arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2201.00004math.OC
收藏

随机场材料模型下的鲁棒可靠性拓扑optimization

Robust reliability-based topology optimization under random-field material model

Trung Pham, Christopher Hoyle

摘要:

提出了一种在随机场材料模型下基于可靠性的鲁棒拓扑优化设计算法。初始设计域由线性弹性材料制成,其性质,即,杨氏模量由随机场模拟。为了便于计算,Karhunen-Loève展开将建模随机场离散为少量随机变量。鲁棒性通过优化感兴趣的量的平均值和标准差的加权和来实现,而可靠性通过概率约束来使用。为了减少计算量,采用了Sokerak型稀疏网格和随机响应面法。此外,一个有效的逆可靠性算法被用来解耦的双环结构的可靠性分析。该算法在文献中的两个常见的基准问题进行了测试。最后,通过蒙特卡罗仿真验证了优化设计的鲁棒性和可靠性。

英文摘要:

This paper proposes an algorithm to find robust reliability-based topology optimized designs under a random-field material model. The initial design domain is made of linear elastic material whose property, i.e., Young's modulus, is modeled by a random field. To facilitate computation, the Karhunen-Loève expansion discretizes the modeling random field into a small number of random variables. Robustness is achieved by optimizing a weighted sum of mean and standard deviation of a quantity of interest, while reliability is employed through a probabilistic constraint. The Smolyak-type sparse grid and the stochastic response surface method are applied to reduce computational cost. Furthermore, an efficient inverse-reliability algorithm is utilized to decouple the double-loop structure of reliability analysis. The proposed algorithm is tested on two common benchmark problems in literature. Finally, Monte Carlo simulation is used to validate the claimed robustness and reliability of optimized designs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑