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Stress-based topology optimization using bi-directional evolutionary structural optimization method

机译:基于双向演化结构优化方法的基于应力的拓扑优化

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摘要

This work proposes an evolutionary topology optimization method for stress minimization design using the bi-directional evolutionary structural optimization (BESO) method. The discrete nature of the BESO method avoids naturally the well-known "singularity" problem in density-based methods with degenerated materials. The p-norm stress aggregation scheme is adopted for the measure of global stress level. A computationally efficient sensitivity number formulation is derived from the adjoint sensitivity of the global stress measure. With regard to the highly nonlinear stress behavior, both sensitivity numbers and topology variables are filtered to stabilize the optimization procedure; meanwhile, the filtered sensitivity numbers are further stabilized with their historical information. The method has been shown efficient, practical and easy-to-implement through a series of 2D and 3D benchmark designs. (C) 2018 Elsevier B.V. All rights reserved.
机译:这项工作提出了一种使用双向演化结构优化(BESO)方法进行应力最小化的演化拓扑优化方法。 BESO方法的离散性质自然避免了使用退化材料的基于密度的方法中众所周知的“奇异性”问题。采用p范数应力聚集方案来度量整体应力水平。从整体应力测度的伴随灵敏度中得出了计算有效的灵敏度数公式。对于高度非线性的应力行为,对敏感度数和拓扑变量均进行了过滤以稳定优化过程。同时,过滤后的敏感度数字将通过其历史信息进一步稳定。通过一系列2D和3D基准测试设计,该方法被证明是高效,实用和易于实现的。 (C)2018 Elsevier B.V.保留所有权利。

著录项

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  • 作者单位

    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Topology optimization; BESO; Stress minimization; Sensitivity analysis;

    机译:拓扑优化;BESO;应力最小化;灵敏度分析;

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