Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5471204 | Applied Mathematical Modelling | 2017 | 17 Pages |
Abstract
This paper proposes a new hybrid uncertain design optimization method for structures which contain both random and interval variables simultaneously. The optimization model is formulated with the feasible robustness and the reliability of the worst scenario. The hybrid uncertainty is quantified by using the orthogonal series expansion method that integrates the Polynomial Chaos (PC) expansion method and the Chebyshev interval method within a uniform framework. The design sensitivity of objective and constraints will be developed to greatly facilitate the use of gradient-based optimization algorithms. The numerical results show that this method will be more possible to seek the feasible solution.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Wu Jinglai, Luo Zhen, Li Hao, Zhang Nong,