Identification of Flexural Rigidity in a Kirchhoff Plates Model Using a Convex Objective and Continuous Newton Method

Author:

Jadamba B.1,Kahler R.1,Khan A. A.1,Raciti F.2,Winkler B.3

Affiliation:

1. Center for Applied and Computational Mathematics, School of Mathematical Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, NY 14623, USA

2. Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy

3. Institute of Mathematics, Martin Luther University of Halle-Wittenberg, 06120 Halle (Saale), Germany

Abstract

This work provides a detailed theoretical and numerical study of the inverse problem of identifying flexural rigidity in Kirchhoff plate models. From a mathematical standpoint, this inverse problem requires estimating a variable coefficient in a fourth-order boundary value problem. This inverse problem and related estimation problems associated with general plates and shell models have been investigated by numerous researchers through an optimization framework using the output least-squares (OLSs) formulation. OLS yields a nonconvex framework and hence it is suitable for investigating only the local behavior of the solution. In this work, we propose a new convex framework for the inverse problem of identifying a variable parameter in a fourth-order inverse problem. Existence results, optimality conditions, and discretization issues are discussed in detail. The discrete inverse problem is solved by using a continuous Newton method. Numerical results show the feasibility of the proposed framework.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A new regularized stochastic approximation framework for stochastic inverse problems;Nonlinear Analysis: Real World Applications;2023-10

2. Spectral Optimization of Inhomogeneous Plates;SIAM Journal on Control and Optimization;2023-04-28

3. A Variational Inequality Based Stochastic Approximation for Inverse Problems in Stochastic Partial Differential Equations;Springer Optimization and Its Applications;2020-09-30

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