1. A sub-domain method for solving stochastic problems with large uncertainties and repeated eigenvalues
- Author
-
Xiang Zhihai, Cen Zhangzhi, Fan Lijia, and Xue Mingde
- Subjects
Continuous-time stochastic process ,Mathematical optimization ,Applied Mathematics ,Monte Carlo method ,Biomedical Engineering ,Perturbation (astronomy) ,Computational Theory and Mathematics ,Modeling and Simulation ,Stochastic optimization ,Molecular Biology ,Random variable ,Stochastic finite element method ,Software ,Eigenvalues and eigenvectors ,Mathematics - Abstract
The traditional perturbation-based stochastic finite element method has the inherent limitation of requiring small uncertainties to ensure reliable results. To overcome this limitation, this paper presents a new method that redefines the stochastic problem into some sub-domains of random variables. Then, the stochastic structural responses defined in the global domain can be explicitly reconstructed from the responses obtained in each sub-domain. In this way, the uncertainties of random variables could be relatively large to achieve the acceptable accuracy. In addition, this method is also able to deal with stochastic problems with repeated eigenvalues. Numerical examples are presented to illustrate the validity and capability of this new method by comparing the results with ones from Monte Carlo simulations. Copyright © 2009 John Wiley & Sons, Ltd.
- Published
- 2009