首页> 外文期刊>Mathematics and computers in simulation >A Monte Carlo approach to computing stiffness matrices arising in polynomial chaos approximations
【24h】

A Monte Carlo approach to computing stiffness matrices arising in polynomial chaos approximations

机译:用于计算多项式混沌逼近中的刚度矩阵的蒙特卡洛方法

获取原文
获取原文并翻译 | 示例

摘要

We use a Monte Carlo method to assemble finite element matrices for polynomial Chaos approximations of elliptic equations with random coefficients. In this approach, all expectations are approximated by a Monte Carlo method. The resulting methodology requires dealing with sparse block-diagonal matrices instead of block-full matrices. This leads to the solution of a coupled system of elliptic equations where the coupling is given by a Kronecker product matrix involving polynomial evaluation matrices. This generalizes the Classical Monte Carlo approximation and Collocation method for approximating functionals of solutions of these equations. (C) 2018 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
机译:我们使用蒙特卡洛方法组装有限元矩阵,以求解具有随机系数的椭圆方程的多项式混沌逼近。在这种方法中,所有期望值均通过蒙特卡洛方法进行近似。最终的方法需要处理稀疏的块对角矩阵,而不是块完整的矩阵。这导致了椭圆方程耦合系统的解,其中耦合由涉及多项式评估矩阵的克罗内克乘积矩阵给出。这概括了经典的蒙特卡洛近似和并置方法,以近似这些方程的解的泛函。 (C)2018国际模拟数学与计算机协会(IMACS)。由Elsevier B.V.发布。保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
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