic properties.

76

2.9 Multi-objective optimization results

This latest optimization allows us to have the best treatment without any cost influence. The acoustic values obtained are very satisfactory. In fact, we have a lower RT of 0.6s also the clarity and definition parameters are satisfactory and also the SNR(A) values. There is a minimal difference with the second optimization since applying a ceiling with the baffles, and thus a greater amount of acoustic material, get good results. This configuration differs from that of the second optimization because it has a longer reverberation time and better SNR(A) values. But by applying a greater amount of diffuse material throughout the lower part of the class we have even better distributed values of C50, D50 and SNR (A). This aspect is very important as it generates more distributed hearing comfort for all students.

77

2.10 Conclusion

Here again, the analyzes were resumed by considering the twenty-four students in the classroom. By increasing the absorption within the classroom, as we have seen in the study of the individual parameters, we get smaller RT and SNR(A) values while for the parameters of D50 and C50 there is a small increase.

2.10 Conclusion The proposed acoustic study is an interesting approach to obtain a good and complete preliminary analysis of any environment. In this case, it has been used to optimize the properties and location of acoustic materials within a classroom, trying to best meet the acoustic requirements that were set beforehand. A very important aspect of using this approach is careful preliminary analysis, not only in terms of 78

2.10 Conclusion

acoustic results but also knowing what you want to get from such a study. In this research, it was crucial to use guidelines from others studies to get an idea of where to focus the research work without wasting time on analyzing incoherent cases. The possibility of dividing the model into geometry parts with fixed materials and parts of variable materials proved to be a timesaving method, to obtain in a short time a large amount of useful results for good acoustic design. Eventually understanding what is the influence of these materials in relation to the acoustic parameters considered important for the case study.

The study on classroom B led to a configuration with excellent acoustic results in a well-distributed way. An interesting and useful thing for a designer is the ability to study the other “best” cases and not only the perfect configuration, i.e. those very close to the top results. In this way, you can have a general picture of the acoustic response of the environment per the applied treatment. In the case of class B, the results show that it is essential to apply diffusing materials to the lower part of the classroom, in order to improve the first reflection and to ensure good comfort to receivers far from the source. In this way, we get consistent clarity and definition values by comparing the first row with the last row. Another consideration is to not have an absorbing ceiling but to apply a reflective material close to the professor in order to reach as far as possible the last rows with the first reflections. Absorbent material on the upper side of the classroom has always been present in all three optimizations and is therefore crucial to reducing reverberation time. Additionally, the work done allows you to export all the examinations made during the optimization in Excel files. This aspect has been useful in understanding the trend and acoustic response of the classroom according to the applied treatment. All the results obtained can be found in the appendix. It is possible to export various acoustic parameters without having to optimize them. An example is the last optimization performed where the price parameter has not been optimized but is present in the export of the analysis.

As already mentioned, this approach is applicable to various types of environments and, depending on the needs, it is possible to model it. In a short time, any designer will get a very accurate analysis and a solution that, depending on the desired parameters to be optimized, will best balance the outputs pre-set. Afterwards, the designer can use another analysis programs to get more accurate results than the solutions considered interesting by this preliminary study.

79

2.10 Conclusion

In conclusion, the proposed approach is useful and interesting for a preliminary analysis of environments with precise acoustic requirements. It is up to the designer to apply a specific optimization aimed at obtaining useful data for good acoustic design based on the type of environment.

80

81

82

82

3. Lighting The lighting design for a school needs to provide a lit environment which is appropriate for the particular interior and indeed exterior, achieving lighting which enables students and staff to carry out their particular activities easily and comfortably in attractive and stimulating surroundings.[1] Illumination in school environments plays a key role in making the school a pleasant and healthy environment for learning. Lighting, both natural and electrical, will be recognized as an essential contribution if it comes and encourages the fulfillment of school activities. Getting good lighting in the environment is not a purely formal goal, but it is necessary to create environments where users can carry out their tasks safely and comfortably. The research focuses on the study of natural light, which during daylight hours should always be the main source, integrated when fading with the electricity that will resume in the dark hours. Natural light is the best way to illuminate the environments and in this research will try to use it to the utmost to achieve schooling environments with high levels of lighting comfort. The lighting part differs somewhat from the acoustics as it considers a new case study in addition, a classroom located on the top floor of the building which has a remarkable natural light input with classroom B. The analyzes carried out on the two classrooms were done using traditional methods and dynamic methods (CBMD) and an accurate study of glare was also made. Then the idea is to create a parametric model in which the variable parameter is represented by the curtains. The curtains will perform shielding work to avoid excessive light in the classrooms to ensure good lighting comfort. The hypothesis of external shields has been eliminated at the outset since at the design level it is not possible to apply to a building such as the one under consideration, façade modifications. The study of lighting starts from the current situation of the Classroom B and Classroom Y with an analysis using traditional parameters following national standards and dynamic parameters using the Climate-Based Daylight Modeling. After an in-depth study of the current situation and having highlighted the major problems, an optimization will be made on the curtains of each classrooms. Finished the optimization we will get the best curve light transmission coefficient in relation to two fundamental parameters that are sDA and DAmax. These two parameters allow us to understand the amount of natural

Department for Education and Skills, Building Bulletin 90, “Lighting Design for Schools”. London: Stationery Office

1

83

3.1 Lighting design

light within the environment and in particular if it is useful or harmful. Three-dimensional models of the two classrooms were created on Rhinoceros and then exported to Grasshopper to make the parametric model. The analysis program on which all the analyzes were performed is DIVA (is a highly optimized daylighting and energy modeling plug-in for the Rhinoceros). Most of the analyzes were carried out with Diva-for-Grasshopper but it will be shown later in the search termination it was not possible to implement dynamic shading optimization as the program has limitations for the Grasshopper version.

3.1 Lighting design While considering plan, it is important to bear in mind various diverse and maybe opposing requirements and to do as such considering conceivable constraints.

It is additionally important to consider the general compositional idea and, thus, the deciding elements that will make it happen. While each component is essential and must be taken under consideration, the accentuation put on every perspective may not be the same. Figure 3.1 illustrates the main areas of consideration for the lighting design, along with the determining features and an indication of how they relate to each other.

84

3.1 Lighting design

Figure 3.1: Framework showing main components of lighting design & determining factors, from Building Bulletin 90, “Lighting Design for Schools”.

In the following subfolders they analyzed more thoroughly the structure to help the designer develop a strategy.

3.1.1 Task/Activity lighting It is fundamental to analyse the task/activity requirement before designing the lighting.

Practical lighting or assignment lighting is one that enables consumers to play out their different errands and assets with no visual disservices and it is essential that 85

3.1 Lighting design

the architect painstakingly considers these necessities. For school situations it is important to have a light level that makes it simple to perform very little and troublesome undertakings. Reading and composing, pecular school exercises, require a base level of light with a generally high luminance unit in the undertaking region.

Another critical viewpoint is the part that plays shading in learning and light sources must have great shading rendering execution; This will enable you to perform precise shading judgments. Since this prerequisite is essential for a scope of school exercises, for example, craftsmanship, science and specialties, it is prudent to utilize a decent shading light source in every single educational space. Visual solace is additionally vital keeping in mind the end goal to maintain a strategic distance from eye and brain pain, it is important to restrict the scope of brilliance inside the typical visual field. Coordinate daylight may likewise be an issue in these terms, relying upon the window introduction and its outline, and it is imperative that these possibly splendid sources are maintained at a strategic distance.

3.1.2 Lighting for visual amenity Illumination for the visual attitude is just as important as lighting the activities and depends on the balance and the composition of light and shadow.

Giving satisfactory lighting to a school’s undertakings and didactic spaces is obviously critical, yet it is not to be belittled to guarantee lighting that enhances the look of spatial lighting for visual interest. Indeed, it is important to light up the space to seem “brilliant” and “fascinating” and the unmistakable surfaces, for example, the dividers and maybe the roof add to this impression. You should likewise attempt to be mindful so as to make spaces of light and shadow since this could prompt visual distress. While coordinating daylight on the undertaking region can be an issue, an extra thought in visual convenience is the improvement of nature by the presence of sunlit zones; these could be available for corridors or in the outside view.

86

3.1 Lighting design

3.1.3 Lighting and achitectural integration Both electric and natural lighting must be an integral part of the architecture.

The lighting of a building, both regular and electrical, is additionally an estimation of design change and ought to subsequently be an indispensable piece of the venture. In the passages above, the significance of shine inside the school has been underlined, as well as the significance of reflections and the shade of the principle surfaces. It is attractive to utilize clear surfaces, so space will show up clearer, while attempting to utilize dull hues with miserliness. A standout amongst the most critical reflecting surfaces in a building is the floor and it is essential to have this light in shading. For lighting to work appropriately from the perspective of consumers and energy-efficient, they should have the composed and situated control changes to fit the utilization and state of the space. Considering this angle toward the start of the outline procedure, control circuits can be masterminded to enable electric lighting to coordinate common lighting in a positive and vivacious way.

3.1.4 Lighting and energy efficiency An effective use of energy in lighting is an essential part of lighting design.

A viable and effective utilization of vitality is an essential part of any lighting proposition and school structures are not a special case. This is to limit the utilization of essential vitality and thus decrease carbon dioxide discharges and furthermore, obviously, to diminish the running expense of each lighting establishment.

When arranging vitality productivity in lighting it is important to consider daylighting and electric lighting both separately and in conjunction with each other. A broad utilization of regular lighting can give significant vitality reserve funds yet sunlight is not “free” and the other natural parts of extensive coated regions must be considered. Equally by the watchful determination of vitality proficient electric lighting gear, introduced in a vitality successful route, together with controls which energize the utilization of electric lighting just when it is required, a vitality effective lighting framework can be accomplished. It is pointless to make such a vitality proficient plot if the outcome was traded off regarding execution and appearance. In these 87

3.1 Lighting design

conditions, consumers will regularly endeavor to enhance the lighting themselves, and maybe, in doing as such, annihilate the vitality effectiveness arranged.

3.1.5 Lighting maintenance Poor maintenance is a cause of bad lighting and is also a waste of energy and money.

Amid the life of a lighting establishment, the measure of light it produces will decrease with the progression of time. There are different reasons that make this execution decrease, the principle one is caused by dirt that sits on the lights , the luminaires, or on account of natural lighting, on the windows. Light yield will likewise diminish with maturing. Upkeep along these lines will assume a critical part in keeping up great lighting in the conditions and should be expected by great plan of the impingers.

3.1.6 Lighting costs Consider both capital and running costs in concert and avoid false economies.

The cost of lighting can be separated into two sections; The aggregate cost of the hardware, including its establishment and administration costs, which incorporate both upkeep and vitality costs. At configuration organize it is critical to remember these two angles that make up the venture. Actually, in the outline stage, it is important to consider the energy and support costs that are a consistent weight on the working of a school. For some schools, the two cost components might be borne by various bodies which can bring about an irreconcilable circumstance. It is vital along these lines that the lighting architect delivers a plan which takes an adjusted perspective of vitality and cost effectiveness, considering both capital and running expenses.

88

3.2 Lighting design standards

3.2 Lighting design standards This section will outline some rules for enlightenment in school environments. In particular, UNI 10840 will be analyzed for school premises and EUNI N 12464 that specifies lighting requirements in the workplace.

3.2.1 UNI EN 12464 The standard specifies lighting requirements for people, in indoor workplaces, which meet the requirements of visual comfort and visual performance of people with normal visual capabilities. All the usual visual tasks, including those involving the use of equipment equipped with video terminals, are considered. UNI 12464 says “This standard does not include specific solutions, it does not limit the designer’s freedom to experiment with new techniques or the application of innovative equipment.”

The realization of lighting tasks is conditioned by: • safety; • visual comfort; • limitation of glare; • color rendering.

Safety: • visibility of objects and work fields; • perception of dangerous obstacles; • it is necessary to associate the lighting with signage.

Visual comfort: “Visual comfort is an essential necessity for man that can affect work performance, health and safety, mood and atmosphere. Workers in the office can feel fatigued in the presence of a facility that produces glare in the lighting, but the same people can temporarily feel pleasure and feel excited by the flashing lights of a disco “(from the IES manual) 89

3.2 Lighting design standards

Vision: • the visibility of an object is associated with its contrast to the background. It would therefore be necessary to define a type object and to prescribe luminance levels for each job; • the multiplicity of objects and backgrounds makes this hypothesis unworkable; • therefore enlightenments are prescribed; • when color needs to be discriminated, a color yield index of at least 80 is required.

UNI EN 12464 prescribes dependent values from visual task for some lighting parameters: • lighting; • color rendering; • glare; • for uniformity, flickering and maintenance factor, the standard relies on the expertise and experience of the designer.

To get a good lighting concept, it is important to know the different classroom tasks.

Every activity needs its own light conditions. During the day there are a number of different visual tasks in a classroom. Hence, high requirements for light quality are important. Students and teachers benefit from illumination that supports them optimally in doing their business. Important for a good lighting design is that human needs are central, but at the same time energy efficiency can not be overlooked.

The European standard EN 12464-1 provides lighting requirements in schools and the following table lists these requirements.

90

3.2 Lighting design standards

Table 3.2 Overview of tasks in a classroom together with the requirements for the illuminances.

91

3.2 Lighting design standards

3.2.2 UNI 10840 The standard specifies the general criteria for the artificial and natural lighting of classrooms and other school premises, in order to guarantee the general conditions for the well-being and safety of students and other school users.

The standard defines lighting according to the activity, presents the mean daytime light factors for each school environment, as shown in the following table. The calculation method is shown in Appendix A. In order to ensure an adequate uniformity of natural lighting within the environments, the following reports regarding the daytime light factor must be guaranteed:

In order to avoid dazzling phenomena associated with excessive luminance contrast between glazed surfaces and opaque surfaces, the size and position of the glass surfaces and the reflection factors of the opaque walls should be checked.

In addition, adjustable light control systems such as curtains, blinds and screens should be provided to reduce dazzle in the presence of large glazing surfaces and in high luminance conditions of the celestial vault or visible outer surfaces. The use of devices that modify the spectrum of the transmitted light (eg glasses or athletic filters, tents) makes it necessary to verify the color of natural light within the rooms, in order to avoid the possibility of psycho-physical fatigue. To measure the natural color temperature of the natural light, the measurement can be conducted in front of the glazed surface, at a distance of 1.50 m, at a height of 0.85 m from the floor using a colorimeter.

The standard also includes dazzling due to natural light. It can be verified by the formula:

92

3.2 Lighting design standards

DGI - the index of glare; Gi - the dazzling constant calculated for each primary source portion and secondary, seen through the window (sky, obstructions, terrain); Ls - the source luminance (primary or secondary) in cd m-2; is the solid angle subtended by the source (primary or secondary) corrected in relation to the direction of observation in steradianti (sr); Lb - the average luminance of the internal surfaces of the environment, which fall into the field visual view of the occupant in cd m-2; Ω - the total solid angle subtended by the window in steradianti (sr); Lw - the average luminance of the window, weighted relative to the relative areas of the sky, obstruction and ground in cd m-2.

DGI reference values can be derived from the following table, or identified, in indicative terms, based on the match with dazzling due to artificial light.

Table 3.3 DGI limit values in relation to different activities

93

3.3 Design parameters of natural lighting

Table 3.4 Comparison of dazzling indices with natural light and glare rating criteria.

3.3 Design parameters of natural lighting In this section, two types of lighting, traditional and dynamic parameters will be explained. We will see their differences in terms of calculation. Their main difference is that traditional parameters do not take into account several key aspects for a good analysis such as the location of the building its orientation and can not have a good studio of glare. The traditional parameters have the following limitations: • Independent of the orientation of the environment (the luminance of the celestial vault, referred to the condition of the covered sky, is considered constant at the variation of the azimuth solar angle); • Independent of the locality (it does not vary with the latitude of the place); • Independent of the sky conditions (always consider a pattern of covered sky); • Independent of direct sun exposure (excludes direct solar radiation calculation); • Independent of the season; • Independent of the presence of mobile solar shades.

While dynamic parameter analysis generates a large amount of variable illumination values over time that need to be analyzed and synthesized. It would be necessary to treat the results in synthetic forms that can give an easy and intuitive evaluation of the amount of natural light in the environment. To date, climate-based 94

3.3 Design parameters of natural lighting

modeling has been used only in numerical simulations and never in real cases. The modeling mechanism has reached a very advanced level of study but there are still no internationally recognized guidelines for applying this type of approach. Most of the software that today is able to perform a climate-based modeling are based on Radiance’s calculation model. All subsequent implementations are reserved for expert users and very little understandable for a common designer.

3.3.1 Daylight factor (FLDm) The daylight factor is introduced a parameter for assessing the natural lighting inside a confined environment. It is currently recognized by the Italian legislation in the field of residential construction, school and hospital (Decreto Min. Sanità 5/7/75, Decreto Min. 18/12/75, Circ. Min. Lavori Pubblici n.13011, 22/11/74) and it is a priority to ensure optimal daytime lighting in the premises. Within a closed environment, the natural lighting in the different points of an internal space consists of three components: the contribution of light coming from the external primary sources (the sky, the sun), the contribution of light due to the reflections of the surfaces of any external local obstructions, the contribution of light due to multiple reflections that occur within the environment. In the evaluation of the internal natural lighting conditions it considers the most unfavorable case that occurs in the absence of direct solar radiation, characterized instead by a strong directionality in function of the position of the sun. Defined the overcast sky as an optimal condition evaluation, the relationship between interior and exterior lighting should be constant and should not depend neither the time of day, nor the time of year, nor the local orientation: it then introduces the factor daylight [FLD], synthetic size and dimensionless expressed as a percentage, defined as the ratio between the illumination measured in a specific point of the environment inside and outside the illumination measured on a horizontal surface that sees the whole time heavenly no obstructions in overcast conditions. In order not to limit the calculation of a single point is used the average daylight factor [FLDm], where average means for averaging over most of the internal environment measurement points in relation with the outside: in this way it is possible to better estimate global illumination in the local confined. The values required by the regulations may change according to the different destinations of use of environments: there are, however, the threshold values to below which are 95

3.3 Design parameters of natural lighting

not verified the natural lighting conditions sufficient to specific needs.

An indicative evaluation scheme can be the following: • • • •

FLDm < 1% = Insufficient 1% < FLDm < 2% = Discreet 2% < FLDm < 4% = Good FLDm > 4% = Excellent

Be limited to considering only the window areas for window/floor surface ratio does not meet the health standards in the premises: follow the average daylight factor means successfully deploy windows and assess its ability to ensure natural lighting conditions comfortable.

Af = net glass surface of the window [m2] τl = factor of light transmission of the glass ρl,m = light reflectance factor weighted average of the interior surfaces of the environment ε = window factor ϒ = reduction factor of window factor

3.3.2 Climate-based daylight modelling (CBDM) Climate-based daylight modelling (CBDM) is the prediction of various radiant or luminous quantities (e.g. irradiance, illuminance, radiance and luminance) using sun and sky conditions that are derived from standard meteorological datasets. Climate-based modelling delivers predictions of absolute quantities (e.g. illuminance) that are dependent both on the locale (i.e. geographically-specific climate data is used) and the building orientation (i.e. the illumination effect of the sun and non-o-

96

3.3 Design parameters of natural lighting

vercast sky conditions are included), in addition to the building’s composition and configuration. Climate-based daylight modelling consists of much more accurate analysis taking into account many more factors, to obtain a lighting assessment more defined respect to an analysis by traditional parameters.

The main index of Climate-based daylight modelling are: Daylight Autonomy - DA [%] Daylight Autonomy index developed by Reinhart and Walkenhorst, defines the percentage of time in the year in which the only natural light is able to ensure an illuminance predetermined minimum; Continuous Daylight Autonomy - DAcon [%] Continuous Daylight Autonomy proposed by Zack Rogers, is defined as the percentage contribution that the only natural light is able to provide, over the year, for the reaching the predetermined minimum illuminance value; Maximun Daylight Autonomy - DAmax [%] Maximun Daylight Autonomy is defined as the percentage of time in the year when the natural lighting in the environment it exceeds a certain value of illuminance, identified as 10 times the illuminance required for carrying out the visual task. The index indicates, therefore, the possibility of the occurrence of a potential condition of glare within the environment considered; Useful Daylight Illuminance - UDI [%] Useful Daylight Illuminance index proposed by John Mardaljevic and Nabil Azza in 2005; It indicates the percentage of time in which the natural light is “useful” in relation to the visual task done by the user, that is to say neither too low (<100lux), nor too high (> 2500lux, where this limit is set as a threshold beyond which the availability of light natural may be excessive, causing visual discomfort problems and / or thermal); Annual light exposure [luxh] Annual light exposure represents the cumulative amount of luminous flux incident on a surface within a year [lxh / year];

97

3.3 Design parameters of natural lighting

Spatial Daylight Autonomy - sDA [%] Spatial Daylight Autonomy[2] describes how much of a space receives sufficient daylight. Specifically, it describes the percentage of floor area that receives at least 300 lux for at least 50% of the annual occupied hours; Annual Sun Exposure - ASE [%] Annual Sun Exposure[3] describes how much of space receives too much direct sunlight, which can cause visual discomfort (glare) or increase cooling loads. Specifically, ASE measures the percentage of floor area that receives at least 1000 lux for at least 250 occupied hours per year.

2 IES Daylight Metrics Committee (2012). IES Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) (Report No. LM-83-12)

98

3.4 Case studies current situation

3.4 Case studies current situation As already anticipated before, the lighting study also takes into account another classroom. It was necessary to do this because the classroom B has a low light inside it so we have studied also the classroom Y which presents a greater amount of light inside it even if as we will see the dimensions and the main features are the same.

3d model used for lighting analyzes extracted from Rhinoceros. The model shows the location of the two classrooms in the facade of the school and also a part of urban context.

99

3.4 Case studies current situation

3.4.1 Classroom B

Classroom B plan

The classroom B is located on the ground floor with an elevation over the road surface of about 1.5 m and in front of it there is a building with a height of about 15 m that creates an important sun obstruction as the sun shines from mid-morning onwards. The environment has a south-east windows orientation. The twenty-four students are southward while the teacher is oriented to the east. The windowed wall is made up of three windows with a size of 1.40x3.17 m each.

Classroom B data: • • • • • 100

depth 6.60 m width 8.90 m height 4.30 m floor area 60.00 m2 volume 282.00 m3

3.4 Case studies current situation

• facade suface 38.00 m2 • size windows 3 x (1.40 x 2.87 m) • glazed surface 12 m2

3.4.1.1 3D Model

Classroom B Sun Path, 03/20 - 06/21 - 09/21 - 12/21, from 8.00am to 1.00pm.

The 3d model of study was modeled on Rhinoceros and is composed of a part of urban context, useful for a good analysis that includes all aspects that affect the light inside the classroom, of the school building and of the two classrooms examined. Then all geometry was imported on Grasshopper where it was used for the various analyzes carried out, to obtain a useful parametric geometry for the optimization we will see in the next paragraphs.

3D model layers (materials from DIVA): • environment - OutsideGround_10 • school - OutsideFacade_30 • floor - TileFloor_40 101

3.4 Case studies current situation

• • • • • •

wall - GenericInteriorWall_50 ceiling - WhiteInteriorWall_70 window - Glazing_SinglePane_88 door - GenericFurniture_50 desk - GenericFurniture_50 blackboard - GenericFurniture_50

View taken from Rhinoceros about the 3D model of the classroom B.

3.4.1.2 Traditional parameter analysis - DF Average Daylight Factor is currently the only index adopted in the national technical regulations and legislation that define the requirements for the quality and health of confined spaces. It allows you to define the percentage of natural light that you have inside an environment compared to what you have externally. It is a synthetic and dimensional indicator with which to characterize the luminous performance of the environment. The definition of this parameter implies, however, a set of simplifications of the real phenomenon that make it unimportant if it is to quantify the actual availability of natural light throughout the day and year.

Calculation of Average Daylight Factor (FLDm): 102

3.4 Case studies current situation

Af = 12 m2 (total) Atot = 264 m2 τl = 0.95 (simple transparent glass)

ρl,m = 0.68

wall n° 1 = 0.70 (common plaster or very light color card) wall n° 2 = 0.70 (common plaster or very light color card) wall n° 3 = 0.70 (common plaster or very light color card) wall n° 4 = 0.70 (common plaster or very light color card) floor = 0.50 (light colored floors) celing = 0.80 (common white plaster)

ϒ = 0.90 L (width window) = 1.40 m Hf (height window) = 2.87 m ρ (depth) = 0.27 m Hf/p = 10.62 L/p = 5.18

ε = 0.35 (with obstruction) H=5m h = 2.4 m

103

3.4 Case studies current situation

La = 11 m a° = 13.30° H - h / La = 0.23

Formula application:

FLDm = 2.90 % Good

104

3.4 Case studies current situation

The Daylight Factor was also calculated by DIVA-for-Grasshopper: Daylight Factor - DF 2.05 %

3.4.1.3 Analysis with dynamic parameters - CBDM The following analyzes were made using the Climate-based daylight modelling on DIVA-for-Grasshopper.

The grid used is located at 80 cm from the floor, it has a dimension of 560x745 cm and a grid spacing of 50 cm.

105

3.4 Case studies current situation

Daylight Autonomy - DA 59.00 % - threshold 300 [lux]

Continuous Daylight Autonomy - DAcon 76.16 %

106

3.4 Case studies current situation

DA Availability (37.95 %)- DAv upper threshold 3000[lux] - DAv time threshold 5[%]

Useful Daylight Illuminance - UDI 74.66 % - UDI threshold >100[lux] < 2000[lux]

107

3.4 Case studies current situation

UDI Underlit 100 [lux] - UDI Underlite 17.15 %

UDI Overlit 2000 [lux] - UDI Overlit 6.69 %

108

3.4 Case studies current situation

ASE Hours - ASE 60.20 %

Spatial Daylight Autonomy - sDA 66.00 % - sDA time threshold 50[%] Vertical Grid - DA Availability

109

3.4 Case studies current situation

CBDM analysis, composed of twenty-four vertical grids of dimensions 30x30 cm and a grid spacing of 15 cm, which reproduce the faces of students inside the classroom.

Consideration on CBDM study of Classroom B: The graphs extracted from the CBDM analysis show that the classroom B has sufficient daylight throughout the school year. The natural light guarantees a target of 300 lux for about 59% (Daylight Autonomy) of time, which falls within the recommended range of 40/60%.

In the Daylight Availability chart, underlines the row of desks near the windows could have any dazzling phenomena, as you notice areas with a Daylight Autonomy greater than 3000 lux for more than 25% of time during the year.

The Useful Daylight Illuminance (UDI) is about 75% so it is a good value that defines a workable illumination for the 3/4 of the year with a renge of 100 to 2000 lux.

Even the Spatial Daylight Autonomy is sufficient with a 66% of the surface where you have at least 300 lux for 50% of the use time.

Subsequently, for a more accurate study, the research has foreseen another CBDM analysis but this time with a vertical grid 30x30 cm that simulated the face of twenty-four students and calculated Daylight Availability. This has been done to be sure that there was no excessive natural light input directed at the face of the students. In fact, as we can see from the Vertical Grid image, we don’t have students with more than 3000 lux more than 5% lighting in the year.

In conclusion the classroom B doesn’t have excessive daylight and this aspect will also be found in the glare study.

110

3.4 Case studies current situation

3.4.1.4 Analysis with dynamic parameters - Glare

Position of the three views inside the classroom for the study of glare.

The glare study takes three points inside the classroom. The first one (n° 1) is in the teacher’s position, at a height of 1.50m, watching the pupils and in this case is oriented to the east. The second (n° 2) is located in the penultimate row of desks between the two students, looks towards the teacher in the south direction and at a height of 1.20m. The third point (n° 1) taken into account has the same characteristics as the second but its direction is toward the workbench.

These three positions taken into consideration were used for two types of glare study: one annually and the other on solstice and equinox days during classroom use hours. Doing so we will get a very accurate glare analysis that will allow us to get a lot of information about how natural light behaves towards the schoolroom.

111

3.4 Case studies current situation

Annual Glare Teacher B (schoolyearsepthrujun7to3withDST.60min.occ.csv)

Annual Glare Student B (schoolyearsepthrujun7to3withDST.60min.occ.csv)

Annual Glare Student desk B (schoolyearsepthrujun7to3withDST.60min.occ.csv)

112

hours 12:00 28% DGP

hours 11:00 22% DGP

hours 10:00 12% DGP

hours 09:00 24% DGP

3.4 Case studies current situation

Glare Teacher B - 03/20

113

hours 12:00 24% DGP

hours 11:00 27% DGP

hours 10:00 26% DGP

hours 09:00 30% DGP

3.4 Case studies current situation

Glare Teacher B - 06/21

114

hours 12:00 28% DGP

hours 11:00 25% DGP

hours 10:00 11% DGP

hours 09:00 23% DGP

3.4 Case studies current situation

Glare Teacher B - 09/23

115

hours 12:00 03% DGP

hours 11:00 03% DGP

hours 10:00 03% DGP

hours 09:00 03% DGP

3.4 Case studies current situation

Glare Teacher B - 12/21

116

hours 12:00 23% DGP

hours 11:00 09% DGP

hours 10:00 05% DGP

hours 09:00 20% DGP

3.4 Case studies current situation

Glare Student B - 03/20

117

hours 12:00 19% DGP

hours 11:00 25% DGP

hours 10:00 27% DGP

hours 09:00 30% DGP

3.4 Case studies current situation

Glare Student B - 06/21

118

hours 12:00 22% DGP

hours 11:00 26% DGP

hours 10:00 04% DGP

hours 09:00 17% DGP

3.4 Case studies current situation

Glare Student B - 09/23

119

hours 12:00 01% DGP

hours 11:00 01% DGP

hours 10:00 01% DGP

hours 09:00 01% DGP

3.4 Case studies current situation

Glare Student B - 12/21

120

hours 12:00 26% DGP

hours 11:00 05% DGP

hours 10:00 04% DGP

hours 09:00 27% DGP

3.4 Case studies current situation

Glare Student desk B - 03/20

121

hours 12:00 17% DGP

hours 11:00 25% DGP

hours 10:00 28% DGP

hours 09:00 40% DGP

3.4 Case studies current situation

Glare Student desk B - 06/21

122

hours 12:00 24% DGP

hours 11:00 23% DGP

hours 10:00 03% DGP

hours 09:00 25% DGP

3.4 Case studies current situation

Glare Student desk B - 09/23

123

hours 12:00 01% DGP

hours 11:00 01% DGP

hours 10:00 01% DGP

hours 09:00 01% DGP

3.4 Case studies current situation

Glare Student desk B - 12/21

124

3.4 Case studies current situation

Consideration on glare study of Classroom B: As anticipated in the preliminary study phase, the study of glare highlights the criticalities associated with the orientation of the classroom. As we can see from the results obtained, the higher DGP values refer to the months of May of June and in particular strike the teacher more because it is oriented towards the south. The classroom B has a building in front of it that creates an obstruction of the sun from late morning onwards. This guarantees shadowing at the morning of the classroom but in the early lesson we can say that the taught is what has a greater discomfort. The glare of the teacher however never exceeds 35% of DGP but it has a peak of 30% on day 06/21 at 09am. The same dazzling behaviour is presented to the Student B that has a maximum DGP of 30% in the early hours of classroom use in June.

Instead, the study of glare of Student desk B shows how the sun acts in the classroom in particular in June where the sun’s path is higher and hits the banks near the windows creating, as you can see in the punctual study of the glare, many areas illuminated on the work surface. Overall, the glare study of the classroom B only has a value beyond the limit threshold of 35% DGP and this shows up in the Student desk B on day 06/21 at 09am with a value of 40% DGP. In conclusion, the classroom B doesn’t have any major glare problems as we have seen from the CBDM study doesn’t present a large amount of light within it. In the next phase, however, we should take into account the considerations we have drawn from this study in such a way as to ensure a good lighting comfort for the students and the teacher.

125

3.4 Case studies current situation

3.4.2 Classroom Y features

Classroom B plan

The classroom Y is located on the second and has no obstruction so it has a greater amount of sunshine throughout the day . The environment has a south-east windows orientation. The twenty-four students are eastward while the teacher is oriented to the south. The windowed wall is made up of three windows with a size of 1.40x3.17 m each.

Classroom Y data: • • • • • • • • 126

depth 6.60 m width 8.90 m height 4.30 m floor area 58.00 m2 volume 279.00 m3 facade suface 38.00 m2 size windows 3 x (1.40 x 2.87 m) glazed surface 12 m2

3.4 Case studies current situation

3.4.2.1 3D Model classroom B

Classroom Y Sun Path, 03/20 - 06/21 - 09/21 - 12/21, from 8.00am to 1.00pm.

The 3d model of study was modeled on Rhinoceros and is composed of a part of urban context, useful for a good analysis that includes all aspects that affect the light inside the classroom, of the school building and of the two classrooms examined. Then all geometry was imported on Grasshopper where it was used for the various analyzes carried out, to obtain a useful parametric geometry for the optimization we will see in the next paragraphs.

3D model layers (materials from DIVA): • environment - OutsideGround_10 • school - OutsideFacade_30 • floor - TileFloor_40 • wall - GenericInteriorWall_50 • ceiling - WhiteInteriorWall_70 • window - Glazing_SinglePane_88 127

3.4 Case studies current situation

• door - GenericFurniture_50 • desk - GenericFurniture_50 • blackboard - GenericFurniture_50

View taken from Rhinoceros about the 3D model of the classroom Y.

3.4.2.2 Analysis with traditional parameters Average Daylight Factor is currently the only index adopted in the national technical regulations and legislation that define the requirements for the quality and health of confined spaces. It allows you to define the percentage of natural light that you have inside an environment compared to what you have externally. It is a synthetic and dimensional indicator with which to characterize the luminous performance of the environment. The definition of this parameter implies, however, a set of simplifications of the real phenomenon that make it unimportant if it is to quantify the actual availability of natural light throughout the day and year.

Calculation of Average Daylight Factor (FLDm): Af = 12 m2 (total) Atot = 269 m2

128

3.4 Case studies current situation

τl = 0.95 (simple transparent glass) ρl,m = 0.68

wall n° 1 = 0.70 (common plaster or very light color card) wall n° 2 = 0.70 (common plaster or very light color card) wall n° 3 = 0.70 (common plaster or very light color card) wall n° 4 = 0.70 (common plaster or very light color card) floor = 0.50 (light colored floors) celing = 0.80 (common white plaster)

ϒ = 0.90 L (width window) = 1.40 m Hf (height window) = 2.87 m ρ (depth) = 0.27 m Hf/p = 10.62 L/p = 5.18

ε = 0.50 (vertical surfaces without obstructions) Formula application:

129

3.4 Case studies current situation

FLDm = 4.2 % Excellent

The Daylight Factor was also calculated by DIVA-for-Grasshopper: Daylight Factor - DF 3.35 %

3.4.2.3 Analysis with dynamic parameters The following analyzes were made using the Climate-based daylight modelling on DIVA-for-Grasshopper. The grid used is located at 80 cm from the floor, it has a dimension of 520x710 cm and a grid spacing of 50 cm.

130

3.4 Case studies current situation

Daylight Autonomy - DA 77.77 % - threshold 300 [lux]

Continuous Daylight Autonomy - DAcon 84.73 %

131

3.4 Case studies current situation

DA Availability (1.4%)- DAv upper threshold 3000[lux] - DAv time threshold 5[%]

Useful Daylight Illuminance - UDI 62.98 % - UDI threshold >100[lux] < 2000[lux]

132

3.4 Case studies current situation

UDI Underlit 100 [lux] - UDI Underlite 12.39 %

UDI Overlit 2000 [lux] - UDI Overlit 23.16 %

133

3.4 Case studies current situation

ASE Hours - ASE 175.15 %

Spatial Daylight Autonomy - sDA 100.00 % - sDA time threshold 50[%]

134

3.4 Case studies current situation

Vertical Grid - DA Availability

CBDM analysis, composed of twenty-four vertical grids of dimensions 30x30 cm and a grid spacing of 15 cm, which reproduce the faces of students inside the classroom.

Consideration on CBDM study of Classroom Y: The CBDM analysis of classroom Y show values completely different from the the results of classroom B. The Daylight Autonomy has a value of about 78% which exceeds the recommended range of 40/60%. In fact this high value of DA already anticipates the possibility of glare problems inside the classroom Y. Particular attention should be paid to the DA Availability chart that highlights in most of the grid we have values of DA more than 3000 lux for a period longer than 5% of the year reaching cases where we have a percentage of 42%. The values of UDI related to the other classroom are lower while having a greater DA and this is verified by consulting the percentage of UDI overlit that is 23%. Subsequently, for a more accurate study, we did another CBDM analysis but this time we created various vertical 30x30 cm planes that simulated the face of twenty-four students and calculated Daylight Availability. This chart shows how the students in the row near the window and much of the central row receive a large amount of light in the face. In conclusion the cbdm analysis anticipates that we should pay particular attention to the study of glare because there is a large amount of natural light inside the classroom Y.

135

3.4 Case studies current situation

3.4.2.4 Analysis with dynamic parameters - Glare

Position of the three views inside the classroom for the study of glare.

The glare study takes three points inside the classroom. The first one (n° 1) is in the teacher’s position, at a height of 1.50m, watching the pupils and in this case is oriented to the south. The second (n° 2) is located in the penultimate row of desks between the two students, looks towards the teacher in the east direction and at a height of 1.20m. The third point (n° 1) taken into account has the same characteristics as the second but its direction is toward the workbench. These three positions taken into consideration were used for two types of glare study: one annually and the other on solstice and equinox days during classroom use hours. Doing so we will get a very accurate glare analysis that will allow us to get a lot of information about how natural light behaves towards the schoolroom.

136

3.4 Case studies current situation

Annual Glare Teacher Y (schoolyearsepthrujun7to3withDST.60min.occ.csv)

Annual Glare Student B (schoolyearsepthrujun7to3withDST.60min.occ.csv)

Annual Glare Student desk B (schoolyearsepthrujun7to3withDST.60min.occ.csv)

137

hours 12:00 24% DGP

hours 11:00 29% DGP

hours 10:00 30% DGP

hours 09:00 33% DGP

3.4 Case studies current situation

Glare Teacher Y - 03/20

138

hours 12:00 21% DGP

hours 11:00 25% DGP

hours 10:00 29% DGP

hours 09:00 30% DGP

3.4 Case studies current situation

Glare Teacher Y - 06/21

139

hours 12:00 23% DGP

hours 11:00 27% DGP

hours 10:00 31% DGP

hours 09:00 75% DGP

3.4 Case studies current situation

Glare Teacher Y - 09/23

140

hours 12:00 24% DGP

hours 11:00 27% DGP

hours 10:00 26% DGP

hours 09:00 24% DGP

3.4 Case studies current situation

Glare Teacher Y - 12/21

141

hours 12:00 27% DGP

hours 11:00 31% DGP

hours 10:00 35% DGP

hours 09:00 34% DGP

3.4 Case studies current situation

Glare Student Y - 03/20

142

hours 12:00 22% DGP

hours 11:00 25% DGP

hours 10:00 28% DGP

hours 09:00 31% DGP

3.4 Case studies current situation

Glare Student Y - 06/21

143

hours 12:00 26% DGP

hours 11:00 29% DGP

hours 10:00 34% DGP

hours 09:00 32% DGP

3.4 Case studies current situation

Glare Student Y - 09/23

144

hours 12:00 27% DGP

hours 11:00 30% DGP

hours 10:00 31% DGP

hours 09:00 23% DGP

3.4 Case studies current situation

Glare Student Y - 12/21

145

hours 12:00 26% DGP

hours 11:00 39% DGP

hours 10:00 34% DGP

hours 09:00 32% DGP

3.4 Case studies current situation

Glare Student desk Y - 03/20

146

hours 12:00 21% DGP

hours 11:00 25% DGP

hours 10:00 27% DGP

hours 09:00 39% DGP

3.4 Case studies current situation

Glare Student desk Y - 06/21

147

hours 12:00 24% DGP

hours 11:00 32% DGP

hours 10:00 36% DGP

hours 09:00 31% DGP

3.4 Case studies current situation

Glare Student desk Y - 09/23

148

hours 12:00 22% DGP

hours 11:00 25% DGP

hours 10:00 30% DGP

hours 09:00 22% DGP

3.4 Case studies current situation

Glare Student desk Y - 12/21

149

3.4 Case studies current situation

Consideration on glare study of Classroom B: The annual glare shows how the position of the student and the teacher influences glare during the school year. In fact, the teacher is most impressed in the winter and autumn months. While students are subject to strong dazzling in the spring and summer months, especially March and September. Going to study more specifically, with the timely glare analysis, we see how the teacher in March is subjected to the early hours of the lesson at a glare ranging between 30% and 35% of DGP. Also in September we notice a strong dazzle in the early hours of the morning especially at 9:00 am where the teacher is subjected to a dazzling 75% DGP. The students instead have a dazzle given from 9 am to 11 am in the months of March and September, ranging from 30% to 35% of DGP. While their work area has a similar glare in time but with slightly higher values reaching to peak in March at 11:00 am with a value of 39% of DGP. For this case study we should pay more attention to the subsequent design phases since both CDBM and glare analysis show excessive natural light inside the classroom creating an excessive discomfort to those who enjoy it.

150

3.5 Case studies comparison

3.5 Case studies comparison The following table shows the comparison of the traditional and dynamic parameters of the two newly analyzed classrooms. Analysis of the current situation has highlighted the great difference in exposure to the natural light of the two case studies. The most influential factor is the location, in fact, the classroom B is on the ground floor and screened for a good part of the day from a front building. While the classroom Y has a more favorable position at the entrance to natural light, it is placed on the second floor and has no building that shields it. This generates a clear difference in CBMD results and in particular in the glare study as previously shown.

Table X.X results comparison of Classroom B and Y.

By analyzing more specifically the results of the analyzes, they show how the Daylight Factor parameter meets the minimum requirements of Italian standards, but there is still a clear difference in values of the two classroom.

Dynamic parameters explain in greater detail this difference, in fact, we have satisfactory DA values for the two rooms even though for class B it seems to be just satisfactory. The difference of the natural light is well expressed by the DAcon index, which expresses the percentage of time when only natural light guarantees a target of 300 lux. In the Classroom Y this index is about 85%, but this does not mean that all of this incoming light is great for good lighting comfort. As can be seen from the 151

3.6 Lighting design

UDI index, the large amount of light of the Classroom Y appears to be excessive and will present, as already seen in the study of the glare, problems of excessive illumination. The UDI index highlights this fact, in fact, Classroom B has a higher UDI value than Classroom Y while having lower DA and sDA values. By comparing UDI overlit values, show a clear difference and demonstrate how in Classroom Y you will need a screening intervention to avoid discomfot situations within the school environment. For 23% of the time in the Classroom Y there is a natural light not useful but even detrimental to learning.

This comparison highlighted the great difference between the two classrooms and shifted our attention to the Classroom Y. In the following paragraphs, the study of shielding will only be made to Classroom Y, as Classroom B does not show any apparent criticality during throughout the school year.

3.6 Lighting design Illumination design is the main subject of the Classroom Y, since as previously shown, class B does not have a large amount of natural light and no obvious glare problems throughout the year. So, as a case study, the Classroom Y has been chosen, which presents a large amount of light due to its position without any building that creates obstacles to light. Throughout the year it receives direct light coming from the southeast. The aim of the research was to create a parametric model in which a good amount of curtains could be tested within the environment in relation to two main parameters: sDA calculated with a target of 300 lux and DA max calculated with a target of 500 lux. These two parameters have been chosen because they are important in understanding how much light is distributed on the work surface and how much is harmful to the users. A parametric model was then created in which the geometry layers presented a series of materials to be applied during optimization. But later during the study it has been shown that this kind of approach can not be implemented. This inability to proceed with optimizing curtains is due to the fact that the program DIVA-for-Grasshopper does not show the same settings as DIVA-for-Rhinoces to manage the dynamic shading. As a result, the study shifted on Rhinoceros and two main curves were studied with diffuse diffuse transmission 152

3.6 Lighting design

characteristics and analyzing them individually.

3.6.1 Classroom Y study model The classroom B model for dynamic shading study differs from the current situation model for the presence of curtain application. Initially they were waxed using Honeybee a list of materials referring to curtains. The figure below shows the list of curtain materials where each material presents a different percentage of the diffuse transmission coefficient (from 10% to 50%).

Figure X.X creating curtain materials

Since we can’t proceed with optimization to get the best curtain with the optimum transmission coefficient for our environment, the research has studied three main materials, materials with a transmission percentage of 10%, 30% and 50%. The intention to optimize a list of curtains according to two different parameters was not possible, so using DIVA-for-Rhinoceros will be analyzed three types of curtains with different transmission coefficients. In the study process a curtain level was created within the three-dimensional model of the Classroom Y. At this tide level, different 153

3.6 Lighting design

materials with different properties will be applied to understand which transmission percentage is better for our case study. The following figure shows the model created on Rhinoceros and the various dynamic shading settings. The geometry of the curtain material was molded like glass and a 5cm offset to the inside of the classroom was made.

Figure X.X model Classroom Y created in Rhinoceros and setting of dynamic shading.

Shading settings provide a type of mechanical shading with an activation set to 5000 lux and a deactivation set to 500 lux. In the next paragraphs, three types of curtains with different light transmission properties will be tested to give an indication of what type of curtain will be required to obtain a well-lit and gluten-free environment.

154

3.6 Lighting design

3.6.1.1 Test n° 1 Curtain material_00 diffuse transmission10% Daylight Area (DA300lux[50%]): 94% of floor area Mean Daylight Factor: 3.4% Shading 70% of occupied hours Daylight Autonomy (DA) Analysis: The mean daylight autonomy is 68% for active occupant behavior. The percentage of the space with a daylight autonomy larger than 50% is 94% for active occupant behavior.

Continuous Daylight Autonomy (DA) Analysis: The mean continuous daylight autonomy is 85% for active occupant behavior. The percentage of sensors with a DA_MAX > 5% is 7% for active occupant behavior.

Useful Daylight Illuminance (UDI): The percentage of the space with a UDI<1002000lux larger than 50% is 100% for active occupant behavior.

Daylight Area (DA300lux[50%]):

155

3.6 Lighting design

DA availability (500 lux): the percentage of sensors with a DA_MAX > 5% is 0% for active occupant behavior.

Shading control: The system is automatically controlled in a way that excessive interior daylighting levels are avoided. When the illuminance at any of the the control sensors rises beyond 5000 lux, the system automatically readjusts to the next lower setting. If the system is not fully opened and the illuminance at a control sensor falls below 500 lux the system is opened to the next higher state.

156

3.6 Lighting design

3.6.1.2 Test n° 2 Curtain material_05 diffuse transmission30% Daylight Area (DA300lux[50%]): 100% of floor area Mean Daylight Factor: 3.4% Shading 54% of occupied hours Daylight Autonomy (DA) Analysis: The mean daylight autonomy is 76% for active occupant behavior. The percentage of the space with a daylight autonomy larger than 50% is 100% for active occupant behavior.

Continuous Daylight Autonomy (DA) Analysis: The mean continuous daylight autonomy is 89% for active occupant behavior. The percentage of sensors with a DA_MAX > 5% is 3% for active occupant behavior.

Useful Daylight Illuminance (UDI): The percentage of the space with a UDI<1002000lux larger than 50% is 100% for active occupant behavior.

Daylight Area (DA300lux[50%]):

DA availability (500 lux): the percentage of sensors with a DA_MAX > 5% is 0% for 157

3.6 Lighting design

active occupant behavior.

Shading control: The system is automatically controlled in a way that excessive interior daylighting levels are avoided. When the illuminance at any of the the control sensors rises beyond 5000 lux, the system automatically readjusts to the next lower setting. If the system is not fully opened and the illuminance at a control sensor falls below 500 lux the system is opened to the next higher state.

158

3.6 Lighting design

3.6.1.3 Test n° 3 Curtain material_10 diffuse transmission 50% Daylight Area (DA300lux[50%]): 100% of floor area Mean Daylight Factor : 3.4% Shading 46% of occupied hours Daylight Autonomy (DA) Analysis: The mean daylight autonomy is 77% for active occupant behavior. The percentage of the space with a daylight autonomy larger than 50% is 100% for active occupant behavior.

Continuous Daylight Autonomy (DA) Analysis: The mean continuous daylight autonomy is 89% for active occupant behavior. The percentage of sensors with a DA_MAX > 5% is 12% for active occupant behavior Useful Daylight Illuminance (UDI): The percentage of the space with a UDI<1002000lux larger than 50% is 100% for active occupant behavior.

Daylight Area (DA300lux[50%]):

159

3.6 Lighting design

DA availability (500 lux): the percentage of sensors with a DA_MAX > 5% is 0% for active occupant behavior.

Shading control: the system is automatically controlled in a way that excessive interior daylighting levels are avoided. When the illuminance at any of the the control sensors rises beyond 5000 lux, the system automatically readjusts to the next lower setting. If the system is not fully opened and the illuminance at a control sensor falls below 500 lux the system is opened to the next higher state.

160

3.7 Conclusion

3.7 Conclusion As seen in the previous chapters, it was not possible to run a full optimization simulation for curtains. This limitation led to studying three significant types of curtains, each with a different transmission properties. The classroom in which the shading study was carried out using curtains is an environment that presents an excessive amount of natural light in its full. In fact, the preliminary study has highlighted many critical issues, one of them is the presence of prolonged glare throughout the year for both students and teacher. By comparing the three types of curtains used, it is possible to make some considerations about their application within the school environment. Applying a curtain with a 10% diffuse transmission coefficient generates reduced sDA and DA values compared to the current situation and 70% occupation of shading during use. The shading control chart shows the activation and deactivation of friable curtains over the course of the day and leads us to assert that this type of tent does not meet the requirements of good lighting comfort.

While the results of analysis with the application of curtains with diffuse transmission coefficients of 30% and 50% are more interesting. They have higher sDA and DA values and the activation of shading is distributed better throughout the year. The most interesting curtain is that of 30% because it has balanced DA values and in particular a shading control of about 50% during the year. The analysis carried out shows how this type of curtain is able to obtain good comfort within the studied environment. It also showed that curtains with a diffuse transmission higher than 30% gave decent results and can be redeemed acceptable for the scenario above.

An objective was set at the beginning of this study, having a parametric model for the classroom with parameters that can be varied. Unlike the acoustics research, the lighting part highlighted various limitations that led to difficulties with the goal stated above. In fact, it was not possible to reach the desired goal. This was caused by the limitation of the program used and in particular by the type of target set. In fact, the proposed work took a lot of time and long hours of analysis. Considering that this thesis seeks to propose a preliminary analysis method that can be applied in both acoustic and lighting design, the requirement to be able to conduct short-time analysis is definitely crucial. The study has moved from wanting to perform an automatic optimization of the curtain, to performing individual tests for curtains with different parameters. In any case, it was able to give a guideline on how to interve161

3.7 Conclusion

ne within the school environment but in our view it did not meet the pre-requisites of the research. In conclusion, the proposal of the lighting study was not entirely satisfactory and has highlighted some limitations of the program. The study still managed to get a large number of data from the existing state of the classroom, which is considered beneficial for performing a careful lighting design. Based on the results of the lighting study, it was possible to give a guideline on what type of curtain to choose. The requisite for a fast preliminary analysis was not met because it was not possible to launch a single optimization on the parametric model but manual simulations for the three types of curtains had to be launched. Testing these various materials significantly increases the time of the proposed preliminary approach.

This is considered not productive, the designer should not spend this much time on the preliminary study of a single component like the properties of a curtain.

162

163

164

Appendix A Multi-objective optimization results, type of ceiling n° 1.

165

166

167

168

169

170

171

172

Appendix B Multi-objective optimization results, type of ceiling n° 2.

173

174

175

176

177

178

179

180

181

Appendix C Multi-objective optimization results, type of ceiling n° 1 and 2.

182

183

184

185

186

187

188

Bibliography Astolfi A., Bottalico P., Bronuzzi F., “Indagini oggettive e soggettive sull’infl uenza del rumore e della riverberazione sullo sforzo vocale di insegnanti di scuola primaria”.

In: isl. Igiene & sicurezza del lavoro. I corsi (2014); Astolfi A., Corrado V., Griginis A., “Comparison between measured and calculated arameters for the acoustical characterization of small classrooms”, Applied Acoustics (2008); Astolfi A., Pellery F., “Subjective and objective assessment of acoustical and overall environmental quality in secondary school classrooms”, JASA (2008); Choi Y., “Effects of periodic type diffusers on classroom acoustics”, Applied acoustics 74 (2013); Choi Y., “Experimental investigation of the combination of absorptive and diffusive treatments in classrooms” (2015); Barron M. “Auditorium acoustics and architectural design”, 2nd ed. London: E &FN Spon (2009); Bradley JS, “Speech intelligibility studies in classrooms”, J Acoust Soc Am (1986); Bradley JS, “Reich R, Norcross SG. On the combined effects of signal-to-noise ratio and room acoustics on speech intelligibility”. J Acoust Soc Am (1999); Bradley JS, Sato H, Picard M. “On the importance of early refl ections for speech in rooms”, J. Acoust. (2003); Cherry E. C., “Some experiments on the recognition of speech with one and with two ears”. Journal of the Acoustical Society of America (1953); British standard 8233:1999, “Sound insulation and noise reduction for buildings code of practice” (1999); Commins D., “Survey of UK voice clinics 2001/2 (2002)”. Voice Care Network UK (2002);

189

Department for Education and Skills, Building Bulletin 93, “Acoustic Design of School”, London: Stationery Office (2003); Hygge S., Evans G.W. and Bullinger M., “The Munich Airport noise study: Cognitive effects on children from before to after the change over of airports”, Proceeding of internoise ‘96 (1996); Kidd, G., Mason, C. R., Richards, V. M., Gallun, F. J., and Durlach, “Informational masking in Auditory Perception of Sound Sources” N. I. (2008); Kob M., Behlery G., Kamprolfz A., Goldschmidtx O., Neuschaefer-Rube C., “Experimental investigations of the influence of room acoustics on teachers’ voice”, Acoust. Sci. & Tech. (2008); Leijska V., “Occupational voice disorders in teachers”, Pracovini Lekarstvi 19 (1967); Lindsey R. B., “Wheel of acoustics” in J. Acoust. (1964); Loreti L., Barbaresi L., D’Orazio D., Garai M., “La percezione del parlato all’interno dell’aula magna della facoltà di ingegneria di Ravenna: caratterizzazione ed interventi migliorativi”, AIA (2016); Oliaro P., “Rumore degli impianti tecnologici”, in Manuale di acustica applicata (2007); Pamphlet WHO, Regional Office for Europe, n.38, Noise in Schools (2001); Bolognesi F., “Prevision of optimal speech intelligibility in primary school classrooms through simulation of optimal acoustic absorption and diffusion conditions”, Mater Thesis, Politecnico di Torino (2016); Department for Education and Employement, Building Bulletin 90, “Lighting design for schools”, London: Stationery Office (2014); Pellegrino Anna, Cammarano Silvia, Savio Valeria, Daylighting for Green Schools: 190

“A Resource for Indoor Quality and Energy Efficiency in Educational Environments” (2015).

191