On the existence of a global minimum in inverse parameters identification by Self-Optimizing inverse analysis method

被引：1

作者：

Yun, Gun Jin ^{[1
]}

Shang, Shen ^{[2
]}

机构：

[1] Seoul Natl Univ, Dept Mech & Aerosp Engn, Seoul 08826, South Korea

[2] AZZ WSI, 2225 Skyland Court, Norcross, GA 30071 USA

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2019年 / 77卷 / 03期

基金：

新加坡国家研究基金会;

关键词：

Parameter identification; Inverse problems; Self-Optimizing inverse analysis method; Anisotropic linear elasticity; Non-homogeneous materials; VIRTUAL FIELDS METHOD; MODEL; COMPOSITES; UNIQUENESS; STIFFNESS;

D O I：

10.1016/j.camwa.2018.10.019

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, a mathematical proof of the existence of a global minimum of Self-Optim (Self-Optimizing Inverse Analysis Method) cost functional is presented based upon weak-solution theory of partial differential equations. The Self-Optim provides single global minimum rather than having multiple global minima corresponding to unrealistic solutions of the inverse problem. Furthermore, discrete approximation of the inverse problem and computational methods for the cost functional are proposed and the proof is numerically verified. This paper provides a rigorous mathematical foundation for applications of the Self-Optim method to various inverse problems in mechanics. (C) 2018 Elsevier Ltd. All rights reserved.

引用

页码：803 / 814

页数：12

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