Publication | Design Modeling Symposium 2017
Nature-based Hybrid Computational Geometry System for Optimizing Component Structure
Abstract
Nature-based Hybrid Computational Geometry System for Optimizing Component Structure
Danil Nagy, Dale Zhao, David Benjamin
Design Modeling Symposium 2017
This paper describes a novel computational geometry system developed for application in the design of full-scale industrial components. This system combines a bottom-up growth strategy based on slime mold behaviour in nature with a top-down genetic algorithm strategy for optimization. The growth strategy uses an agent-based algorithm to create individual instances of designs based on a small number of input parameters. These parameters can then be controlled by a genetic algorithm to optimize the final design according to goals such as minimizing weight and minimizing structural weakness. Together, these two strategies create a hybrid approach which ensures high performance while allowing the designer to explore a wider range of novel designs than would be possible using traditional design methods.
Download publicationAssociated Autodesk Researchers
Related Resources
2023
Generative design for COVID-19 and future pathogens using stochastic multi-agent simulation
Proposing a generative design workflow that integrates a stochastic…
2023
Advancing Construction Processes with Industry Collaboration
Learn how Autodesk Research and Howick are collaborating to push the…
2015
Hy-Fi
A building project to test and refine a new low-energy biological…
2019
Project Discover: Workflow for Generative Design in Architecture
This project involves the integration of a rule-based geometric…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us