...
首页> 外文期刊>Computers & structures >Combined parametric-nonparametric uncertainty quantification using random matrix theory and polynomial chaos expansion
【24h】

Combined parametric-nonparametric uncertainty quantification using random matrix theory and polynomial chaos expansion

机译:Combined parametric-nonparametric uncertainty quantification using random matrix theory and polynomial chaos expansion

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Propagation of combined parametric and nonparametric uncertainties in elliptic partial differential equations is considered. Two cases, namely, (a) both uncertainties are over the entire domain, and (b) different types of uncertainties are over non-overlapping subdomains are proposed. Parametric uncertainty is modelled by a random field and is discretised using the Karhunen-Loeve (KL) expansion. The nonparametric uncertainty is modelled by Wishart random matrix. Both uncertainties are considered independent, and the two first moments of the response are calculated using polynomial chaos expansion and analytical random matrix theory results. Closed-form analytical expressions of the first two moments are derived for both cases.

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号