A polynomial dimensional decomposition-based method for robust topology optimization

• Published in: Structural and multidisciplinary optimization Vol. 64; no. 6; pp. 3527 - 3548
• Main Authors: Ren, Xuchun, Zhang, Xiaodong
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021; Springer Nature B.V
• Subjects: Approximation; Civil engineering; Computational Mathematics and Numerical Analysis; Decomposition; Derivatives; Design optimization; Engineering; Engineering Design; Mathematical analysis; Methods; Polynomials; Probability; Random variables; Reaction-diffusion equations; Research Paper; Response functions; Robustness; Sensitivity analysis; Theoretical and Applied Mechanics; Topology optimization; Topology optimization; Stochastic moments; Topology derivatives; Polynomial dimensional decomposition; Robust design
• ISSN: 1615-147X; 1615-1488
• DOI: 10.1007/s00158-021-03036-5

This paper implements a novel integration of the polynomial dimensional decomposition (PDD), topology derivative, and level-set method for robust topology optimization subject to a large number of random inputs. With this method, the influence of a large number of random inputs can be easily capture...