On the use of artificial neural networks in topology optimisation
RV Woldseth, N Aage, JA Bærentzen… - Structural and …, 2022 - Springer
The question of how methods from the field of artificial intelligence can help improve the
conventional frameworks for topology optimisation has received increasing attention over …
conventional frameworks for topology optimisation has received increasing attention over …
Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics
Three recent breakthroughs due to AI in arts and science serve as motivation: An award
winning digital image, protein folding, fast matrix multiplication. Many recent developments …
winning digital image, protein folding, fast matrix multiplication. Many recent developments …
Topology optimization via implicit neural representations
Along with the rapid development of artificial intelligence (AI) technology, scientific research
enters a new era of AI. Topology optimization (TO) and AI technology are recently showing a …
enters a new era of AI. Topology optimization (TO) and AI technology are recently showing a …
Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing Guided Design
A Vadillo Morillas, J Meneses Alonso… - Inventions, 2024 - mdpi.com
CAD-CAE software companies have introduced numerous tools aimed at facilitating
topology optimization through Finite Element Simulation, thereby enhancing accessibility for …
topology optimization through Finite Element Simulation, thereby enhancing accessibility for …
On neural networks for generating better local optima in topology optimization
L Herrmann, O Sigmund, VM Li, C Vogl… - Structural and …, 2024 - Springer
Neural networks have recently been employed as material discretizations within adjoint
optimization frameworks for inverse problems and topology optimization. While …
optimization frameworks for inverse problems and topology optimization. While …
Problem-independent machine learning-enhanced structural topology optimization of complex design domains based on isoparametric elements
Topology optimization requires dozens or even hundreds of iterations, each requiring a
complete finite element analysis (FEA). Significant computation cost limits the application of …
complete finite element analysis (FEA). Significant computation cost limits the application of …
[HTML][HTML] 深度学习赋能结构拓扑优化设计方法研究
陈小前， 张泽雨， 李昱， 姚雯， 周炜恩 - 力学进展, 2024 - lxjz.cstam.org.cn
本文综合论述了近年来结构拓扑优化领域与深度学习技术交叉融合发展的相关研究进展.
围绕结构拓扑优化设计的核心方法与关键环节, 以深度学习赋能的角度系统性梳理了两大类赋能 …
围绕结构拓扑优化设计的核心方法与关键环节, 以深度学习赋能的角度系统性梳理了两大类赋能 …
[HTML][HTML] Research on structure topology optimization design empowered by deep learning method
C Xiaoqian, Z Zeyu, LI Yu, YAO Wen, Z Weien - 力学进展, 2024 - lxjz.cstam.org.cn
This article comprehensively discusses the relevant research progress in the field of
structural topology optimization and the cross-integration development of deep learning …
structural topology optimization and the cross-integration development of deep learning …
Wasserstein generative adversarial networks for topology optimization
L Pereira, L Driemeier - Structures, 2024 - Elsevier
The finite element method (FEM) is a well known approach to solve partial differential
equations. It has important applications in structural engineering, such as in topology …
equations. It has important applications in structural engineering, such as in topology …
Taming Connectedness in Machine-Learning-Based Topology Optimization with Connectivity Graphs
MM Behzadi, J Chen, HT Ilies - Computer-Aided Design, 2024 - Elsevier
Despite the remarkable advancements in machine learning (ML) techniques for topology
optimization, the predicted solutions often overlook the necessary structural connectivity …
optimization, the predicted solutions often overlook the necessary structural connectivity …