Shape reconstruction in transient heat conduction problems based on radial integration boundary element method

被引:12
|
作者
Jiang, Geng-Hui [1 ]
Tan, Chen-Hao [2 ]
Jiang, Wen-Wei [2 ]
Yang, Kai [2 ]
Wang, Wei-Zhe [1 ]
Gao, Xiao-Wei [2 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech & Power Engn, Key Lab Power Machinery & Engn, Shanghai 200240, Peoples R China
[2] Dalian Univ Technol, State Key Lab Struct Anal Ind Equipment, Key Lab Adv Technol Aerosp Vehicles, Dalian 116024, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Shape reconstruction; Transient heat conduction problems; Radial integration boundary element method; Complex variable derivation method; LEVENBERG-MARQUARDT ALGORITHM; DOMAIN INTEGRALS; CONJUGATE-GRADIENT; INVERSE; OPTIMIZATION; GEOMETRY; DESIGN; BEM; BODY; IDENTIFICATION;
D O I
10.1016/j.ijheatmasstransfer.2022.122830
中图分类号
O414.1 [热力学];
学科分类号
摘要
In order to accurately identify the geometric boundary, the radial integration boundary element method (RIBEM) combined with the modified Levenberg-Marquardt (LM) algorithm is proposed for shape reconstruction in transient heat conduction problems. Compared with the finite element method (FEM), the boundary element method (BEM) only discretizes the boundary rather than the whole domain, so it has incomparable advantages in the shape reconstruction. Especially, the radial integration method still maintains the superiority of boundary discretization in transient heat conduction problems. For the iterative scheme of LM algorithm, the shape reconstruction greatly depends on whether the sensitivity matrix can be obtained accurately. Therefore, complex variable derivation method (CVDM) is firstly introduced to carry out shape reconstruction in the transient heat conduction problems, which accurately solves the sensitivity coefficients of node temperature to the reconstructed boundary, and the RIBEM is transformed from the real domain to the complex domain to solve the transient heat conduction problems. The modified LM algorithm effectively overcomes the shortcoming of the excessive dependence on the step size of finite difference scheme. It should be noted that compared with the finite difference scheme, the proposed method can greatly reduce the computational cost of the direct problem in the multi-variate optimization process, thereby greatly improving the efficiency of identifying the boundary shape. Finally, different reconstruction strategies are applied in numerical models with three types of variable boundary, and reconstruction results demonstrate the great accuracy and efficiency of the proposed method in 2D and 3D shape reconstruction, and it also shows good robustness in the presence of measurement errors.(c) 2022 Elsevier Ltd. All rights reserved.
引用
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页数:12
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