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Sebastian Białkowski Bachelor of Architecture and Urbanism Technical University of Lodz (TUL), Poland, 2011 1st Advisor: KRASSIMIR KRASTEV 2nd Advisor: ALEXANDER KALACHEV



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Visionary Prototypes

The Material Performance Studio will continue the pursuit to develop visionary prototypes for habitation, from the scale of a single dwelling to an entire neighbourhood, creating tectonics that engage landscape, topography and infrastructure, while remaining flexible and adaptive to unpredictable behavioural patterns of the future occupants. Prototyping will be executed in different media: rough, malleable, analogue, hand-crafted mock-ups and precise, digitally calibrated structural assemblies will be developed in an iterative process of fabricating design alternatives, testing hypotheses, and progressively refining the prototypes while improving their performance.

Material and Simulation

Matter, data and energy flows will be studied as the outcome of the interaction between differential gradients; experimental simulations will be carried out to test material properties and behaviour in a dynamic environment, in order to inform educated decisions early in the design process. Harnessing the power of computation to process environmental data, energy flow calculations, structural analysis and material behaviour simulation, the resulting designs will be charged with the power of fluctuating gradients that keep energy and matter in constant transformation.

Technology and Optimization

Embedded sensors coupled with artificial intelligence algorithms will enable the prototypes to be responsive agents with real-time behavioural adjustment informed by collected data on trajectories of past behaviour. Taking advantage of computational power, interactive and sensory devices, the prototypes will be designed as agents situated in a dynamic environment, remaining tolerant and adaptive to the ever-changing demands of unpredictable occupant behaviour. Digitally calibrated assemblies with adjustable performance responsive to dynamically changing environmental pressures will ultimately re-define the meaning of Optimization, shifting the quality of efficiency towards multiple and variable optimal states. Krassimi Krastev




We are living in a world of changes. Rapid changes. Needs of society from a decade to decade change very quickly, which has a great impact on the functionality of modern buildings. Costs adaptability of old buildings to new demands often exceed the budget for a new design from scratch. he design requirements that are imposed contemporary engineers and designer, make it necessary to formulate new design guidelines. The design strategy undertaken in this paper will try to solve the problems of rational use of the material, its effective use to allow complete freedom in the creation of space. Establishing of a system, which gives the possibility of evolution the building over time, simultaneously optimizing its structure, leading to the sustainable use of the material.



Load Reactive Morphogenesis is considering bone-tissue behaviour as a principle for the definition of a material distribution system into adaptable structures for architecture. Research lead to numerical algorithms which are principle to understood analysis and optimization method. Based on Wolf’s law, which describes the transformations of material patterns in bones in response to changing stress distributions, the building system optimizes material densities according to variable loads. However, this does not mean that whole design process is controlled by algorithm. Their distribution is closely related and dependent on the decision of architect and engineers. Dwelling location, it area, volume or users habits, influence whole buildings structure appearance. By knowing this algorithms neither advantages or limits, correctly prepared and designed initial conditions can receive the most efficient main building structure with wide freedom of form creation.



Form, structure and material act upon each other, and this behaviour of all three cannot be predicted by analysis of any one of them separately. The self-organisation of biological material systems is a process that occurs over time, a dynamic that produces the capacity for changes to the order and structure of a system, and for those changes to modify the behaviour of that system. The characteristics of self-organisation include a 3-D spatial structure, redundancy and differentiation, hierarchy and modularity.










Habitat 67, or simply Habitat, is a model

community and housing complex in Montreal, Canada, designed by Israeli–Canadian architect Moshe Safdie. It was originally conceived as his master’s thesis in architecture at McGill University. This creation, an experiment in apartment living, became the permanent symbol of Expo 67, the World’s Fair held from April to October 1967. It is located at 2600 Avenue Pierre-Dupuy on the MarcDrouin Quay next to the Saint Lawrence River. Habitat 67 is widely considered an architectural landmark and one of the most recognizable and significant buildings in both Montreal and Canada. Habitat 67 comprises 354 identical, prefabricated concrete forms arranged in various combinations, reaching up to 12 storeys in height. Together these units create 146 residences of varying sizes and configurations, each formed from one to eight linked concrete units. The complex originally contained 158


apartments, but several apartments have since been joined to create larger units, reducing the total number. Each unit is connected to at least one private terrace, which can range from approximately 20 to 90 m2 in size.






revolution in the way homes were built - by the industrialization of the building process; essentially factory mass production. He felt that it was more efficient to make buildings in factories and deliver them prefabricated to the site. Safdie was dissatisfied with both suburbia, which destroyed open space surrounding cities and cut off people’s enjoyment of the amenities of city life, and with the high-rise apartment block, which concentrated people on less land. The development was designed to integrate the benefits of suburban homes, namely gardens, fresh air, privacy, and multilevelled environments, with the economics and density of a modern urban apartment building. It was believed to

illustrate the new lifestyle people would live in increasingly crowded cities around the world. He wanted to build a city in the sky, a 3- D city and his city would contain 1000 housing units, with shops and even a school. What he proposed was an experiment, not just in housing, but in community life. He planned Habitat with the goal to find a way to put a great many people on a small space, yet provide them with at least some of the pleasures of a private home. But between 1964 and 1966 when construction started, it was downsized to only 158 dwelling units, without shops and a school. What started out as a plan for a small city, instead became a hugely expensive apartment building.

Safdie’s goal for the project to be

affordable housing largely failed: demand for the building’s units has made them more expensive than originally envisioned. While factory production techniques should have cut overall costs, building 158 apartments isn’t really


productive in factory work since there is often a steep learning curve. Also since the individual units would bear the weight load of the units above, the units on the bottom where actually thicker and stronger. In the end Habitat 67 cost $22,195,920, or about $140,000 per living unit. Effectively that was the same cost as building six-eight ordinary town houses. Luckily one could rationalize that it was only a prototype, and if scaled up, it might be much cheaper to construct. A factory was built beside the Habitat site. It contained four large molds in which the standardized units were made. To make each of them, a reinforcing steel cage was placed inside the mold, then concrete was poured around the cage. After the concrete cured, the unit was moved to an assembly line where a wooden sub-floor was installed with electrical and mechanical services below it. Windows and in

sulation were then inserted; afterwards prefabricated bathrooms and kitchen modules. Finally the unit was moved to its position in the building. They were arranged to provide fifteen different types of “houses”. These varied from one-bedroom houses (35 m2) to four-bedroom houses (160 m2). Each had a private open garden space, 11 x 3,5 m. Each man’s roof was another man’s garden. The arrangement of the units provided privacy and the variation in house layouts provides a sense of uniqueness.

While the visiting public was impressed, they didn’t embrace the concept. At a distance the complex looked like an exciting piece of Cubist sculpture, at close up it’s flat concrete-gray exterior looked boring and as if nobody lived there. Inside the complex Safdie’s plastic covered pedestrian streets, connecting the apartments with the elevators and parking lots, were poorly sheltered from Montreal’s cold window weather. Perhaps if it had been built near one of Montreal’s exciting neighborhoods, the public might have been more willing to accept it, but then few of Expo’s fifty million visitors would have seen the innovative housing site. 21


The word metabolism describes the process of maintaining living cells. Young Japanese

architects after World War II used this word to describe their beliefs about how buildings and cities should be designed.

The postwar reconstruction of Japan's cities spawned new ideas about the future of

urban design and public spaces. Metabolist architects and designers believed that cities and buildings are not static entities, but are are ever-changing—organic with a "metabolism." Postwar structures of the future are thought to have a limited lifespan and should be designed and built to be replaced. Metabolically designed architecture is built around a spine-like infrastructure with prefabricated, replaceable cell-like parts easily attached. These 1960s avantgarde ideas became known as Metabolism.

The ideas evolved into urban utopias that envisioned mega-cities through the generation

of giant geometric shapes. In the exhibition, 3D reconstructions show images of what these huge futuristic structures would have been, but in my personal opinion, they lack human scale and people were considered little more than ants in a huge mechanical assembly. However, these ideas led to the creation of some Metabolist buildings, particularly certain works by Tange, Kikutake, Kurokawa, Maki, Otani and others. Without a doubt the most important icon of this movement was the Nakagin Tower by Kisho Kurokawa, the first interchangeable capsule building in the world. Composed of 140 concrete pods plugged into two interconnected circulation cores, the structure was meant as a kind of bachelor hotel for businessmen working in the swanky Ginza neighborhood of Tokyo. Each of the concrete capsules was assembled in a factory, including details like carpeting and bathroom fixtures. They were then shipped to the site and bolted, one by one, onto the concrete and steel cores that housed the building’s 23

elevators, stairs and mechanical systems. In thory, more capsules could be plugged in or removed whenever needed. The idea was to create a completely flexible system, one that could be adapted to the needs of a fast-paced, constantly changing society. The building became a symbol of Japan’s technological ambitions, as well as of the increasingly nomadic existence of the whitecollar worker.

Of course, the great irony of building

and construction standardization is that it hasn’t produced a revolution in architecture. Kurokawa was right that modularity and flexibility would suit “the needs of a fast-paced, constantly changing society;” but when married to the reality of real estate development, and the unreality of the mortgage market in the 2000s, the result was kind of architecture very different from what the Metabolists imagined-- a useful reminder for futurists that what we think of as “exogenous” factors often have a bigger impact on the futures we’re trying to understand than the factors we do pay attention to.



Cellular biological materials have intricate

interior structures, self-organised in hierarchies to produce modularity, redundancy and differentiation. The foam geometries of cellular materials offer open and ductile structural systems that are strong and permeable, making them an attractive paradigm for developments in material science and for new structural systems in architecture and engineering. Bone tissue, forming the skeleton, is a remarkable material. Bone can be either cortical (compact solid) or cancellous, with cortical usually forming the exterior of the bone and cancellous tissue forming the interior. The cellular structure is highly differentiated, formed by an irregular network of trabecular, or rod-shaped fibrous tissue.

Already in 1892 Wolff found that the

orientation of trabecular coincides with the direction of the stress trajectories. It is known that bone mass and trabecular orientation are adapted to the external forces and that alter27

native loading conditions lead to adaptations of the internal tissue architectur. This principle of functional adaptation is generally known as ‘Wolff’s Law’ (Wolff, 1892). The ability of bone to adapt to mechanical loads is brought about by continuous bone resorption and bone formation. If these processes occur at different locations, the bone morphology is altered. The research of the remodelling of trabecular bone is in the main area of many medical research centres. There are many models of bone remodelling based on the strain energy density and used for the adaptation simulations of the bone, treated as a continuum material. The first models were empirical. Scientist completely abstracted from the underlying cellular processes, but related density changes in bone directly to local strain magnitudes. These models were capable of predicting density distributions in the bone as an effect of mechanical loads.

The computational theories became

more refined thereafter, i.e. they became more

mechano-biologically oriented. The mechanical stimulation is one of the most important factors of the normal bone functionality. It assumes that osteocytes are mechanosensitive cells capable of controlling resorption and formation at the trabecular surface. Applying computer





trabecular-like structures are formed aligned to the mechanical loading direction, based on this regulation scheme. Hence, the theory provides a qualitative explanation for modeling and remodeling of trabecular bone as controlled by mechanical forces. The main idea behind that is to prepare the model of the bone adaptation as a material of specific, changing properties depending on the loading history. After many experiments it is clear, that the amount and organisation of the beams in trabecular bone tend to mechanical optimum.



The finite element method (FEM), sometimes referred to as finite element analysis

(FEA), is a computational technique used to obtain approximate solutions of boundary value problems in engineering. Simply stated, a boundary value problem is a mathematical problem in which one or more dependent variables must satisfy a differential equation everywhere within a known domain of independent variables and satisfy specific conditions on the boundary of the domain.

Finite element analysis has become commonplace in recent years, and is now the basis

of a multibillion dollar per year industry. Numerical solutions to even very complicated stress problems can now be obtained routinely using FEA. In spite of the great power of FEA, the disadvantages of computer solutions must be kept in mind when using this and similar methods: they do not necessarily reveal how the stresses are influenced by important problem variables such as materials properties and geometrical features, and errors in input data can produce wildly incorrect results that may be overlooked by the analyst. Perhaps the most important function of theoretical modelling is that of sharpening the designer’s intuition. In practice, a finite element analysis usually consists of three principal steps:

FEM - calculation of cantiliver -

EM - calculation of cantiliver -


Example of FEM calculation o bridge structure on different sets of load pattern

1. Preprocessing: The user constructs a model of the part to be analysed in

which the geometry is divided into a number of discrete subregions, or “elements,” connected at discrete points called “nodes.” Certain of these nodes will have fixed displacements, and others will have prescribed loads.

2. Analysis:

The dataset prepared by the preprocessor is used as input to the

finite element code itself, which constructs and solves a system of linear or non-linear algebraic equations. One of FEA’s principal advantages is that many problem types can be addressed with the same code, merely by specifying the appropriate element types from the library.

3. Postprocessing: In the earlier days of finite element analysis, the user would

pore through reams of numbers generated by the code, listing displacements and stresses at discrete positions within the model. It is easy to miss important trends and hot spots this way, and modern codes use graphical displays to assist in visualizing the results. A typical postprocessor display overlays coloured contours representing stress levels on the model, showing a full-field picture similar to that of photoelastic or moire experimental results.



Another great analytic tool is Topology

Optimizer. The efficient use of materials is important in many different settings. Topology optimisation is a mathematical approach that optimises material layout within a given design space, for a given set of loads and boundary conditions such that the resulting layout meets a prescribed set of performance targets. It has been implemented through the use of finite element methods for the analysis, and Example






optimisation techniques based on the method of moving asymptotes, genetic algorithms, optimality criteria method, level sets and topological derivatives. The optimization of the geometry and topology of structural lay-out has great impact on the performance of structures, and the last decade has seen a great amount of work in this important area of structural optimization. This has mainly been spurred by the success of the material distribution method for generating optimal topologies of structural








elements. This defines shape in terms of a material density and geometry is described by what amounts to a raster representation as seen in computer graphics. Today one naturally distinguishes between the search for “classical� designs made from a given material, and methods that allow for a broader range of material usage.

The optimization process starts with

the subdivision of the overall volume based on FEM (Finite Elements Method) logic. In its most general setting shape optimization of continuum structures should consist of a determination for every point in space if there is material in that point or not. Alternatively, for a FEM discretization every element is a potential void or structural member. In this setting the topology of the structure is not fixed a priori, arid the general formulation should allow for the prediction of the layout of a structure. This defines shape in terms of a material density and

geometry is described by what amounts to a raster representation.

For continuum structures one can apply

an interpolation scheme that works with a density of isotropic materials together with methods that steer the optimized designs to “classical� black and white designs or one can use a relaxation of the problem that introduces anisotropic composites such as layered periodic media, also leading to a description of shape by a density of material. In both cases the density can take on all values between zero and one, and one can also make physical sense of intermediate density values.

The direct method of topology design

using the material distribution method is based on the numerical calculation of the globally optimal distribution of the density of material p which is the design variable. For an interpolation scheme that properly penalizes intermediate densities the resulting 0-1 (or black and white) 37

design is actually the primary target of our scheme. The optimality criteria method for finding the optimal topology of a structure constructed from a single isotropic material then consists of the 3 steps. First task is pre-processing of geometry and loading process based on choosing a suitable reference domain which should contain solid or voids domains. Next TO model need to construct finite element spaces for the independent fields of displacements and the design variables. After all we can move to next step which is Optimization. Algorithm compute the optimal distribution over the reference domain of the design variable p. The optimization uses a displacement based finite element analysis and the optimality update criteria scheme for the density. In Post-processing essential is Interpret the optimal distribution of material as defining a shape, for example in the sense of a CAD representation like a three dimensional mesh or in terms of 2d rasterized images of material distribution, VonMieses Stress or Stiffness.

The method allows for an efficient prediction of the optimal topology, the optimal shape

and the optimal use of the prescribed possible support conditions. Also, it has proven to be a flexible and reliable design tool.

The topology design problem has been cast as a problem of finding the optimal density

distribution of material in a fixed domain, modelled with a fixed FEM mesh. This is of major importance for the implementation of topology optimization methods.



"Nature's simplest structural system in the universe is the tetrahedron. The regular tetrahedron does not fill all-space by itself. The octahedron and tetrahedron complement one another to fill all space. Together they produce the simplest, most powerful structural system in the universe� Buckmeister Fuller



To allow constant changing of building, in therms of it evolution, is required materials, or

components to alter the kinetically, at the same time without losing their mechanical properties. Therefore, any typical architectural elements like slab, beam or column cannot be prefabricated, or made in traditional way on the site. What is needed is a solution in which materials could be removed from one part of the building and moved to another. It seems reasonable to create a system consisting of unified units, like bricks, based on a common grid.

Bricks are one of the oldest known building materials dating back to 7000BC where they

were first found in southern Turkey and around Jericho. The first bricks were sun dried mud bricks. Bricks are more commonly used in the construction of buildings than any other material except wood. Brick and terracotta architecture is dominant within its field and a great industry has developed and invested in the manufacture of many different types of bricks of all shapes and colours. With modern machinery, earth moving equipment, powerful electric motors and modern tunnel kilns, making bricks has become much more productive and efficient.

Based on the concept of modularity, which gives bricks, this idea allow to the full freedom



of creation space, with abilities to relocate material. But another problem is how to connect this bricks. In the conventional construction, the adhesive can only work on the compressive forces. By eliminating it, which mostly is the glue or cement mortar and replace it with a combination of mechanical lock, gets new mechanical properties. That unit would be able to transfer tensile strength, compressive, torsional moments or shear, and also allow to disjoin some part of bricks and relocate them in another part of construction site.

Other questions is how that three dimensional base grid should looks like. In one side,

it should be regular and simple, that’s mean, each component have to fit everywhere. On the other side, it have to be mechanically effective. First thoughts is of course cube. Is simple regular, but is not effective in terms of force distributing because, connection between cube work only

Grid based on cube corners nad center of weight

on three main axis creating based on quads lattice. Another possibility is sphere packing, which deal with arrangement of non-overlapping spheres within a containing space. There is lots of solution, and algorithms how to pack it to get the most denser space. But this solutions assume different spheres sizes, which in this case are not possible. Rejecting this possibility, there is only 45

Sphere package diagram

one algorithm deployment areas, so that each of them interacted with their neighbours. If you look at the three-dimensional model of this packing spheres, we find they come in contact with diagonally. In this case, we obtain four axis, however, contact of spheres is the point, which is not a good mechanical solution.

Unit geometrie with 3 main axis and additional 4 diagonal.


Combination of these two leads




Building Unit geometrie based on Fullers primitives

octahedron, space filling cells of equal volume with the least area of surface between them design by Lord Kelvin in 1887. He proposed a foam, based on the bi-truncated cubic honeycomb, which is called the Kelvin structure. This is the convex uniform honeycomb formed by the truncated octahedron, which is a 14-sided space-filling polyhedron (a

3 tetrahedrons.

tetradecahedron), with 6 square faces and 8 hexagonal faces. Using this solid gives the 3 axis solution of the cube, in conjunction with the 4 diagonal axis from the packing of spheres solution. Truncated octahedron can work in 7 axis force distribution, which is most affective and the simplest way to create structure, with very good mechanical abilities.

3 tetrahedrons + 3 half octahedrons


One from eight hexagonal site od truncated octahedron.

All hexagonal site of truncated octahedron.

Cluster of 4 hexagonal site od truncated octahedron.

Filling empty square sids by half of octahedron

One uniform brick shape can help also to use it for different purposes. It can be plethora

of variety of function types. On type is BasicUnit, which is main construction brick with high mechanical properties with stress sensors and communication component. Another kind of function can be distribution of services by ServiceUnit like a water supply, energy , data streaming or plumbing. Bricks can also play the role of lighting in the building. Agglomeration of LightUnit connected to service on can solve problem of lighting building with one uniform way easy to maintain. There is plethora of possibilities. Personal computers, hologram displays, HI-FI equipment and so on, Everything can by design like a truncated octahedron and by using unify standard of sockets on ServiceUnit, easy plugged everywhere creating one system of media interface for residents. Big advantage of this solution is, that you are not strict by past decision about distribution of services in your flat.By this system all possibilities are avalable, all the time. 49


To achieve a continuously evolving structure the system requires the introduction of

movable units, able to sense their own location and the forces acting upon them. By embedded simple and cheap processor unit in all bricks, system can respond for environment changing, caused either by users of building or environment changes. Each Brick Computing Unit (BCU) can gather data about neighbours, its own technical condition and if available, stress acting on it. These data are sent in real time to a Main Computing Unit (MCU), which recreates the whole structure model to analyse changes and respond to them.

There is also another option available. Instead of gathering all data recreating model and

calculate it in one main computer is possible to create cluster of computing processor. Following the principles of FEM we can force each BCU to compute them self. In this solution one Unit is self computing FEM node, which is sending ready structural data about itself to MCU, which

Scenario I: MCU - Main structure analyzing computing unit

Scenario II: Clasters of BCU like a self computing FEM node


in this case is only analysing incoming data , and making decisions how structure should behave. In both cases additional role of MCU is maintaining data flow between BCUs and storing data for future purpose. Despite of which option will be applied, thanks to the real-time connection between bricks and main computing unit, engineers are able to analysis condition of building, and preserve it from unexpected damages. Furthermore, in main computer can be created a history of changes, so always its possible back to better building configurations, as well after typhoons or earthquakes, this records can help to discover structural discontinuity and fixes problem on time.

Rising up this kind of complex structure can be challenging without proper construction

technology and suite toolbox. Looking on today available solution, there are two ways to erect

this type of structure. One is usage of 6 axis industrial robots, which will be guided by MCU. we next block should be placed. Second option is manually rising it by humans. During the construction process, thanks to data exchange technology between BCU and MCU, workers can be equipped by some devices like a Tablets, or to somethink more handy like a Google Glass. By Virtual Reality technology, by merging view from camera and virtual model of ready building workers can be guided where next unit should be placed. But not only workers. All residents can be equipped on this kind of device, to maintaining their dwellings. So they can by themselves change their space. This cooperation between computer and people can help to evolve structure in real time with preservation of structure from irrational behaviour which can cause damages.






CASE STUDY 1 In order to examine the effectiveness of a topology optimization algorithm has been carried out a few simple tests. The simplest was to examine the uncomplicated scenario in which the relationship between load and support, give easily interpretable results. In each of them, the structure had to transfer load equal 10kN/m2. Depending on the scenario, the support structure to investigate the optimization results, changed. These tests showed of efficiency in the algorithm, as well as its high efficiency in solving the simplest structure contained in the script.

1 Support // 1 Slab

4 Supports // 1 Slab



VonMiese Stress

VonMiese Stress

2 Supports // 1 Slab // Linear

2 Supports // 1 Slab // Diagonaly

1 Support // 1 Slab // NonCentral




VonMiese Stress

VonMiese Stress

VonMiese Stress 59

CASE STUDY II The test model contains two types of objects. The first of these objects are static, that is, those which do not change during the evolution of the building. These include footings and an external domain in which the material is distributed. The second type of objects in the model are slabs and housing space. Those change over time in the evolution of the building. This puts certain requirements for the script. It must follow the changes in load, as well as space in which construction can not occur. The theoretical model consists of ten steps changes being presented. For each of them created is optimized spatial model of the structure, including information about the internal stresses and their directions. Based on these data, the resulting simulation showing the process of change and growth of such a building. This test showed possibilities and usefulness of topology optimization in the construction of buildings. Analyzing each step of the simulation, you can find a lot of interesting moments when the structural system, the most efficient in terms of predetermined varies in order to adapt to the new requirements set by the designer.

Support pattern

Slab pattern

structure material 立 = 0,0 - 1,0

material void 立 = 0,0 2,0 kN m2

material void 立 = 0,0 2,0 kN m2 floor slab

support blocks

Load pattern

Volume constrains

General diagram of T.O.


Stage 0

Stage 1

Stage 4

Stage 5

Stage 2

Stage 3

Stage 6

Stage 7



Stress Lines in all principle axis of stress vector

Stress Lines in principle Z axis of stress vector

Stress Lines in principle Y axis of stress vector

Stress Lines in principle X axis of stress vector

Thanks to the Topology Optimization algorithm, designer can reach many priceless data about structure, which is developing. Stiffness factor and stress vectors can tell us what is happening inside our structure. Base on this knowledge we can extract, and visualized this data using isocurves or isosurfaces to interpolate data over stress and dens field. That generated curves, in case we are working on casted structures, can be very useful for engineers, to design reinforcement for it. For each FEM node in T.O. algorithm, we are returning stress plane with plenty of data. Main X axis is determining normal stress in structure, Y and Z axis trace shear forces perpendicular to normal stress force in both directions. Base on that information engineers can easily predict future cracks of structure, reinforcement distribution, and it size and density.





During developing idea about constantly changing building, was clear that dwellings and they spaces, will affect structure the most. To simplify whole design and building process, was developed simple Flat Creator. Purpose of this application was to allow all residents to customize they own living space by simply clicking and occupying more cells for they flat. This solution can make easier whole process of designing individual space for each family. Each user, can create they own design, see how other occupants dwellings look like, and redesign his flat to adjust it to new requirements. All changes inside application influence real building. When main architect of residence building approve changes, they immediately start being applied.

Workflow inside application is really simple and intuitive. After running it, application welcoming you by main menu. Here you have to decide , do you want to create new design, or do you want to change or delete already existing one. If you chose new design, it will prompt you to input name for your project. After clicking “submit”, or choosing “Open” in previous menu, FlatCreator will show you all already existing designs, according to site. In this window you can click on any already existing project, to load it for detail edition, change general boundaries for your design, or choose new domain for new flat. Whatever which option you will take, next step is detail edition of you dwelling. In this window all other design are gone to not disturb you 73

during creation process. Also on left site of window will appear new set of tools allow you to sculpt your own space. You can “Paint” your spaces or selecting it just by clicking one by one. If you want to create big spaces and you are not patient , also you will find some MassSelection tools, which allows you to select bigger group of point contained inside box or sphere. When you finish your design, last think is to save you work, and that’s all.

After saving, all data about

dwelling design will be taken into T.O. script for structure optimization.

Click by Click selection

Click by Click selection

Box selection tools

Sphere selection tools

Paint selection tools

MassSelection selection tools 75







“Istanbul (Turkish: İstanbul) is the largest city in Turkey, constituting the country’s economic, cultural, and historical heart. With a population of 13.9 million, the city forms one of the largest urban agglomerations in Europe and is the second-largest city in the world by population within city limits” This short description provided by Wikipedia, shows how important is that city for Turkish citizens. Sadly this one of the oldest city in the Europe, has lot of problems with old abandoned building in old part of city. Most of them are very valuable but in very bad condition. For my case studies on architectural proposal, I’ve chose small site near Galata tower. This slight peace of Istanbul land is located in the Sishane district, on the European site of city. The plot is the remnant of a recently demolished building. The choice fell on a small plot of land in the historic city centre, with good reason. This place need to be resorted, and my easy adaptable structure system can be applied on different situations. This can accelerate, and help to bring back higher quality of spaces created.



Step 1: Dwellings Step 2: Topology Optimization Step 3: Stress Tracing Step 4: Populating Structure by Units


Step 1: Dwellings For architectural propose, was made few types of dwellings. Design process was driven by different requaierments. Thanks to pure freedom of creation, flats layouts are limited only be residense imagination and site boundaries. For this particula r project was created double floor dwelling with 2 badrooms, huge dwellings with 4 beadrooms, or small flat wit one badroom. All changes inside application influence real building. When main architect of residence building approve changes, they immediately start being applied.


Step 2: Topology Optimization

Input data scheme for T.O.

Creation of structure is based on four main sets of domains, which are describing specific space types. Main domain is general material boundary for script. Inside this domain material density can change from 0.0 to 1.0. Also for each node of this domain is calculated stress plain, deflection factor, density and stiffness. Very important is to define, if is necessary, additional domains which describe certain behaviour of material such a fixed density on nodes, or void parts of volume, in which structure cannot be defined. Next sets of parameters are load and support conditions. Like rest of parameters tis group also need to be defined by volumes. For support it is not problematic, but for load, are needed extra calculation to input proper value of load condition. Most of static analysis use areas load kN/m2, so it has to be converted in to kN/m3. Operational Load for housings is 2kN/ m2, adding structural load from slab, with additional safe factor, equal to 5000 N/m2, we are getting sum of 7kN/m2. Slab thickness is approximate constant and equal to 0.20 m, so dividing Areal load by slab thickness, we are getting 35 kN/m3, and this value was inputted for T.O. calculation

Load and support condition - view from street 89


SUPPORT Load and support condition - view from cotyard

Loading and support diagram referenced to FEM nodes

Stress vector field 91

Step 3: Stress Tracing Output form Topology Optimization algorithm contains huge set of data, and it need to be filter and translate to geometrical approach. Like most of optimization algorithm also Topology algorithm is using iteration logic for whole process. If more step will occurred, them more accurate output model and data are. Aldo resolution of FEM grid, on which is divided whole material domain also have big impact on the output. Of course more iteration on bigger resolution can give more precise result, but we all are limited by computational power and capacity of data storage. Another problem on huge resolution T.O model, can be post processing output data. One solution of this problem can be creation lower resolution model and interpolating data

Basement - Units location points diagram

between already existing values. This logic was principle for me during creation script which could trace for me stress path. Base on stress vector field, on each iteration of algorithm tracer is gathering data about closes vectors and they magnitude. Base on that data it is calculating interpolated direction of tracing, and base on magnitude of vector, it strength. During tracing process, script is also deciding about location of future Units based on maximal VonMies Stress on that location. This feature allow to correct distribution of building material, depend on real needs of supporting certain part of structure. Similar logic we can observe in real world - just look on tree.

Basement - Stress Lines diagram 93

Flats - Units location points diagram

Flats - Stress Lines diagram


Step 4: Populate structure by Units

Outcome Structure

Outcome Structure 97













Staircase Elevator


LEVEL 0.2 SCALE 1 :100

Staircase Elevator


LEVEL 0.3 SCALE 1 :100

Staircase Elevator

Public Space SHop / Restaurant


Public Space

LEVEL 1.0 SCALE 1 :100

Staircase Elevator




Living room

LEVEL 1.1 SCALE 1 :100

Staircase Elevator

Bedroom Bathroom



Living room Kitchen


LEVEL 1.2 SCALE 1 :100

Staircase Elevator



Bathroom Bathroom

Living room

Living room

Kitchen Kitchen

LEVEL 1.3 SCALE 1 :100

Staircase Elevator




Living room Bedroom Bedroom Kitchen

LEVEL 1.4 SCALE 1 :100

Staircase Elevator






Living room Kitchen

Living room

LEVEL 1.5 SCALE 1 :100

Staircase Elevator

Bedroom Bedroom




LEVEL 1.5+ SCALE 1 :100


SECTION 1-1 SCALE 1 :100

SECTION 2-2 SCALE 1 :100

SECTION 3-3 SCALE 1 :100

SECTION 4-4 SCALE 1 :100





BIBLOGRAPHY 1) M. P. Bendsoe, O. Sigmund – “Topology Optimization Theory, Methods and Applications” ISBN 3-540-42992; Springer-Verlag Berlin Heidelberg New York; 2) Ryszard Kutyłowski “Topology Optimization of Martial Continuum” ISBN 83-7085-788-4 ;Technical University of Wroclaw 2004 3) David Roylance – “Finite Element Analysis” - Department of Materials Science and Engi neering Massachusetts Institute of Technology; Cambridge 4) David V. Hutton - “Fundamentals of Finite Element Analysis” - ISBN 0-07-239536-2; McGraw-Hill 2004; 5) Tomasz Łodygowski, Witold Kąkol – “Finite Element Method in some problems of construction engineering mechanics” ; Technical university in Poznan 2003; 6) Philip Ball – “The Self-Made Tapestry” ISBN 0 19 850244 3 (Hbk) ; Oxford University Press; 7) Architectural Design – “Techniques and Technologies in Morphogenetic Design” ISBN13 9780470015292; Wiley-Academy 2006 8) Michał Nowak, Marek Morzyski - “Simulation of trabecular bone adaptation – creating the optimal biological structure” - Poznań University of Technology, Division of Machine Design Methods; 9) John Frazer - “Evolutionary Architecture” ; Architectural Association 1995; 10) Heino Engel - “Tragsystem - Structure Systems” ISBN 978-3-7757-1876-9; Hatje Cantz Vertrag; Germany 2009 11) Casey Reas Ben Fry - “Processing: a programming handbook for visual designers and artists” ISBN 978-0-262-18262-1 ; The MIT Press Cambridge, Massachusetts London, England 2007 12) Daniel Shiffman - “The Nature of Code” 2012