Article
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Fail-Safe Topology Optimization Using Damage Scenarios Filtering
Version 1
: Received: 26 December 2023 / Approved: 26 December 2023 / Online: 26 December 2023 (09:47:39 CET)
A peer-reviewed article of this Preprint also exists.
Sun, W.; Zhang, Y.; Liu, Y.; Cheng, K.; Cheng, F. Fail-Safe Topology Optimization Using Damage Scenario Filtering. Appl. Sci. 2024, 14, 878. Sun, W.; Zhang, Y.; Liu, Y.; Cheng, K.; Cheng, F. Fail-Safe Topology Optimization Using Damage Scenario Filtering. Appl. Sci. 2024, 14, 878.
Abstract
This paper presents an efficient topology optimization approach considering fail-safe requirements in the framework of the solid isotropic material with penalization method. Existing methods either are computationally extremely expensive or do not consider fail-safe requirements in the optimization. The current approach not only obtains the fail-safe optimization structure, but also significantly improves the computational efficiency of fail-safe topology optimization. In this method, the worst-case compliance is considered to minimize as the optimization objective, using the Kreisselmeier–Steinhauser function to approximate the non-differentiable max-operator. The sensitivity is derived by the adjoint method, and a general fail-safe optimality criteria method is developed to update design variables. The damage scenarios greatly reduces in the process of failsafe strategy optimization by employing the density-based filter method. Finally, the effectiveness and computational efficiency of this method for fail-safe optimization is verified by several numerical examples.
Keywords
topology optimization; fail-safe design; dage scenarios filtering; snsitivity analysis
Subject
Engineering, Safety, Risk, Reliability and Quality
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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