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 simulationProposing a generative design workflow that integrates a stochastic…
2023
Advancing Construction Processes with Industry CollaborationLearn how Autodesk Research and Howick are collaborating to push the…
2023
Autodesk Research Celebrates Earth Day, Every DayA round up of recent posts from the Research Blog highlighting our…
2018
Generative Urban Design: Integration of financial and energy design goals in a generative design workflow for residential neighborhood layoutThis paper demonstrates an application of Generative Design to an…
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