Daylight as an Evolutionary Architectural Form Finder. Tarek Rakha The American University in Cairo...

Daylight as an Evolutionary Architectural Form Finder.

Tarek RakhaThe American University in Cairo Paper id: 121

Authors:Tarek Rakha and Khaled Nassar.

Paper Contents

• Introduction– Objectives– Literature Review

• Ceiling Form Optimization Methodology– Daylighting/Ceiling Problem Formulation– Optimization Process

• Ceiling Example, Results & Discussion– Optimization Results– Ceiling Form & Daylighting Analysis

• Conclusion

Introduction

ConclusionResults / DiscussionMethodologyIntroduction

Evolution of form generation is becoming based on performance (performative) strategies

• Emphasis shifts from the

“Generation of Form” to the

“Finding of Form”.

Kolarevic B (2005) Computing the performative. In: Kolarevic B and Malkawi A, eds. Performative Architecture: Beyond Instrumentality. New York: Spon Press.

Introduction

• Objective– Develop a Computer Aided Architectural

Design (CAAD) procedure/tool for optimizing a generic curvilinear ceiling form in accordance with daylight uniformity.

• Literature Review– Geometry of Form– Shading Devices– Window Design


Ceiling Form Optimization Methodology


What is a Genetic Algorithm(GA)?

Yi, Y. and Malkawi A., (2009). Optimizing building form for energy performance based on hierarchical geometry relation. Automation in Construction 18: 825-833.

Stage 1:

Stage 2:

Stage 3:


• Daylighting/Ceiling Problem Formulation




Sweeped B-spline Ceiling

𝐂(𝑡) = σ 𝑓𝑖ሺ𝑡ሻ𝐏𝑖𝑚𝑖=0 ; 𝑡 ∈ሾ0,1ሿ. 𝑃𝑖𝑤 = (𝑤𝑖𝑥𝑖,𝑤𝑖𝑦𝑖,𝑤𝑖𝑥𝑧𝑖,𝑤𝑖)

Domain = ۏێێێێێ

Z01 Y11 Z11 Y21 Z21 . . . Ym1 Zm1 Zm+11Z02 Y12 Z12 Y22 Z22 . . . Ym2 Zm2 Ym+11. . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . .Z0n Y1n Z1n Y2n Z2n . . . Ymn Zmn Zm+1n ےۑۑۑۑۑ

Chromosome

Gene

P2(z2,y2)


• Optimization Process


Fitness Functions: Daylight Uniformity

Fሺxሻ= Emax/Emin F′ሺxሻ= 1/F(x)




G1 a

G2 a

G3 a

. .Gg a

G1b

G2 b

G3 b

. .Gg b

G1 a

G1 b

G3 a

. .Gg a

G1 b

G2 a

G3 b

. .Gg b

Parent “a”

Parent “b”

Child “1”

Child “2”

Parent “a”

Parent “b”

Child “1”

Child “2”

Randomly chosen control node gene for crossover

Randomly chosen control node gene for crossover and mutation

Mutated gene

Parent “a”

Parent “b”

Roulette wheel selection of parent ceiling chromosomes

G1 a

G2 a

G3 a

. .Gg a

G1b

G2 b

G3 b

. .Gg b

G1 a

G1 b

G3 b

. .Gg a

G1 b

G2 a

G3 a

. .Gg b

Crossover

Mutation




Setting Up Model Data

Environmental Conditions:- Geographic Location – Cairo, Egypt

- Date and Time – June 21st, 12 Noon

Model Geometry:- Case Geometry and 3D Form- Materials

Population of Chromosomes

Generate random B-spline control

genes

Populate B-Spline Ceiling Chromosomes

Chromosomes (Geometry) Database

Daylighting Performance Simulation

Radiance Daylighting Simulation

Model Sweeped B-Spline Geometry

Performance (Illuminance)

Database

Fitness Function Evaluation (Uniformity Ratio)

Reproduction and Breeding

ParentRoullete Selection

Crossover Node Genes

Mutate and Crossover Node

Genes

Continue?

Offspring B-Spline Chromosome

Results

Yes

No

OR

Ceiling Form FindingExample, Results & Discussion

• Example Case



• Example Case


Simulation parameters were as follows:

Location: Cairo, Egypt (Latitude: 29.8, Longitude: 31.3). Date and time: June 21st (summer), 12 Noon. Sky condition: clear sky with sunshine. Ground reflectance: 20% - medium colored stone. Walls reflectance: 56% - off white color paint. Ceiling reflectance: 85.7% - plasterboard. Floor reflectance: 59.2% - grey colored concrete. Glass visible light transmittance (VLT): 85%. Analysis grid: 20 measuring point in a grid of 2.5m *2.5m at a height of 0.75m. Four B-spline ceiling control nodes (P0, P1, P2 and P3) with limitations: (2.0m < z1, z2 < 3.5m), (2.2m < z0, z3 < 3.3m), (0.1m < y1 < 5.4m) and (5.4m < y2 < 10.79m)

55.5

66.5

77.5

88.5

99.510

0 10 20 30 40 50

Uni

form

ity

Rat

io

Iteration

Run Results for 100 Population/Iteration

55.5

66.5

77.5

88.5

99.510

0 10 20 30 40 50

Uni

form

ity

Rat

io

Iteration




• Optimization Results

55.5

66.5

77.5

88.5

99.510

0 10 20 30 40 50

Uni

form

ity

Rat

io

Iteration


55.5

66.5

77.5

88.5

99.510

0 10 20 30 40 50

Uni

form

ity

Rat

io

Iteration




• Optimization Results

5.1

5.2

5.3

5.4

5.5

5.6

5.7

1 8 15 22 29 36 43 50

Uni

form

ity

Rat

io

Iteration

Minimum Uniformity Ratio

50 Populations 100 Populations

5.1

5.6

6.1

6.6

7.1

7.6

1 8 15 22 29 36 43 50

Uni

form

ity

Rat

io

Iteration

Population Average


5.1

5.2

5.3

5.4

5.5

5.6

5.7

1 8 15 22 29 36 43 50

Uni

form

ity

Rat

io

Iteration

Minimum Uniformity Ratio


5.1

5.6

6.1

6.6

7.1

7.6

1 8 15 22 29 36 43 50

Uni

form

ity

Rat

io

Iteration

Population Average




• Ceiling Form & Daylighting Analysis

Selected chromosomes of ceiling form changes.



• Ceiling Form & Daylighting Analysis

Optimized

Unfit



• Discussion

Ceiling geometry that gives comparable performance, allowing choice in optimum design (50 p/i).

Through this procedure, the code demonstrated different novel directions for performativly fit geometry, which leaves the architect with a variety of choices for design.

The computer now becomes more than a visualization tool; an unbiased tireless partner in design with extraordinary ways of approaching problems.

Conclusion


Conclusion


FurtherResearch

Architectural Design is the Elegant Science of Creation

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Daylight as an Evolutionary Architectural Form Finder. Tarek Rakha The American University in Cairo...

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