As part of AAG2020, we participated in the very well conducted workshop “Structural Form-Finding through Machine Learning“, led by Pierluigi D’Acunto, Vahid Moosavi, Catherine Rankine, Vincenzo Reale and Federico Bertagna.


Some pictures of the process developed :

Here is a description of the subjects developed during these two days :

The aim of this workshop is to introduce the participants to a novel design method for the form-finding of equilibrated structures in three-dimensions based on computational methods for structural design, like the Force Density Method (FDM) and the Combinatorial Equilibrium Modelling (CEM). The FDM is a powerful form-finding approach that allows designing complex spatial structures in equilibrium, such as tension-only or compression-only surface structures. The CEM is an innovative geometry-based approach to structural design that is grounded on vector-based 3D graphic statics and graph theory, and which is particularly tailored for the design of mixed tension-compression structures. The design process will be supported by the use of Machine Learning (ML) algorithms, such as Self Organising Map (SOM) for clustering, Gradient Boosted Trees (GBT) for classification, and Convolutional Neural Network (CNN) for deep learning. These algorithms will be used to guide the exploration of the design space generated by the FDM or the CEM.The workshops will open up new perspectives in the design of structures in static equilibrium, by enabling the participants to take full advantage of the relationship between topology, geometry, and structural behaviour starting from the early stages of the design process. To make this approach operative, a series of interactive, computer-aided design tools within the 3D software environment McNeel Rhinoceros and Grasshopper will be introduced. The tools enable the designers to work inreal-time and in an intuitive way to generate non-conventional 3D spatial networks in equilibrium for any designer-specified connectivity, any combination of compression and tension forces, and any set of force magnitudes.

During the first workshop day, the theoretical background of FDM and CEM will be introduced, including some basic elements of graphic statics and graph theory, as well as important concepts from ML algorithms, which are relevant for structural design. Afterwards, the main functionalities of the related computer-aided design tools within the 3D software environment McNeel Rhinoceros and Grasshopper will be demonstrated via simple exercises. During the second day, participants will beasked to develop an individual design exercise to get familiar with the FDM, the CEM, and ML and the related design tools. Participants will develop their proposals with help from tutors. In this phase, advanced coding tutorials with Python will be provided to address specific design-related questions of the participants. Furthermore, the participants will be asked to build simple physical models to illustrate the structural concept of their proposals.


Here is a bibliography to go further on these subjects:

Ohlbrock, Patrick Ole, Pierluigi D’Acunto, and Jean-Philippe Jasienski. 2018. “Hierarchical Form-Finding with Combinatorial Equilibrium Modelling,” 4.
Zheng, Hao, Vahid Moosavi, and Masoud Akbarzadeh. 2020. “Machine Learning Assisted Evaluations in Structural Design and Construction.” Automation in Construction 119: 103346.
D’Acunto, Pierluigi, Jean-Philippe Jasienski, Patrick Ole Ohlbrock, Corentin Fivet, Joseph Schwartz, and Denis Zastavni. 2019. “Vector-Based 3D Graphic Statics: A Framework for the Design of Spatial Structures Based on the Relation between Form and Forces.” International Journal of Solids and Structures 167: 58–70.
D’Acunto, Pierluigi, Jean-Philippe Jasienski, Patrick Ole Ohlbrock, and Corentin Fivet. 2017. “Vector-Based 3D Graphic Statics: Transformations of Force Diagrams,” 10.
Fuhrimann, Lukas, Vahid Moosavi, Patrick Ole Ohlbrock, and Pierluigi D’Acunto. 2018. “Data-Driven Design: Exploring New Structural Forms,” 8.
Ochoa, Karla Saldana, Patrick Ole Ohlbrock, Pierluigi D’Acunto, and Vahid Moosavi. n.d. “Beyond Typologies, beyond Optimization: Exploring Novel Structural Forms at the Interface of Human and Machine Intelligence.” International Journal of Architectural Computing, 25.
Ohlbrock, Patrick Ole, and Pierluigi D’Acunto. 2020. “A Computer-Aided Approach to Equilibrium Design Based on Graphic Statics and Combinatorial Variations✩,” 19.
Bertagna, Federico, Pierluigi D’Acunto, Patrick Ole Ohlbrock, and Vahid Moosavi. 2021. “Holistic Design Explorations of Building Envelopes Supported by Machine Learning.” Journal of Facade Design and Engineering, April, 31-46 Pages.



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