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Convex modeling based topology optimization under load uncertainty.

机译：负载不确定性下基于凸模型的拓扑优化。

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摘要

In traditional topology optimization formulation the external load are deterministic and the uncertainties are not considered. The convex modeling based topology optimization method for solving topology optimization problems under external load uncertainties is presented in this dissertation. The load uncertainties are formulated using the non-probabilistic based unknown-but-bounded convex model. The sensitivities are derived and the problem is solved using gradient based algorithm. The proposed convex modeling based method yields the material distribution which would optimize the worst structure response under the uncertain loads. Comparing to the deterministic based topology optimization formulation, the proposed method provided more reliable solutions when load uncertainties were involved. The proposed method can work with other method to solved complicated design problems. A protective structure design problem involving load uncertainties, multiple design objectives and unconstrained structure is solved by integrating the convex modeling based topology optimization method with regional strain energy formulation and inertial relief method. The simplicity, efficiency and versatility of the proposed convex modeling based method can be considered as a supplement to the sophisticated probabilistic based topology optimization methods.
机译：在传统的拓扑优化公式中，外部负载是确定性的，没有考虑不确定性。本文提出了一种基于凸模型的拓扑优化方法，用于解决外部载荷不确定性下的拓扑优化问题。负载不确定性使用基于非概率的未知但有界凸模型来表示。得出灵敏度并使用基于梯度的算法解决问题。所提出的基于凸模型的方法产生了材料分布，该材料分布将在不确定载荷下优化最差的结构响应。与基于确定性的拓扑优化公式相比，该方法在涉及负载不确定性时提供了更可靠的解决方案。所提出的方法可以与其他方法一起解决复杂的设计问题。通过将基于凸模型的拓扑优化方法与区域应变能公式化和惯性释放方法相结合，解决了涉及荷载不确定性，多个设计目标和无约束结构的防护结构设计问题。所提出的基于凸建模的方法的简单性，效率和多功能性可以被视为对复杂的基于概率的拓扑优化方法的补充。

著录项

  • 作者

    Zhao, Xike.;

  • 作者单位

    Rutgers The State University of New Jersey - New Brunswick.;

  • 授予单位 Rutgers The State University of New Jersey - New Brunswick.;
  • 学科 Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 99 p.
  • 总页数 99
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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