Sensitivity analysis for any functions of static elastic systems using combination of adjoint variable method and automatic differentiation for topology optimization

This study proposes a methodology to generalize and reduce the computational cost of sensitivity analysis for static linear elastic systems in topology optimization. The process is fully generalized by applying sensitivity analysis in conjunction with the adjoint variable method and automatic differentiation. The design sensitivities can be computed independently of any evaluation function and the material interpolation method for static elastic systems. Furthermore, the issue of excessive computational memory required by automatic differentiation is resolved by utilizing the adjoint variable method. To demonstrate the generality of the proposed method, we focus on multi-material topology optimization for isotropic linear elastic systems, evaluating compliance and maximum stress based on the Lp-norm. Additionally, the extended SIMP and Discrete Material Optimization (DMO) methods are investigated as interpolation schemes for material properties in multi-material problems. Finally, the finite difference method and automatic differentiation are benchmarked against other sensitivity analysis methods, and the proposed method is evaluated in terms of accuracy, computational cost, and memory usage. Moreover, examples of topology optimization for a 3-dimensional problem are presented to demonstrate the applicability of the proposed method to large-scale analyses.

Authors

Institutions

Publication Details

Journal
Transactions of the JSME (in Japanese)
Published
2024-12-22
DOI
https://doi.org/10.1299/transjsme.24-00225
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sensitivity analysis for any functions of static elastic systems using combination of adjoint variable method and automatic differentiation for topology optimization

Kazuo Yonekura, Shun Ogawa, Katsuyuki Suzuki
Transactions of the JSME (in Japanese)
Topology Optimization in Engineering
article

Sensitivity analysis for any functions of static elastic systems using combination of adjoint variable method and automatic differentiation for topology optimization

Kazuo Yonekura, Shun Ogawa, Katsuyuki Suzuki
article en

Abstract

This study proposes a methodology to generalize and reduce the computational cost of sensitivity analysis for static linear elastic systems in topology optimization. The process is fully generalized by applying sensitivity analysis in conjunction with the adjoint variable method and automatic differentiation. The design sensitivities can be computed independently of any evaluation function and the material interpolation method for static elastic systems. Furthermore, the issue of excessive computational memory required by automatic differentiation is resolved by utilizing the adjoint variable method. To demonstrate the generality of the proposed method, we focus on multi-material topology optimization for isotropic linear elastic systems, evaluating compliance and maximum stress based on the Lp-norm. Additionally, the extended SIMP and Discrete Material Optimization (DMO) methods are investigated as interpolation schemes for material properties in multi-material problems. Finally, the finite difference method and automatic differentiation are benchmarked against other sensitivity analysis methods, and the proposed method is evaluated in terms of accuracy, computational cost, and memory usage. Moreover, examples of topology optimization for a 3-dimensional problem are presented to demonstrate the applicability of the proposed method to large-scale analyses.

Transactions of the JSME (in Japanese)Vol. 91(941)
The University of Tokyo (JP)
Openalex Percentile: Top 73%
Topology Optimization in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.