portfolio_20110615

[ G E N E ] R A T I V E [ F O R M ] U L A T I O N SADNAN IHSAN / B.ARCH / MSAAD [COLUMBIA UNIVERSITY]

WHAT IS IT ALL ABOUT ?|i|

In the past twenty five years, the digital revolution has accelerated cultural change at a rate and to an extent unparalleled since the Industrial Revolution. Digital technologies have the potential to profoundly transform architecture practices and techniques. Since the early 1990s, pioneering architects such as Frank Gehry and Greg Lynn have been investigating the repercussions of implementing computing technologies on the design and production of architecture.

The most radical experiments in design and computing, however, have remained largely sequestered in academic institutions and a few boutique offices. Softwares are employed by many conventional practices as tools for representing a design after it has been conceived. Another common practice is to use applications such as CATIA and Rhinoceros to preform analytical operations. The incorporation of computer softwares as tools of representation and analysis has led to important advances for the discipline. Yet architecture can and must go further. In my projects, I investigate digital technologies as platforms from which architects can develop new techniques, giving rise to innovative works of architecture with significant cultural effects.

Architects must become more responsive to their users and environments. They must incorporate feedback from their physical and cultural contexts rather than relying solely on conventional analytical or internal processes of development. Feedback provides a means to evaluate architecture’s effects and to promote further transformation. Thus, scripting has the capacity to create feedback-loops with in the design arena to continuously inform architecture to transform and mutate.

The collection of digital projects is heavily relied on the process to achieve architecture, rather than the outcome. Though these are all digital projects, they all have their own trajectories or agendas to approach architecture. They fall in categories of computational variation, optimization, and agents and agencies. [Gene]rative [Form]ulations is an architect’s struggle to reboot the approach towards architecture. It plans to create friction by disrupting conventional operating territories in the realm of culture, context and structure that informs architectural philosophy. This is not a handbook or a manual; it’s a monologue of a designer’s intent to inject architectural thinking with technological developments for producing forms of architecture that generate feedback from their users and within culture at large.

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2008// 2011

OPTIMIZATION

AGENTS AND AGENCY

VARIATION

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PROJECTS

___ONCE_UPON_A_HOUSE________03____

___SUPER_MODEL_CITY__________17____

___PROOF_6_________________27____

___SAWRM_INTELLIGENCE________37____

___ADAPTIVE_FORMULATIONS______43____

___SEARCH__________________47____

___CITY_OF_LOVE_&_HATE________53____

___VIRTUAL_/_ACTUAL___________60____

___XY_PROTOTYPE______________76____

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The project used the program of a house as a tool to study the shift towards a paradigm of Species as opposed to the ubiquitous platform of Types. If Types are traditionally viewed as categories of standardization, and symbolic expressions of form, then Species are malleable entities that are in constant metamorphosis; adaptation and mutation are the main characteristics from Species. A Species needs a lineage to be acknowledged as such, indeed a Type also needs a lineage to become such. But a Species has more freedom, because it can mutate. A Type can change, but it cannot mutate, it can be combined, or renewed, but it will always be a type. The project proposed, to conduct an

extensive research in the cellular logic and construction of structural instability. To radicalize the agenda of the autonomy of form, using the possibilities of kinetic and movement. Mirco-techniques for combining the thresholds of the horrific-becoming-beautiful and the beautiful-becoming-horrific (grotesque) have imprinted themselves as visual-temporal cues on the current design retina. The importance of the multiplicity has finally opened the door for mutation as a permanent state of the present.

The Genealogy of the autonomy of the forms, has been indivisible form the genealogy of the single house.This studio used latest technology for

design, as this technology indulges mutation as a new paradigm of architectural design. Form is never less and more is even more.

The house was designed to play out three stages of transformation, at each stage the design of the house drastically changed, for example the couple that lives in it will get divorced in Act 2 and there is then an catastrophic earthquake; it changes the center argument for the thesis of this studio, as design is not acting as a static entity, nor process is developed in a linear manner, from more diagrammatic to more detail, indeed form is always detailed, and never diagrammatic.

TOOLS // MAYA / ILLUSTRATOR / AFTEREFFECTS

CRITIC // HERNAN DIAZ ALONSO / XEFIROTECH

ONCE UPON AHOUSE

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STRUCTURAL CELL / CLADDING CELL / CELLULAR MEMBRANE The Structural cell is the basic building unit for holding the spaces together. They multiply by rotational connec-tion system creating a monoque space frame.

Cladding cells aggregate by sprialling and scaling along a linear plane. The cells variate to adjust to previous cells surface typology to create a cohesive membrane like

quality. This cell fills in the voids of structural cell system, creating porosity for ventilation and light

This is a tertiary cell which helps to complete enclosure. It comes to play when enclosure is needed between the cladding and structural members. This cell is elastic and has the capactiy to create volumetric conditions

DEPLOYMENT OF STRUCTURAL CELLS FOR ENCLOSED PROGRAMTIC ELEMENTS

SITE AT AN INCLINE

DEPLOYMENT OF STRUCTURAL CELLS FOR INTERMEDIARY PASSAGES

PROGRAM SPARSELY DISTRIBUTED TO CREATE INDOOR/OUTDOOR RELATIONSHIP

CLADDING AND MEMBRANE CELLS ADAPT TO STRUCTURE TO FORM ENCLOSURE

SEPARATION OF PUBLIC AND PRIVATE SPACES

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STRUCTURAL CELL / CLADDING CELL / CELLULAR MEMBRANESITE / PROGRAM PARTIThe design intent was to create an indoor/outdoor experience., since the climatic conditions of LOS ANGELES are amiable and invite outdoor activity.To acheive that the program was distributed in a scattered manner , which became the enclosed indoor experience. These programs are linked with external circulation. Together

they make a complete indoor/outdoor experience through out the house. Furthermore, the public spaces such as kitchen and living are deployed on the ground creating convenience for access into these public spaces where as the bedrooms were sectional separated by elevating them of the

ground. Vertical circulation discourages frequent access since climbing against gravity is inconveneint.The site is at an incline where the two ends have an 8M difference in elevation. The landscape adapts to the structure creating a dialogue and forming a cohesive language with the rest of architecture.

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ACT1 / JUST MARRIED

ACT2 / DIVORCE

ACT3 / EARTHQUAKE

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The house was designed to play out three stages of transformation, at each stage the design of the house drastically changed, for example the couple that lives in it will get divorced in Act 2 and there is then a catastrophic earthquake; it changes the center argument for the thesis of this studio, as design is not acting as a static entity.

// DESIGN MAP / TIME LINE

[2011] [2012] [2013] [2014]

[2011] [2012] [2013] [2014]

TRANSFORMATION_2

TRANSFORMATION_3

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PARASITIC REINFORCEMENT BY GROWING TENTACLES TO ITS NEIGHBORS

VERTICAL SEPARATION WITHIN THE EXISTING ARCHITECTURE

[2015] [2016] [2017] [2018] [2019]

[2015] [2016] [2017] [2018] [2019]

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ROOF PLAN

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AXONOMETRIC VIEW

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// PLAN -06.00M

// LIVING SPACE // KITCHEN / DINING // BEDROOM/STUDY/ KITCHENETTE // ROOF

// PLAN 00.00M // PLAN +08.00M // PLAN +12.00M

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[10] [11] [12] [13] [14] [15] [16] [17] [18] [19]

[10] [11] [12] [13] [14] [15] [16] [17] [18] [19]

//SECTION Cleary shows the separation of the house into two identifiable entities. Where one adapts a horizontal language and the other contrasts it by verticality and alertness

// TOP LEFT / VIEW FROM HIGHWAY END// BOTTOM RIGHT / OUTDOOR CIRCULATION// RIGHT / BEDROOM INTERIOR

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SECTOR 03’15INTENSITY 0.349




SECTOR 28’23INTENSITY 0.649SECTOR 03’65

INTENSITY 0.849





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SUPERMODEL CITY is both highly ambitious and super-straightforward. Simply put, this project enthusiastically embarked into the unknown, relying upon fanatical, systematic and rigorously imaginative exploration as the driving mechanisms for this eleven-week ride. Through an intricate series of inter-project collaborative modes and iterative tactical operations, SUPERMODEL CITY developed into sets of multifaceted, chimerically refined and deeply spatial constructs. Like any city, it manifests as a series of negotiations played out through time as a multitude of interwoven spatial

conditions and opportunities. As such, SUPERMODEL CITY occupies its own operational territory; in this sense it is freely disengaged from any other city. On the other hand, as the intent is to generate an extensively diverse catalog of elegantly refined spatial episodes that both reflect and spark imaginary urban futures, it is potentially interwoven with every (possible) city.

Even while in flux, SUPERMODEL CITY served as its own site, the constraints and parameters of which are generated by the introduction of issues and ideas set

forth by individual project participants, cultivated through productive internal collaboration. Its extents, scalar reach and strategic implications are limited only to individual and collective initiatives developed within the studio. Oscillating between specificity and ambiguity, SUPERMODEL CITY is intrinsically sci-fi, successfully fabricated only if it generates more questions than answers through its various proposed conditions. In other words, this project’s efforts were both focused and wide-open.

TOOLS // RHINO / GRASSHOPPER / 3DMAX

CRITIC // KEITH KASEMAN / KBAS

SUPER MODEL CITY

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Kleptocracy, alternatively cleptocracy or kleptarchy, from Ancient Greek: κλέπτης

(thief) and κράτος (rule), is a term applied to a government subject to control fraud that

takes advantage of governmental corruption to extend the personal wealth and political

power of government officials and the ruling class (collectively, kleptocrats), via the embezzlement of state funds at the expense of the wider population, sometimes without

even the pretense of honest service. The term means “rule by thieves”. Not an official form

of government such as a democracy, republic, monarchy, or theocracy; a kleptocracy is

rather a pejorative for a government perceived to have a particularly severe and systemic

problem with the selfish misappropriation of public funds by those in power.

The effects of a kleptocratic regime or government on a nation are typically adverse

in regards to the faring of the state’s economy, political affairs and civil rights. Kleptocracy

in government often vitiates prospects of foreign investment and drastically weakens

the domestic market and cross-border trade. As the kleptocracy normally embezzles money

from its citizens by misusing funds derived from tax payments, or money laundering

schemes, a kleptocratically structured political system tends to degrade nearly everyone’s

quality of life.In addition, the money that kleptocrats steal

is benefits a few by creating extravagant lifestyle for few behind closed doors, while its

victims are struggle for basic s.

SUPERMODEL city abridges these gaps by weaving these disparities in social groups

by increasing transparency and creating moments of intersections.

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EVOLUTIONARY VARIATIONSThese complex surfaces are product of variations in the behavioral constructs over time.

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LEFT / Diagrams measuring the deviation of the normal angle from gravitational angle, a representatiun of disparity between gross domestic income per capital and earned incomes within regions at microscopic levels.These evaluations are used to inform porosity on the surfaces to encourage the interaction between extreme social classes.

The experiment was setup to produce a spectrum between two hues, in this case yellow and purple. The graphical output is used as evaluative data. They represent two different end ursers found with in an economy. The conceptual struggle is to weave these social classes together to create a welfare society. Moments when these two intereact, creates porosity with in the membrane to create a more transparent space. This bolsters the idea of creating public spaces such as markets and plazas that generate micro economy with in its macro structures.

RIGHT / View if the market where there are no doors to prevent access or create those social barriers.

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Proof is a studio based on investigating wide new design spaces and on the process of testing. The research involves using computation and digital technologies specifically in service of probing the unknown, and creating architecture through design of experiments rather than design of solutions.

In the field of architecture, we are swimming in our own specific data related to social and political conditions, infrastructure, environment, geometric form, construction schedule and cost, physical sensors, user-generated content, and the growing realm of building simulations. In other words, we may have more data for any complex project than a single person could hope to comprehend.So how might we make sense of all this

data? What strategies and algorithms might we use to draw correlations and determine relationships? Can we avoid getting boxed in by the data, and instead use it as fuel for our creativity? Does massive data alter the architect’s traditional role as a manager of complex forces and competing demands—or is it simply another type of input into the usual process of design?

This is the primordial soup of Proof, a studio based on investigating wide new design spaces and on the process of testing. In our research, we will use computation and digital technologies specifically in service of exploring our deluge of data and probing the unknown. We will generate innovative and high-performing results by using a new design methodology: creating architecture

through design of experiments rather than design of solutions.In our experiments, we will learn and apply parametric modeling tools (CATIA) and advanced computer science methods (evolutionary algorithms). We will be among the first architects in the world to use new multi-objective optimization software (modeFrontier). We will test with digital simulations (FEA, CFD, crowd behavior, and Ecotect) and we will test with physical prototypes (digital fabrication and wind tunnel experiments).

we will have an informed, critical, and open-ended discussion about data, computation, and the future of architecture.

TOOLS // CATIA / EKL SCRIPT / MODEFRONTIER / CATBOT [ROBOT]

CRITIC // DAVID BENJAMIN / LIVING ARCHITECTURE

PROOF 6OPEN SOURCE EXPERIMENTS WITHCOMPUTATION, CULTURE AND DESIGN SPACE

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SOCIAL MIXERS // RETAIL, FOOD COURT, KIDS PLAY AREA

ENVELOPE HOTELVERTICAL CIRCULATION RESIDENTIAL AND CONDOSOBSERVATION DECK MECHANICAL FLOORS

This tower is designed through a performative patterned envelope. The

envelope not only addresses enclosure, aesthetics, structure and program- it also creates a micro-economy within itself, an

economy engaged in by varied income groups. The envelope weaves different social classes by exploiting the creation of voids to

counter the lifelessness of a typical vertical living and embracing the richness of street

markets.

FUNCTION MIXER

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COMMERCIAL OFFICE

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MULTI - OBJECTIVE OPTIMIZATION

MANUAL DESIGN BY A HUMAN

STRUCTURESince gravity forces the weight to flow downwards, it would be right to assume that the vertical force towards the ground members would be higher, thereby needing more structural members

PROJECTIONSThe condition of a certain panel arranged in a specific way induces a projected 3D spaces ( orange panels) Stacking them on top of each other induces the 3D character. Hence a certain arrangement would produce a the results if the face was designed manually.

ASSYMETRICAL PATTERNINGInorder to create assymetrical facade , the opposing end of the envelope should have different panels

VOIDS ( SOCIAL MIXERS)This arrangement would seem the optimum to have the maximum number of void spaces a greatest displacement thru out the tower

SINGLE OBJECTIVE OPTIMIZATION

GENERATIVE DESIGNS THRU AUTOMATION

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//AUTOMATED - TESTING // HIGH PERFORMING RESULTS

PERFORMS VERY HIGH IN CREATING A LARGE NUMBER OF VOIDS USED FOR AS SOCIAL MIXERS BUT FAILS TO PROVIDE STABLE STRUCTURE. THE RESULT IS VERY SYMETRICAL HENCE THE AESTHETICS ARE NOT HIGHLY RATED.

PERFORMS HIGH IN PRODUCING STABLE STRUCTURES WITH REDUCED X AND Y DISPLACEMENT FORCES. BUT THE SELECTED OUTCOME PRODUCES BORING REGULAR FACADE TREATMENT.S. PERFORMS NOT SO WELL IN CREATING SOCIAL PROGRAM SPACES

PERFORMS VERY HIGH IN CREATING A LARGE NUMBER OF VOIDS USED FOR AS SOCIAL MIXERS, ALONG WITH HIGH STRUCTURE STABILITY AND AESTHETICS OF THE BUILDING ENVELOPE

SERIES OF HIGH PERFORMERS WITH FIXED PARAMETER OF 3 VOIDS

3/2250 DESIGNS

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OPTIMIZATIONS

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Automation was utilized in this tower design more as an exploration tool rather than for exploitation. Automation helped in producing a wide design space to discover alternative proposals for a competing objectives ( results which are unexpected and different from those derived by linear problem solving or manual trial and error). Automation eases the process with wich one could produce multiple design models with just few numerical input changes, and has the ability to simulate and evaluate multiple objectives simultaneously.

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This visual study examined the role of agency within generative design processes. The course engaged algorithmic techniques in the development of a computational methodology grounded in swarm intelligence. While discussing the political and social role of agency, the workshop focused on an abstract design methodology, recasting simple decision making ability into agents capable of self-organizing into an emergent intelligence. Scripting formed the basis for algorithmic models which enabled localized interaction of agents to generate emergent topologies in the design of proto-architectural forms, structures and articulation. Unlike the typical application of swarm systems in design, this workshop did not engage simply in the mapping of these complex systems,

but instead, we mined the self-organizing potential of the systems to negotiate between a complex set of desires and parameters in the generation of architecture.

The semester focused around two areas of research, initially developing simulations of vector based swarm systems and then using these as the basis for developing an architectural design methodology which operates within a topological substrate. This second stage of the research will shift away from any analogous relationship to an existing swarm systems and develop a design process capable of negotiating architectural inputs.

The project intensively engaged in scripting, using and expanding on a library of agent

code which ensured that we were not slowed by the necessity of writing all the required code. Instead the focus was on the application and manipulation of code within the design process. This expansive library has been developed through research at Kokkugia and previous studios and seminars. The library consists of relatively simple functions (such as steering behaviors) which can be recombined in the development of more complex algorithms.

Computational design is shifting away from the reliance on heavy platforms such as Maya’s MEL scripting language into lightweight object oriented programming environments, enabling the massive iteration required for emergent processes.

TOOLS // RHINO / GRASSHOPPER / 3DMAX

TUTOR // ROLAND SNOOKS / KOKKUGIA

VISUAL STUDIES

SWARMINTELLIGENCE

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// CATALOGUE OF EMERGING PATTERNS

// BEHAVIORAL LOGICSThe ant colony optimization algorithm (ACO) is a

probabilistic technique for solving computational problems which can be reduced to finding

good paths through graphs. This algorithm is a member of ant colony algorithms family, in swarm

intelligence methods, and it constitutes some metaheuristic optimizations.

In the natural world, ants (initially) wander randomly, and upon finding food return to their

colony while laying down pheromone trails. If other ants find such a path, they are likely not to keep travelling at random, but to instead follow

the trail, returning and reinforcing it if they eventually find food (see Ant communication).

Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength. The more time it takes for an ant to travel down

the path and back again, the more time the pheromones have to evaporate. A short path, by comparison, gets marched over faster, and thus

the pheromone density remains high as it is laid on the path as fast as it can evaporate. Pheromone

evaporation has also the advantage of avoiding the convergence to a locally optimal solution. If

there were no evaporation at all, the paths chosen by the first ants would tend to be excessively attractive to the following ones. In that case,

the exploration of the solution space would be constrained.

Thus, when one ant finds a good (i.e., short) path from the colony to a food source, other ants

are more likely to follow that path, and positive feedback eventually leads all the ants following a single path. The idea of the ant colony algorithm

is to mimic this behavior with “simulated ants” walking around the graph representing the

problem to solve.

// ANT COLONY OPTIMIZATION (ACO)

AGENTS

TIME FRAME [00] TIME FRAME [15]

ATTRACTORS REPELLERS

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TIME FRAME [30]

PHERMONE INTENSITY 5

TIME FRAME [45] TIME FRAME [60] TIME FRAME [75]

PHERMONE INTENSITY 15 PHERMONE INTENSITY 30

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// CIRCULATION TUBES

// HABITABLE CHAMBERS

// ENTRANCE PLAZA

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Researchers in fields like Biomimetrics and Systems Engineering have discovered relationships embedded within complex systems of seemingly unrelated components or, in the case of natural systems, plant and animal life. These relationships (and dependencies) can be shown to enhance the whole, perhaps improving the resiliency of the system to changing conditions or improving efficiency and reducing waste of limited resources. Another common theme in complex systems, particularly natural systems, is adaptive growth. They respond to specific demands and environmental conditions present during their formation. Research aimed at modeling natural systems resurged in the 1980’s with ‘genetic algorithm’ optimization techniques showing promise.

More fundamental to the notion of adaptive design or generative design, however, is the question of problem formulation. How do we build a system to adapt? What does it adapt to?This workshop will investigate the formulation of an adaptive system based on optimization methodologies. Here, the notion of optimality – generally understood to be a singular, mathematical minimum – is reconsidered as a catalyst for design. A rigorous definition of optimization will be applied translating a ‘generalized design model’ into a ‘performance design model’. The student will see how the performance model is easily tested and evaluated against a variety of performance measures, including testing by structural analysis. Students

will also investigate how this approach reveals relationships between elements of design and/or dependencies between often seemingly unrelated aspects of building construction.Optimization methodologies are well suited for studying interrelatedness if only because in their formulation all relationships are predetermined, both explicitly and implicitly (as in the case of dependent criteria). We will use parametric formulations to develop relationships and dependencies between design elements in a 3D modeling environment. Additional studies will be assigned to develop greater intuition of parametric ‘controls’.

TOOLS // CATIA / EKL SCRIPT

INSTRUCTOR // ADAM MODESITT / SHoP

VISUAL STUDIES

ADAPTIVEFORMULATIONS

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ROTATION AXIS - XANGLE IN DEGREE 10



MODULE BEHAVIOUR

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[01] [02] [03] [04] [05] [06]

/* Assign variables*/Let i(integer)Let j(integer)Let myPanelx(PANELX)Let myPt1(point)Let myPt2(point)Let count(integer)Let attDist(length)Let attCrv(curve)Let StartX(length)Let StartY(length)Let StartZ(length)

/* Linking variables to the parametric model*/attCrv = Attractor\Spline.1 StartX = Input_Geometry\GRID_START\X StartY = Input_Geometry\GRID_START\Y StartZ = Input_Geometry\GRID_START\Z

/* //////////Vertical loop///////////*/j=1For j while j <7{ /* /////////// horizontal loop */ //////////// i=1 For i while i < 100 { count = Relations\SCRIPT\LIST_PANELS.Size()+1 myPt1 = point(StartX, StartY, StartZ) attDist = distance(myPt1, attCrv) myPt2 = point(StartX,StartY + max(attDist/5,min_panel_size ), StartZ) StartY = StartY+max(attDist/5, min_panel_size ) If StartY >= Input_Geometry\LIMIT\Y { i=100 } myPanelx=CreateOrModifyTemplate(“PANELX”,UDF_instances ,Relations\SCRIPT\LIST_PANELS ,count) myPanelx.UDF_INPUT_1 = myPt1 myPanelx.UDF_INPUT_2 = myPt2 myPanelx.Spline.1 = attCrv myPanelx.xyplane = UDF_Geometry\Plane.5 myPanelx.panel_width = UDF_Geometry\parameters\Width EndModifyTemplate(myPanelx) } StartZ = StartZ+ (2*UDF_Geometry\parameters\Width) StartY = Input_Geometry\GRID_START\Y }

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[07] [08] [09] [10] [11]

FRAME 05SPLINE ATTRACTOR POSITION : 0,6

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//CATALOGUE OF BEHAVIOURS

//SET

UP_1

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The workshop explored generative design methodologies through the application of algorithmic techniques, looking at fundamental coding principles (recursion, feedback, modularity and I/O) while working within an object-oriented framework, opening the door to complex simulation and animate formation. Artificial life, material intelligence, interactivity, and other second-order principles will be approached from the vantage point of “dynamics” and “search” – or the introduction of directed intelligence into a dynamic process of making.Development : A process in which something passes by degrees to a different stage.Behavior: The aggregate of responses to internal and external stimuli.

Behavior and development are understood to be a sum, or aggregate, of a multitude of innocuous decisions. Each is a ‘dynamic’, or a process ‘in time’ that necessarily feeds-back and regulates procedures to promote higher levels of form, organization, and movement. Students will develop a focused inquiry into a specific area of algorithmic dynamics. Here, “dynamics” is meant as a inclusive term for all kinds of activity: formal development, flocking, embryology, automata, FEA, fractals and l-systems are all examples of time-based recursive practices. The class is meant to flesh out a vocabulary and structural understanding of a wide array of algorithms, to look for correspondences among dynamics, mapping and search heuristics. By casting a

wide net, we hope to see opportunities for portability and the development of a critical stance towards algorithmic ‘tooling.’Object-oriented programming (OOP) is a crucial part of the seminar’s approach to algorithms. Modularity is the key to moving beyond simple ‘scripting’ operations, which necessarily focus purely on geometry, towards a behavioral architecture; we wish to provoke architecture into a robust dynamism, to look for correspondences between formal and spatial articulation, environmental factors and other mediums of agency. To achieve this, we must exploit platforms such as Processing that can support spatial research at a speed, intensity and multiplicity beyond that available in the scripting languages of Maya

TOOLS // PROCESSING / RHINO / 3DMAX

INSTRUCTOR // TORU HASEGAWA / MARK COLLINS / PROXYARCH

VISUAL STUDIES

SEARCHADV. ALGORITHM

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LONELINESS_A CELL WITH LESS THAN 2 ADJOINING CELLS DIES

OVERCROWDING_A CELL WITH MORE THAN 3 ADJOINING CELLS DIES

REPORDUCTION_AN EMPTY CELL WITH MORE THAN 3 ADJOINING CELLS COMES ALIVE

STASIS_A CELL WITH EXACTLY 2 ADJOINING CELLS REMAIN THE SAME

Some of the urban densities developments are becoming failure, partly because the lack of studies of different configurationsand typologies. The goal is to develop

a machine which can quickly simulate many urban iterations configuration of urban growth, which can allow

a more careful examination on how urban densities are formulated and evaluate its potential benefits to craft a

more refined and planned environment.

Keywords: Loneliness, Density, Overpopulation, Reproduction,Stasis, Levitation, Cavity.

Studying GAME OF LIFE’s cell behaviors and characteristics give us a sense of inspiration on how urban conditions are

formed. Using cellualr automata (CA) as the game boarddriving engine for the urban simulation. Rules are

developed and inserted to create simulation of urban developments which allow each cell to identify its existing

neighbors and act upon them.

Our code allow us to be able to simulate variety of iterations of urban density developments, such as its

behavior; if overpopulated horizontally, then levitated vertically and if overdensitfied, then create porosity.

These are the intelligences that are integrated into the code to make the urban development simulation more

comprehensive.To conclude, the outcome of iterations are sufficient enough to quickly produce mock ups. There are still

parameters that can be more comprehensive integrating the edge condition to

mediate with the existing enviroments. The future version of code will be able to embrace more external conditions;

such as urban infrastructure, sun exposure, wind protection, variety of typology, etc...

URBAN SIMULATION

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STATE_1 STATE_2 STATE_3 STATE_4

20_DENSITY02_LONELINESS03_OVERPOPULATION05_REPRODUCTION

T_015 T_030 T_045 T_060




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[Create The Game (SETUP)]Create a board with rows,columns and height ready to be populated by cells (XYZdimension).

Fill the defined board with certain density of cells alive only in theground level (XY Plane).

[Play The Game (DRAW)]The game is played using rules defined in the “check” function.The game is visualized by calling the “render” function.

// Rules of The Game (Check function).Every cell checks his neighbors

a_If the cell is in a lonely situation it dies (less than 2 neighbors in the original setting).b_The cell will experiment reproduction if it has enough neighbors alive (more than 3 in the original setting).c_If the environment of the cell is overpopulated then the cell instead of dying moves vertically to an upper level, producing conditions of vertical densification. This densification instead of is affected by external conditions that insert perforations in the system (modeled with a noise function).d_The cell will survive if it has not died affected by the previous rules (stasis).

The rules can be transformed by using sliding bars that change the variables of the number of neighbors necessary to have reproduction-overpopulation-isolation.The game can finish in the first levels or continue growing infinitely depending on those selected values.

//Visualization of The Game (render function)For every calculation the game stores the information in a temporary board. Once all the cells are checked then the visualization occurswith these conditions:_Dead cells are not visualized._Cells alive are plotted in grey (only ground level)._Reproduced cells are plotted in white color (only ground level)._Cells that are forming vertical piles have a degradation of blue color (lighter on the top – darker in the ground level).Two windows show both a 3D of the system and the ground level, where the cells interact, independently to help understanding and analyzing the growing system.

//PSUEDO CODE

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This research was a by-product of PROOF_6 Studio, where apart from our individual work we had the opportunity to work in groups to further explore the role of optimization in architectural design exploration.

The rising complexity of 21st century cities demands a more rigorous and intense understanding of their inherently complex programs, which cannot be resolved by a conventional design methodology. This

paper proposes a new design process using an automated workflow that incorporates the computational iterations and the design values of an architect in a unified process aiming to produce high performing optimized results.

The procedure, that is described, uses CATIA for parametric simulation and ModeFrontier for multi-criteria optimization. The “value meter”, a qualitative assessment, is used to

grade the results according to subjective design ideas. The setup operates in two stages, Phase 1 [city scale] elaborates on broad urban land-use goals, whereas Phase 2 [neighborhood scale] explores detailed objectives such as density and infrastructure. The complete workflow operates under the realms of conventional urban design ideas, but produces exponentially large variety of design alternatives.

TOOLS // CATIA / MODEFRONTIER / EKL SCRIPT

AUTHORS // FOTEINOS SOULOS / EVA POLOUPOLOU / AMIRALI MERATI / ADNAN IHSAN

CRITIC // DAVID BENJAMIN / LIVINGARCHITECTURE

RESEARCH PAPER // SELECTED RESEARCH AT ‘SIMAUD’ -SYMPOSIUM OF ARCHITECTURE AND URBAN DESIGN

CITY OF LOVE AND HATE |54|

AbstractThe rising complexity of 21st century cities demands a more rigorous and intense understanding of their inherently complex programs, which cannot be resolved by a conven-tional design methodology. This paper proposes a new design process using an automated workflow that incorporates the computational iterations and the design values of an architect in a unified process aiming to produce high performing optimized results. The procedure, that is described, uses CATIA for parametric simulation and ModeFrontier for multi-criteria optimization. The “value meter”, a qualitative assessment, is used to grade the results according to subjective design ideas. The setup operates in two stages, Phase 1 [city scale] elaborates on broad urban land-use goals, whereas Phase 2 [neighborhood scale] explores detailed objectives such as den-sity and infrastructure. The complete workflow operates under the realms of conventional urban design ideas, but produces exponentially large variety of design alternatives.

1. INTRODUCTIONThe use of computation and simulation in urban design has a long line of precedents. Conducted research varies from Michael Batty’s studies at UCL on agent -based models (ABM) and cellular automata (CA) to the gaming approaches of MVRDV such as the “Space Fighter”, “Function Mixer”, “Access Optimizer”. These approaches treat issues of entropy, evolutionary urbanism, complexity, game theory or the use of multiple scenarios for the introduction of decision making processes in urban planning. This long list of new concepts and processes used in urbanism has a complementary analytical aspect related to GIS technology and software such as Urban-Sim and Arch view that merge cartography, statistical analysis, and database technology.From these precedents one can see examples of urban plan-ning that already use multi-objective optimization. However, in most cases the optimizations is part of an intuitive process, therefore it is not automated. In other cases, extensive simula-tion is used but the interface doesn’t allow for a clear overview

of the changing inputs. Or even if the simulation is legible, the design tools cannot generate thousands of designs. Learning from the shortcomings of previous experience we introduce a new design tool with the following features:• Multi-objective optimization• Automated process• Legible interface of inputs-outputs• Thousands of design permutations• Post-processing tools for the evaluation of the resultsFor the first phase of our experiment we took a simple urban grid as our case study and chose proximity and adjacency as our primary criteria based on the “state change” technique. State change is a scripting technique through which an integer is assigned to each specific type of design feature (e.g. the dif-ferent types of program) in order to give the possibility to the user or the optimiza-tion software to automatically replace the feature by changing the integer. This technique is very useful for the optimiza-tion process since it allows for easy control of the design permutations. The reason for choosing state-change and proximity rules as our primary simulation technique is three -folded:This technique has been widely used and is still being used by a variety of advanced urban analysis and simulation institutes (e.g. CASA: Centre for Advanced Spatial Analysis, University College London- Cities as Complex Systems) and it has proven to perform well both for high resolution and low resolution simulations regardless of its simplicity.1) It is applicable to a spectrum of scales from regional to local.2) It has proven to be a good match once it is integrated with GA (Genetic Algorithm) which is the primary optimization engine.Further, the same logic was re-applied to the urban grid but this time instead of using a neutral empty grid we incorpo-rated some natural (lake) and manmade (historical building) elements to our grid as a means of simulating preexisting ur-ban conditions (Figure 1). In the second part of our experiment

we expanded the model by adding circulation- infrastructure (roads) and density (height regulations) (Figure 2).Our workflow includes the parametric software CATIA used for modeling and simulation of urban conditions such as at-traction or repulsion of program through the scripted process of proximity and scoring (value meter). The complete design setup is fed in Mode Frontier for automation and multi-criteria optimization. It is important to point out that the urban simulation is incorporated to the same workflow through the proximity method which is evaluated as positive or negative according to a value system that can take different forms depending on designers’ preference, urban legislation or com-munity boards and commissions.

2. EXPERIMENT 1The first experiment operated on more generic premises of ur-ban fabric. A 8x8 point grid was generated as a basic structure of the urban fabric. We assign these points four land uses as inputs, Residential, Commercial, Industrial and Green Space. Each point could host any of these four programmatic land uses. Even such a small setup can create 64 to the 4th power =16,777,216 permutations of possible relationships among urban programs. And part of the intention for automating design is to discover a wide-design space and novel proposals that are beyond known rules of thumb. The aim of the experi-ment was to explore the relationships/adjacencies formed between these programs and evaluate them based on their arrangement.

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Basically, our ambition was to achieve heterogeneous arrangements of program in addition to specific qualities of proximity (e.g. housing attracted to green space but repelled by industry). These relationships are evaluated using a scoring system or as we call it a value meter, whereby a relationship is rated, either positive or negative, and stored as a score (Figure 3). The criteria for the score of individual relationship is not scientific but is rather based on architectural / urban case-studies. The formulation of these criteria is later discussed in the research paper.The automated test ran with an initial population of 50 urban land-use arrangements generated using random algorithm, and another 20 generations was created using MOGA-II search producing 1000 design outcomes. Each experiment

took approximately two minutes. In the end the optimization software’s charts were used to identify high-performing designs (Figure 4). It is important to note that the optimization software does not give a definite solution but varying design proposals that are optimized. It is further the designers job to look through these design outcomes for the most interesting and unexpected results that overcome the standard rules of thumb.As far as the content of the experiment is concerned, we expected to observe some kind of clustering of land uses depending on our value meter’s setup. For example, clusters of housing surrounded by green spaces or clusters of industry surrounded by commercial. We also expected to see results of totally even grids (e.g. only residential), so we introduced percentages to the experiment in order to avoid this possibility (percentages are further discussed separately). The results of

the experiment confirmed our expectations, but also produced high-performing results that did not correspond to the above clustering logic (Figure 5). Unpredictability was increased in the experiment after the introduction of the pre-existing elements and the extension of the value meter (Figure 3) in order to include local relationships between the new land uses and the manmade or natural topography.3. EXPERIMENT 2After completing experiment 1, we used some of the high-performing designs to initiate our second experiment. The second experiment addresses more detailed issues of urban planning and design. In this experiment we explore how different arrangements of road types affect the density on the chosen outcomes of previous experiments. There are three types of road inputs; green for highway roads, red for double-lane road and blue for a single lane road. The tracing of the road network was pre-defined manually in our experiment but the type of road was allowed to change through “state change” operation in EKL scripting of CATIA. This decision allows the designer to define the neighborhood scales. After defining the tracing, the rest of the process is once more automated.Among the land use programs, green-spaces and industrial zones are not affected or automated in the process of this experiment but the residential and commercial zones are affected by their proximity to a particular road type. The probable outcomes of road instantiation are translated into vertical lengths representing density and height limitations in our experiments. The green line (highways) induces a height of 15m, the red line (double-lane roads) generates a height of 10m and lastly the blue-line (single-lane) creates a height of 5m on its neighboring zones. These discrete height values are not an outcome of an equation but are defined by us as qualitative parameters through a third value meter. Once again the adjacencies of land uses and roads generate a value based on their relationship (Figure 6). These values of relationships are defined by our research on the best known practices. The parametric CATIA model is fed to Mode Frontier to optimize for highest score and narrow its count to a desired percentage

of the total. An initial population of 50 random designs was used through a generation of 10 to produce optimized design proposals (Figure 7). The intent behind this automated process is to create a tool that can be used not only for exploitation, but rather for exploration of new novel designs. Although we were expecting the road types to scatter randomly we realizedthat the high-performing results (Figure 8) that the workflow came up with, ended up presenting aspects of hierarchy and symmetry (e.g. same type of roads are parallel and next to each other).4. SIMULATION TOOLSThe way we address urban simulation is through incorporating it to the design and optimization workflow, without using any additional software. A scripted method of calculating and scoring proximity relations as positive or negative is summarized by the value meter that directly affects the final design. This technique introduces the use of computation for solving qualitative aspects of social, cultural and urban problems in addition to quantitative technical issues. This can be part on a general debate of what defines the design of a successful city in the 21st century.4.1. VALUE-METERThe value-meter refers to the idea of preference and how this can be translated into computational knowledge. Especially in the case of urban design, where no such thing as a global setup can be applied, it is important to find a way of letting the computer know what would be preferable each time, so that the proposals derived from the workflow can make sense on different contexts. Since urban design is primarily about relations of proximity of different land uses, our main goal became to create a tool through which the urban planner/architect could easily set his intentions in a simple workflow that can incrementally become more and more complex. In order to do so, we used a scoring system through which the user can transfer his preferences into the program. Through this system that we call value meter, the program (ModeFrontier) will be capable to evaluate the result according to the designer’s personal set of values.

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The value meter was created by setting positive and negative scores for programmatic adjacencies, following a debate on what makes a successful city. The results of the debate are inserted to a table of values including the relationships between all the possible combinations (Figure 3). So, in the first experiment we made a list that contained all of the possible neighboring elements, such as residence next to residence, industry next to commercial etc. Then, the second thing that was defined was the range of possible scores. Generally, the range depends on the quantity of combinations that exist, and that is why in our case of a balanced system of four different elements, the range is a set of integers from ‘-2’ to ‘+2’. The simulation setup is designed with the intelligence to avoid negative relationships and encourage positive ones in order to produce high-performing heterogeneous arrangements. Similarly, in the second experiment a table with combinations between land uses and road sizes is also designed (Figure 6) in order to define what kind of road will be preferably placed next to a particular land use.

Through the proximity setup that the experiment uses, the software (CATIA) can calculate all of the neighboring conditions and evaluate them according to our scoring system through a custom script. ModeFrontier is also set up to keep all these evaluations to high numbers. This way, the software constantly weighs all of the contradicting goals and comes up with several designs, while the generative algorithm tries to filter all the desired characteristics in order to satisfy the objectives and produce even better results. We realized during the process of the experiments that the generative algorithm needed a certain amount of time in order for to start learning how to produce a more successful design. Most likely the large numbers of 64 inputs with 16,777,216 possible design permutations were making it hard for the software to narrow down the optimized results early in the experiment. However, already after running the experiment for a random initial population of 50 for 20 generations with a MOGA-II algorithm, which corresponds to approximately 1.30 minutes

per iteration, Mode Frontier came up with results that can be used in order to derive conclusions . Obviously, running the experiment for longer would produce even better designs.

4.2. PERCENTAGESIn order to prevent the optimization software from converging towards one type of high-scoring relationship and additionally address the question of quantifying the land uses in an urban design, we created a group of percentage parameters in CATIA that represent the four land uses of the experiment. The reason behind this decision is that the ratios of land uses and program are critical to urban planning and most of the times define whether a proposal meets the necessary requirements. Since one of the major tendencies we observed in the designs that the workflow produced was the scattering of land uses across the master plan, it was hard to quickly quantify the land uses, which made the percentage output useful.Taking this to another level, these percentages can also be set as objectives. For instance, we can set the program to optimize for 60% residential, 15% retail, 5% green spaces and 10% industry. To do that we use the formula:Percentage residential = abs(60% * total number-x)In this formula ‘x’ is the number of the produced residential blocks, and Mode Frontier is being set to minimize this absolute difference so as to achieve this percentage. Another experiment would be to define only some of the land uses through percentages and leave others be processed by the optimization software in order to explore more possibilities and potentially come up with unexpected high-performing designs. Percentages can therefore obtain a double role, as they can contribute in the evaluation of the results or they can be set as goals, depending on the designer’s needs.We believe that the value meter combined with the percentages are powerful tools that are applicable to processes beyond the urban simulation approach. They are easily adjustable to several types of experiments, as demonstrated in our case where they were used for different things in two subsequent experiments. Although in each case the

elements and the values were different, the process still worked successfully. The abstract platform of such tools can be applied to different types of design processes, outside urbanism, such as the creation of complex façade systems, or the aesthetic optimization of a structural system without loss of performance. The ambition behind the automation of already established urban design strategies, apart from the rapid production of massive design permutations, is the production of possible unexpected high-performing results. This can lead to the development of different strategies, as it reduces the designers’ predisposition towards received ideas about neighboring programs, densities, circulation networks etc at the early design stage. Of course, this doesn’t mean that the workflow completely neutralizes their contribution to the produced urban form. After all, as already explained, the system is highly dependent on the architect’s values (value meter and scoring systems) and will produce different results for different value setups. An initial setup valuing the relationship between industry and housing as positive will favor the neighboring of these two uses, although this is largely considered as unacceptable in terms of quality of life, but could be considered as desired in another type of industrial performance-based scenario.

As a conclusion, this experimental workflow intends to create a balanced system of urban design in terms of computational objectivity and architectural predispositions or urban design policies. This exploration tool does not claim to present instant ideal solutions to urban design problems. On the contrary it aims to automate the process of urban design in a way that will allow for a more thorough exploration of the potential that lies in the highly normative urban space. Realizing the flexibility behind the topographical and regulative constraints would be succeeding this experiment. Interpreting and overlaying the results of the computation process to the usual manual process would probably enrich and facilitate the way urban design is generated.

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References

BATTY, MICHAEL, “CITIES AND COMPLEXITY : UNDERSTANDING CITIES WITH CELLULAR AUTOMATA, AGENT-BASED MODELS, AND FRACTALS”, CAMBRIDGE,MASSACHUSETTS,MIT PRESS, C2005.BATTY, MICHAEL, “URBAN MODELLING : ALGORITHMS CALIBRATIONS, PREDICTIONS”, CAMBRIDGE, CAMBRIDGE UNIVERSITY PRESS, 1976.MAAS,WINY, “SPACE FIGHTER : THE EVOLUTIONARY CITY (GAME: ) : MVRDV/ DSD IN COLLABORATION WITH THE BERLAGE INSTITUTE MIT AND CTHROUGH”,BARCELONA, ACTAR,2007.DANIEL DEKKERS, WIELAND & GOUWENS A.O. AND MVRDV, “THE REGIONMAKER, RHEINRUHRCITY ”, OSTFILDERN-RUIT, HATJE CANTZ , 2002.

FIGURE.1

FIGURE.6

FIGURE.5FIGURE.3

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This research was a by-product of PROOF_6 Studio, where apart from our individual work we had the opportunity to work in groups to further explore the role of optimization in architectural design exploration.

The rising complexity of 21st century cities demands a more rigorous and intense understanding of their inherently complex programs, which cannot be resolved by a conventional design methodology. This

paper proposes a new design process using an automated workflow that incorporates the computational iterations and the design values of an architect in a unified process aiming to produce high performing optimized results.

The procedure, that is described, uses CATIA for parametric simulation and ModeFrontier for multi-criteria optimization. The “value meter”, a qualitative assessment, is used to

grade the results according to subjective design ideas. The setup operates in two stages, Phase 1 [city scale] elaborates on broad urban land-use goals, whereas Phase 2 [neighborhood scale] explores detailed objectives such as density and infrastructure. The complete workflow operates under the realms of conventional urban design ideas, but produces exponentially large variety of design alternatives.

TOOLS // 3D MAX / FLASH

CRITIC // GEORGE KATODRYTIS / KEVIN SWEET

VIRTUAL /ACTUAL |60|

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BELOW / Mapping movement of the human body in space overtime during a flip kick action. Subject’s

back and limbs are of interest here.RIGHT / Re-animation of the process with the

discovered constraints and logics.

Translation of Kinetic diagrams to surfaces creating spatial / formal products

Sub-division of surface to modularize. An intelligent module will repeat , respond and populate the system.

Abstract model depicting the notion of a modularized skin.

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Adaptive , honey-comb like skin with porosity to facilitate light and ventilation

Aperture 0.2 Site and program information fed into the surface to adapt its porosity to accomodate the requirements

Aperture 0.5Aperture 0.8

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INTERIOR VIEW OF THE EXHIBITION GALLERY

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[00] [01] [02] [03] [04] [05] [06] [07] [08] [09]

[00] [01] [02] [03] [04] [05] [06] [07] [08] [09]

[10] [11] [12] [13] [14] [15] [16] [17] [18] [19]

[10] [11] [12] [13] [14] [15] [16] [17] [18] [19]

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ABOVE: View of the porosity and scale of the skin.RIGHT: Public Plaza

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Translation of novel architectural or design forms to physical reality has increasingly become a challenge for the industry. The use of 3D digital softwares has extended our boundaries of design. But to move them beyond a utopic image into a real design solution relying on gravity, material and economy was a topic of interest when doing this design competion.

This project was conceived for an international design competition. The competition was to lounge chair that had a

strong conceptual idea that could be dealing with ergonomics, culture , efficacy, cost, or even aesthetics.

This proposal criticized the extensive waste of energy in Dubai. Energy used for construction and inawareness of recyclability. This monoque structure was formed through translating the forces of a human body on to a surface which makes the furnture to communicate with the human body in the most efficient and friendly way.

Actualization of this project was done through corrugated cardboard sheets that were cut as unique sections/slices of the furniture. The corrugation helps in giving strength and keeping it as light as possible. Furthermore, the choice of material is not only cheap but extremely cheap and easy to recycle.

Working with these design intents, this project became one of the winning finalist at the Traffic Design Competition.

TOOLS // RHINO / 3DMAX

WINNING FINALIST FOR AN INTERNATIONAL DESIGN COMPETITION

XY PROTO-TYPE |76|

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LEFT / Initial concept sketch. Understand-ing the parts of the body interacting with furnture.ABOVE / Translation of forces onto a adaptable surfaceRIGHT / Morphology / Development of the form to manifest the notion of a seat

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[00]

[30] [40] [50]

[10] [20]

FABRICATION |80|

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Translation of novel architectural or design forms to physical reality has increasingly become a challenge for the industry. The use of 3D digital softwares has extended our boundaries of design. But to move them beyond a utopic image into a real design solution relying on gravity, material and economy was a topic of interest when doing this design competion.

This project was conceived for an international design competition. The competition was to lounge chair that had a strong conceptual idea that could be dealing with ergonomics, culture , efficacy, cost, or even aesthetics.

This proposal criticized the extensive waste of energy in Dubai. Energy used for construction and inawareness of recyclability. This monoque structure was formed through translating the forces of a human body on to a surface which makes the furnture to communicate with the human body in the most efficient and friendly way.

Actualization of this project was done through corrugated cardboard sheets that were cut as unique sections/slices of the furniture. The corrugation helps in giving strength and keeping it as light as possible. Furthermore, the choice of material is not only cheap but extremely cheap and easy to recycle.

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