Nonlinear conjugate gradient method for identifying Young's modulus of the elasticity imaging inverse problem

IF 1.1 4区 工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY Inverse Problems in Science and Engineering Pub Date : 2021-04-02 DOI:10.1080/17415977.2021.1905638
Talaat Abdelhamid, Rongliang Chen, M. Alam
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引用次数: 2

Abstract

Application of elasticity imaging inverse problem to identify Young's modulus in the elasticity problems in human's life is an interesting research area. In this study, we identify the modulus of elasticity for solving elasticity imaging inverse problem using a modified output least-squares method. Numerical convergence in the displacements of the direct problem for elasticity is investigated. To study the elasticity imaging inverse problem in an optimization framework, we utilize the sensitivity and adjoint problems to conceptualize a new model for computing the gradient of the minimizer. Discrete formulae in the model are then used to devise a scheme for an efficient computation gradient of the modified output least-squares objective function using the nonlinear conjugate gradient method. Numerical experiments demonstrate the effectiveness of the proposed technique.
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弹性成像反问题杨氏模量的非线性共轭梯度辨识方法
应用弹性成像逆问题来识别杨氏模量在人类生活中的弹性问题中是一个有趣的研究领域。在这项研究中,我们使用一种改进的输出最小二乘法来确定弹性成像逆问题的弹性模量。研究了弹性力学直接问题位移的数值收敛性。为了在优化框架下研究弹性成像逆问题,我们利用灵敏度和伴随问题来概念化一个计算极小值梯度的新模型。然后,使用模型中的离散公式,使用非线性共轭梯度方法,设计了一种有效计算修正输出最小二乘目标函数梯度的方案。数值实验证明了该方法的有效性。
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来源期刊
Inverse Problems in Science and Engineering
Inverse Problems in Science and Engineering 工程技术-工程:综合
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审稿时长
6 months
期刊介绍: Inverse Problems in Science and Engineering provides an international forum for the discussion of conceptual ideas and methods for the practical solution of applied inverse problems. The Journal aims to address the needs of practising engineers, mathematicians and researchers and to serve as a focal point for the quick communication of ideas. Papers must provide several non-trivial examples of practical applications. Multidisciplinary applied papers are particularly welcome. Topics include: -Shape design: determination of shape, size and location of domains (shape identification or optimization in acoustics, aerodynamics, electromagnets, etc; detection of voids and cracks). -Material properties: determination of physical properties of media. -Boundary values/initial values: identification of the proper boundary conditions and/or initial conditions (tomographic problems involving X-rays, ultrasonics, optics, thermal sources etc; determination of thermal, stress/strain, electromagnetic, fluid flow etc. boundary conditions on inaccessible boundaries; determination of initial chemical composition, etc.). -Forces and sources: determination of the unknown external forces or inputs acting on a domain (structural dynamic modification and reconstruction) and internal concentrated and distributed sources/sinks (sources of heat, noise, electromagnetic radiation, etc.). -Governing equations: inference of analytic forms of partial and/or integral equations governing the variation of measured field quantities.
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