arrow
返回

An adaptive high-order piecewise polynomial based sparse grid collocation method with applications

delete2021-05-01
delete4
delete
OA
AI
Z
Zhanjing Tao
Y
Yan Jiang *
Y
Yingda Cheng
DOI:10.1016/j.jcp.2020.109770delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
This paper constructs adaptive sparse grid collocation method onto arbitrary order piecewise polynomial space. The sparse grid method is a popular technique for high dimensional problems, and the associated collocation method has been well studied in the literature. The contribution of this work is the introduction of a systematic framework for collocation onto high-order piecewise polynomial space that is allowed to be discontinuous. We consider both Lagrange and Hermite interpolation methods on nested collocation points. Our construction includes a wide range of function space, including those used in sparse grid continuous finite element method. Error estimates are provided, and the numerical results in function interpolation, integration and some benchmark problems in uncertainty quantification are used to compare different collocation schemes. (C) 2020 Elsevier Inc. All rights reserved.
Keyword:
High-dimensional model
Adaptive sparse grid
Piecewise polynomial
Collocation method
Multiresolution analysis
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Journal of Computational Physics 封面图
Journal of Computational Physics
IF:
3.8
论文数:
1.6W
被引数:
7.4W

机构

U
university of science & technology of china, cas
学者数:
3.2W
论文数: 2.7W
被引数: 74
J
Jilin University
学者数:
8.7W
论文数: 5.6W
被引数: 8.9K
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
学者 查看更多机构
引用论文

引用论文

Granite Disintegration, Panola Mountain, Georgia
err1980-05-01
err0
PREAI
errJay Van Tassell; Willard H. Grant
err分享
err收藏
Stochastic collocation approach with adaptive mesh refinement for parametric uncertainty analysis
err2018-10-01
err25
errOAAI
errBhaduri, Anindya; He, Yanyan; Shields, Michael D.; Graham-Brady, Lori; Kirby, Robert M.
err分享
err收藏
err分享
err收藏
err分享
err收藏
学者 查看更多内容