Lecture notes of the course Future Models I (AR1TWF030), The Why Factory, Directed by Prof. Winy Mass, TU Delft, Faculty of Architecture and Built Environment

1. 11
On Computational Design
An overview of essential topics and approaches
Dr.ir. Pirouz Nourian
Assistant Professor of Design Informatics
Department of Architectural Engineering & Technology
Faculty of Architecture and Built Environment

2. 22
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
WYSIWYG versus WYSIWYM
𝑥2
+ 𝑦2
= 𝑅2
The Product vs The Process

3. 33
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Parametric Modeling & Design
• Thinking of parameters instead of numbers!
• Same rationales, many alternatives!
▪ We could model an actual circle as a particular instance of a generic circle, which is
the locus of points equidistant from a given point as C (center), at a given distance R
(Radius), on a plane p.
▪ Parametric modeling is essential for formulating design problems
▪ The same role algebra has had in the progress of mathematics, parametric modeling
will have in systematic (research-oriented) design.
𝑥 = 𝑟𝑐𝑜𝑠(𝑡)
𝑦 = 𝑟𝑠𝑖𝑛 𝑡
𝑡 ∈ [0,2𝜋]
𝑡 =
2𝜋𝑖
𝑛
|𝑖 ∈[1,n]⊂ ℕ
Plane
Radius
Circle

4. 44
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Hierarchical Decision Making
Synthesis SynthesisSynthesis
Evaluation Evaluation Evaluation
Structural Logic
Shape
Structure Details
Materials
Construction
Analysis Analysis Analysis
Phase 0:
Design Intent
Phase 1:
Design Development
Phase 2:
Detail Design
Climatic Logic
Functional Logic Configuration

5. 55
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
How to reach at good solutions out of many alternatives
(optimization/control techniques)
• Identification of spatial/physical design principles
• definition of design goals in terms of performance
criteria; and defining a phase-model for the parametric
design process: from schematic design to detailing;
• formulation of ‘design problems’ (parameterization);
• parametric generation of design alternatives (in
collaboration with Architect, Structural Designer,
Designer Building Services, Façade Designer and Project
Manager);
• performance measurements (again in collaboration with
the other team members);
• design optimization (maximization of desired performance
measures)
Exploration/Optimization Framework
Goals Principles Formulation Evaluation

6. 66
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Common Misconceptions!
• we can automate the design process!
• parametric design is another architectural style!
• parametric design= grasshopper!
• computational design is a magic art!
• computational design is for geek guys!

7. 77
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Using sophisticated software applications does NOT
necessarily mean doing computational design!
• If we start with wrong assumptions at the beginning, a simulation tool cannot
tell us what to do to improve our design!
• Even if we optimize minor things at a late stage of design, the whole
configuration might be extremely ineffective and inefficient due to initial
decisions!
• Most important decisions pertained to configuration and shape are made at
early stages of design process!
Design
(CAD)
Simulate
(FEA)
Label!
(LEED)
Certified—45
points
Silver—60 points
Gold—75 points
Platinum—90 points

8. 88
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Why Computational Design?
What is it that we could not do without computation?
How do we design for better life (more sustainable if you like)?
But what is good??? And how do we compare actual design alternatives?!
How do we know if our design is going to work as intended?
How can we underpin our design as to its functional rationale?
What is it that we could do better with computation?

9. 99
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
How do we design methodically?

10. 1010
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
How do we design methodically?
1. Create (synthesize) objects systematically
2. Measure (analyze/simulate) qualities quantitatively
3. Compare (evaluate) designs objectively

11. 1111
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
How do we design methodically?
1. Create (synthesize) objects systematically through:
• parametric formulation of phenotypes
• systematic generation of genotypes
2. Measure (analyze/simulate) qualities quantitatively
• Analysis using mathematical models, non-contextual
• Simulation using computational models, contextual
3. Compare (evaluate) designs objectively using:
• Absolute Extremums
• Standards/Milestones/Benchmarks
• Evaluation Frameworks

12. 1212
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Design Process
• Design is about making things
• Science is about knowing things
• Design is about working on vague problems that have no definitive solution!
• A design is a concrete proposition for an abstract demand.
• Philosophically, there can never be a proof that a design is the best it could ever be!
(Rittel, 1973)
• Formulation is as important as problem-solving. (Simon, 1999)
• Design is a process of co-evolution of problems and solutions (Cross & Dorst 2007),
through analysis, synthesis and evaluation (Lawson, 2005).

13. 1313
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Design Process
The process of “thinking” for “making” something based on needs,
intentions, requirements and constraints.
 Cross & Dorst 2007
Lawson 2005 

14. 1414
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
What is it? Who is she?

15. 1515
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Computation
Computers and computer are causal systems; meaning, programs and computers
DO NOT THINK in the sense that human beings do; they do not have intentions,
motives, anticipation or creativity: they just act as programmed!
Information processing
by means of algorithms
An algorithm is
a technical recipe for doing something
Image courtesy of http://iheartapple.com

16. 1616
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
To avoid misconceptions:
Analysis and Simulation are meant to provide an indication of Performance (Functionality) of an
Environment by means of Mathematical Models or Computational Models (respectively).
Analytic or Simulated Performance measurements are neutral per se.
Evaluation is a step above Analysis and Simulation that is to conclude with a judgement on the
relative quality of a building/’design’ compared to other buildings/’designs’.
Optimization is the systematic process of seeking the highest attainable level of quality.
Optimization processes are generally either set up as feed-forward or feed-back control
mechanisms.

17. 1717
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Performance Analysis
Measuring potentials, 80% mathematical-20% computational
• Continuous Models:
Analytic measurements using
mathematical models of objects, e.g.
curvature analysis
• Discrete Models:
Analysis of walkability by finding
distances on a network using optimal
path algorithms

18. 1818
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Performance Simulation
Measuring dynamics, 20% mathematical-80% computational
How does a ‘system’ behave (affects or gets affected by) in a particular ‘environment’?
For example, how much a certain building will be lit throughout winter in Amsterdam?
Agent Simulation, image courtesy of Space Syntax LtdSolar Gain Estimation

19. 1919
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Performance Evaluation
How good a system is behaving/performing?
• Quality criteria
• A quantitative interpretation of performance simulations/estimations
• How to tell if design A is performing better than design B?
• Defining an “objective function”
Solar Gain Estimation and Evaluation: comparing a set of different design alternatives for a courtyard housing block

20. 2020
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
A) Continuous Changes:
• Feed-Forward using mathematical analysis or computational simulation
• Feed-Back  using meta-heuristic methods such as evolutionary algorithms, simulated
annealing, swarm intelligence, etc.
Parametric
Circle
Radius𝑟 = ൗ𝐴
𝜋
A 100 𝑚2
big circle
Parametric
Circle
Radius circle
Manipulate R
to minimize Δ
Compute
Area
How do we make a circle that is as big as 100 𝑚2
?

21. 2121
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
B) With Topological Changes
Catalogue/Enumerate and Rank  listing all(most important) possibilities
What layout topologies are possible for our configuration? And which of them is the best…
A syntactic architectural design methodology, Nourian et al, 2013

22. 2222
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
▪ Problem Formulation:
• Defining Design Goals
• Determining the Hierarchy of Goals and their Corresponding Decisions
• Formulating Design Principles (multiple disciplines)
• Ideation for Integrating Design Principles in a Configuration
• Identifying Trade-Offs and Formulating Optimization Problems
• Algorithmic Sketching of the Idea
▪ Design Development:
• Designing a Computational Workflow
 Mathematical Interpretation
 Identifying Systems and Sub-systems
 Drawing Flowcharts
 Writing Pseudocode
• Programming/Workflow Modelling
▪ Problem Solving:
• Feed-Forward Optimization
• Feed-Back Optimization

23. 2323
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
▪ Problem Formulation:
• Defining Design Goals
• Determining the Hierarchy of Goals and their Corresponding Decisions
• Formulating Design Principles (multiple disciplines)
• Ideation for Integrating Design Principles in a Configuration
• Identifying Trade-Offs and Formulating Optimization Problems
• Algorithmic Sketching of the Idea
▪ Design Development:
• Designing a Computational Workflow
 Mathematical Interpretation
 Identifying Systems and Sub-systems
 Drawing Flowcharts
 Writing Pseudocode
• Programming/Workflow Modelling
▪ Problem Solving:
• Feed-Forward Optimization
• Feed-Back Optimization
Watch at home!

24. 2424
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
▪ Problem Formulation:
• Defining Design Goals
• Determining the Hierarchy of Goals and their Corresponding Decisions
• Formulating Design Principles (multiple disciplines)
• Ideation for Integrating Design Principles in a Configuration
• Identifying Trade-Offs and Formulating Optimization Problems
• Algorithmic Sketching of the Idea
▪ Design Development:
• Designing a Computational Workflow
 Mathematical Interpretation
 Identifying Systems and Sub-systems
 Drawing Flowcharts
 Writing Pseudocode
• Programming/Workflow Modelling
▪ Problem Solving:
• Feed-Forward Optimization
• Feed-Back Optimization
IN OUT
A CAUSAL SYSTEM
Nourian, Rezvani, Sariylidiz, 2013, Space Syntax for Generative Design

25. 2525
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
▪ Problem Formulation:
• Defining Design Goals
• Determining the Hierarchy of Goals and their Corresponding Decisions
• Formulating Design Principles (multiple disciplines)
• Ideation for Integrating Design Principles in a Configuration
• Identifying Trade-Offs and Formulating Optimization Problems
• Algorithmic Sketching of the Idea
▪ Design Development:
• Designing a Computational Workflow
 Mathematical Interpretation
 Identifying Systems and Sub-systems
 Drawing Flowcharts
 Writing Pseudocode
• Programming/Workflow Modelling
▪ Problem Solving:
• Feed-Forward Optimization
• Feed-Back Optimization Configraphics: Graph Theoretical Methods of Design and Analysis of Spatial Configurations,
Nourian, P, 2016

26. 2626
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
▪ Problem Formulation:
• Defining Design Goals: Pen & Paper
• Determining the Hierarchy of Goals & Decisions: Rationalization
• Formulating Design Principles: Diverge, Agree to Disagree, Abstract & Generalize
• Ideation for a Configuration: Converge and Synthesize One Solution
• Identifying Trade-Offs and Formulating Optimization Problems: Pen & Paper
• Algorithmic Sketching of the Idea: parametrize the idea or define it based on rules
▪ Design Development:
• Designing a Computational Workflow
 Mathematical Interpretation: pen & paper
 Identifying Systems and Sub-systems
 Drawing Flowcharts: www.draw.io
 Writing Pseudocode: pen & paper
• Programming/Workflow Modelling
▪ Problem Solving:
• Feed-Forward Optimization: genotype creation (e.g. by network configuration)
• Feed-Back Optimization: phenotype evolution (e.g. by genetic algorithms)

27. 2727
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Processing & OSGeo
Generative Components on Micro Station
Viz on SketchUp
Node Editor on Blender
Marionnette on Vector Works

28. 2828
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Collaborative Workflow
Technical Integration of Designs and Building Information Model
https://flux.io/

29. 2929
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Plugins that we recommend:
Structural Design Computations:
• Kangaroo
• Millipede
• Karamba

30. 3030
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Plugins that we recommend:
Climatic Design Computations:
• Ladybug
• DIVA
• ArchSim

31. 3131
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Plugins are out there:
BIM Plugins
• Geometry Gym
• GH>>Revit
• Visual ARQ
• Chameleon

32. 3232
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Plugins that we recommend:
Topological Mesh Modelling
• Mesh Edit (UTO)
• Weaver Bird
• Leopard
• Mesh(+)

33. 3333
• What it is
• What it is not
• Why
• How
o Theory
o Practice
• Design Process
• Computation
• Terminology
o Analysis
o Simulation
o Evaluation
o Optimization
• Methods
• Techniques
• Platforms
• Tools
Plugins that we recommend:
Architectural Design Computations
• Spider Web
• Syntactic (Space Syntax)

34. 3434
Good Luck
Questions:
p.nourian@tudelft.nl