.png){kind=icon}
返回
Numerical strategy for model correction using physical constraints
.png){kind=icon}
OA
AI
DOI：10.1016/j.jcp.2016.02.054.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we present a strategy for correcting model deficiency using observational data. We first present the model correction in a general form, involving both external correction and internal correction. The model correction problem is then parameterized and casted into an optimization problem, from which the parameters are determined. More importantly, we discuss the incorporation of physical constraints from the underlying physical problem. Several representative examples are presented, where the physical constraints take very different forms. Numerical tests demonstrate that the physics constrained model correction is an effective way to address model-form uncertainty. (C) 2016 Elsevier Inc. All rights reserved.
Keyword:
Uncertainty quantification
Model-form uncertainty
Model correction
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
IF:
3.8
论文数:
1.6W
被引数:
7.4W
机构
暂无机构信息
引用论文
分享收藏LCA and Sustainability Assessment for Selecting Deep Foundation System for High-Rise Buildings.png)
ICSI 2014
ICSI 2014IF0
PREAI
分享收藏The Wiener-Askey polynomial chaos for stochastic differential equations随机微分方程的wiener-askey多项式混沌
PREAI
分享收藏 没有更多内容
没有更多内容