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Structural stochastic identification considering modeling uncertainty through sparse grid and similar system analysis

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This article is published in Structural and Multidisciplinary Optimization.The article was published on 2022-08-01. It has received 1 citations till now. The article focuses on the topics: Inverse problem & Inverse.

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A multiple-data-based direct method for inverse problem in three-dimensional linear elasticity

TL;DR: In this paper , a multiple-data-based direct (MD) method is proposed to solve this inverse problem without iterations, which applies a global normalized objective function and a global regularization coefficient τg for energy-like regularization to ensure the convergence of the unknown displacement boundary conditions.
References
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Journal ArticleDOI

A stochastic collocation approach to Bayesian inference in inverse problems

TL;DR: In this paper, a generalized polynomial chaos (gPC) based forward solver for inverse problems is proposed. But the convergence rate of the forward solution is not known.
Book

Computational Inverse Techniques in Nondestructive Evaluation

TL;DR: In this article, Tikhonov et al. proposed an approach towards a total solution in inverse problems in structural systems using GAs for solving Inverse Problems in Structural Systems.
Journal ArticleDOI

A Bayesian inference approach to the inverse heat conduction problem

TL;DR: In this article, a Bayesian inference approach is presented for the solution of the inverse heat conduction problem, where the posterior probability density function (PPDF) of the boundary heat flux is computed given temperature measurements within a conducting solid.
Journal ArticleDOI

Hierarchical Bayesian model updating for structural identification

TL;DR: In this paper, a probabilistic finite element (FE) model updating technique based on Hierarchical Bayesian modeling is proposed for identification of civil structural systems under changing ambient/environmental conditions.
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