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A Comparison of Deterministic, Reliability-Based Topology Optimization under Uncertainties

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Abstract

Reliability and optimization are two key elements for structural design. The reliability-based topology optimization (RBTO) is a powerful and promising methodology for finding the optimum topologies with the uncertainties being explicitly considered, typically manifested by the use of reliability constraints. Generally, a direct integration of reliability concept and topology optimization may lead to computational difficulties. In view of this fact, three methodologies have been presented in this study, including the double-loop approach (the performance measure approach, PMA) and the decoupled approaches (the so-called Hybrid method and the sequential optimization and reliability assessment, SORA). For reliability analysis, the stochastic response surface method (SRSM) was applied, combining with the design of experiments generated by the sparse grid method, which has been proven as an effective and special discretization technique. The methodologies were investigated with three numerical examples considering the uncertainties including material properties and external loads. The optimal topologies obtained using the deterministic, RBTOs were compared with one another; and useful conclusions regarding validity, accuracy and efficiency were drawn.

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Authors and Affiliations

  1. Collaborative Innovation Center of Electric Vehicles in Beijing, School of Mechanical Engineering, Beijing Institute of Technology, 100081, Beijing, China

    Qinghai Zhao & Xiaokai Chen

  2. Department of Mechanical Engineering, University of Michigan, 48105, MI, USA

    Zhengdong Ma

  3. Beijing Automotive Technology Center, 100081, Beijing, China

    Yi Lin

Authors
  1. Qinghai Zhao
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  2. Xiaokai Chen
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  3. Zhengdong Ma
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  4. Yi Lin
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Corresponding author

Correspondence to Xiaokai Chen.

Additional information

Project supported by the National Natural Science Foundation of China (Nos. 51275040 and 50905017), and the Programme of Introducing Talents of Discipline to Universities (No. B12022). The authors are also grateful to Krister Svanberg for providing his implementation of the MMA algorithm.

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Zhao, Q., Chen, X., Ma, Z. et al. A Comparison of Deterministic, Reliability-Based Topology Optimization under Uncertainties. Acta Mech. Solida Sin. 29, 31–45 (2016). https://doi.org/10.1016/S0894-9166(16)60005-8

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  • DOI: https://doi.org/10.1016/S0894-9166(16)60005-8

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