Universal machine learning for topology optimization

DOI10.1016/j.cma.2019.112739zbMath1506.74267OpenAlexW3114517772MaRDI QIDQ2022034

Tsz Ling Elaine Tang, Livio Dalloro, Heng Chi, Le Song, Lucia Mirabella, Yu-Yu Zhang, Glaucio H. Paulino

Publication date: 27 April 2021

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2019.112739

Mathematics Subject Classification ID

Topological methods for optimization problems in solid mechanics (74P15)

Related Items

Learning finite element convergence with the multi-fidelity graph neural network, A phase field-based systematic multiscale topology optimization method for porous structures design, Machine learning for topology optimization: physics-based learning through an independent training strategy, Robust, strong form mechanics on an adaptive structured grid: efficiently solving variable-geometry near-singular problems with diffuse interfaces, Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties, \texttt{DL4TO}: a deep learning library for sample-efficient topology optimization, Material Design with Topology Optimization Based on the Neural Network, TONR: an exploration for a novel way combining neural network with topology optimization, De-homogenization using convolutional neural networks, A phase field method based on multi-level correction for eigenvalue topology optimization, Level set-based topology optimization for thermal-fluid system based on the radial basis functions

Uses Software

• PETSc
• PolyTop
• ElemStatLearn
• ImageNet
• Adam
• AlexNet

Cites Work

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