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
2024
Autodesk Research’s Kean Walmsley Joins Industry PodcastKean Walmsley shares insights gathered over his 20-year plus,…
2023
Using AI to Optimize Construction DesignHow can we leverage AI to make construction design processes more…
2020
Learning to Simulate and Design for Structural EngineeringThe structural design process for buildings is time consuming and…
2017
Survey-Based Simulation of User Satisfaction for Generative Design in ArchitectureThis paper describes a novel humanist approach to generative design…
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