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Join the conversation #AUCity #AU2018
DynaShape Your Architectural
DesignsA Practical Approach to Designing Complex Forms in
ynamo
Long NguyenResearch AssociateInstitute for Computational Design & ConstructionUniversity of Stuttgart
Dieter VermeulenTechnical Sales Specialist AEC
Computational Design & EngineeringAutodesk
© 2018 Autodesk @LongNguyenP @BIM4Struc Join the conversation #AU2018 #AUCity
• Researcher in Computational Design
• Background in Computer Science / Computer Graphics
• Current interests: Computational Geometry, Evolutionary Design,
Simulation, Optimisation, Generative Design, BIM (and beyond)
• Active in teaching (online & offline)
About us: Long Nguyen
@LongNguyenP
www.linkedin.com/in/LongNguyenP
www.youtube.com/user/LongNguyenPhuoc
© 2018 Autodesk @LongNguyenP @BIM4Struc Join the conversation #AU2018 #AUCity
• Technical Sales Specialist AEC @ Autodesk
• Computational Design & Engineering
• Structural Engineer based in Belgium
• +15 years experience in structural engineering
About us: Dieter Vermeulen
@BIM4Struc
www.linkedin.com/in/dietervermeulen
www.youtube.com/user/RevitbeyondBIM
www.revitbeyondbim.wordpress.com
www.autodesk.typepad.com/bimtoolbox/
AU Online Profile
© 2018 Autodesk @LongNguyenP @BIM4Struc Join the conversation #AU2018 #AUCity
In this class you will learn about
▪ The main functionalities of DynaShape
▪ Some common geometric and physical principles in computational design
▪ Using DynaShape in an optimization workflow (Choosing relavant
parameters, evaluating design criteria, visualizing result, applying
evolutionary optimization using Refinery)
▪ How computational design algorithms help expanding design possibilities
Key Learning Objectives
© 2018 Autodesk @LongNguyenP @BIM4Struc Join the conversation #AU2018 #AUCity
▪ Completely free and open source https://github.com/LongNguyenP/DynaShape
▪ Extensible: by defining custom goals and constraints (using C#)
▪ The core algorithm is based on projection-based constraint solver and projective dynamic
• Projective Dynamics: Fusing Constraint Projections for Fast Simulation
• ShapeOp: a robust and extensible geometric modelling paradigm
DynaShape
▪ Usages:
• Form-finding by computing the equilibrium of
the physical forces driving the design
geometries
• Form-finding based on solving multiple, often
conflicting, geometric constraints
• Optimizing existing designs
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Optimize quad panels for planarity(example by Zach Kron)
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Hanging Chains
An elegant way to generate compression-only form (e.g. arches)
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Hanging Chains
Mannheim Multihalle, Frei Otto
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Shape Matching constraints
Target Shape(e.g. a square)
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Shaping matching constraints
(Partially) covering a doubly-curved surface with identically-shaped elements
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Shaping matching constraints
(Partially) covering a doubly-curved surface with identically-shaped elements
CATENARY SHELLComplex frame & panel design based on relaxation and gravity
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Phase 1Parametrizing Geometry
Phase 2Evaluate Design Criteria
Phase 3Visualization of Results
Phase 4Design Optimization
Catenary Shell – Geometry Evaluation & Optimization
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Dynamo Core (“Sandbox”) – v.2.0.1
Packages used▪ DynaShape 0.5
▪ Mesh Toolkit 2.0.1
▪ Optimo for Dynamo
▪ Custom nodes as indicated in the info group
Dynamo & Packages
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PHASE 1Parametrizing Geometry
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PHASE 2Evaluate Design Criteria
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Evaluation of the structural concept
EVALUATION
Rectangularity check
Planarity check
Number of elements not meeting requirements
Surface area of a quad
INPUT
Anchor Positions X
Anchor Positions Y
CONSTRAINTS
Rectangularity Difference
Planar Deviation
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PHASE 3Visualization of Results
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Display of Evaluation Results
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PHASE 4Design Optimization
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Generative Design Process
GENERATEDATA EVALUATE SELECT
EVOLVE
Contraints
and requirements
Manual design
refinement
Initialization Generative Design Post-Processing
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Design Option Optimization
Catenary Shell Definition
Design Concept Evaluation
Optimization with Optimo
Optimizationwith Refinery
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Optimization with Optimo
POPULATION (= initial set of solutions)
Shape
GENOTYPE
Parameters
FITNESS FUNCTION
Evaluation
PHENOTYPE
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Objectives:
▪ Non-Rectangularity Ratio (# elements)
▪ Non-Planarity Ratio
Design Variables:
▪ X-Y relative positions for the 4 anchor points
▪ Ax, Ay, Bx,… Dy.
Design Variables within a range:
▪ -5 ≤ X,Y ≤ 5
Representation of Optimization Problem
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Optimization using Genetic AlgorithmsEVOLUTION
Parent Solution
#1
“Dad”
Evaluation
Insert to the population
Selection
Parental Solution
#2
“Mom”
Child Solution
“Baby Catenary”
Ite
rate
Ge
ne
rati
on
s
Cross Over
Mutation
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Optimization with OptimoAutodesk® Dynamo Studio
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Optimized ResultsAutodesk® Dynamo Studio
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▪ Connects with Dynamo 2.0
▪ Design Exploration software
▪ Optioneering and Optimization workflows
▪ Advanced results display
▪ Syncing selected option back to Dynamo
▪ Request access through this link:
https://beta.autodesk.com/key/refinery
Preview: Optimization with RefineryDynamo Core 2.0 & Refinery
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Preview: Optimization with RefineryDynamo Core 2.0 & Refinery
CONCLUSION
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▪ Ian Keough and the Dynamo development team, for the great visual programming tool.
▪ The EPFL Computer Graphics Lab and Geometry Lab, for developing the important theoretical
framework, which DynaShape is based on.
▪ Daniel Piker, for playing a major role in popularizing physics and constraint-based digital form
finding in the design community.
▪ Autodesk (particularly Phil Mueller and Matt Jezyk) for co-organizing and co-sponsoring AEC
Hackathon Munich 2017, where DynaShape was born.
Acknowledgements
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▪ Give feedback after each session.
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How did we do ?
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