scholarly journals Resolution of an inverse heat conduction problem with a nonlinear least square method in the Hankel space. Application to photothermal infrared thermography

2008 ◽  
Vol 135 ◽  
pp. 012061 ◽  
Author(s):  
D Legaie ◽  
H Pron ◽  
C Bissieux
Keyword(s):  
Heat Conduction ◽  
Infrared Thermography ◽  
Heat Conduction Problem ◽  
Least Square Method ◽  
Inverse Heat Conduction Problem ◽  
Least Square ◽  
Space Application ◽  
Inverse Heat Conduction

Solving the Inverse Heat Conduction Problem with Multi-Variables

2010 ◽  
Vol 168-170 ◽  
pp. 195-199
Author(s):  
Qi Wen Xue ◽  
Xiu Yun Du ◽  
Ga Ping Wang
Keyword(s):  
Sensitivity Analysis ◽  
Heat Conduction ◽  
Heat Conduction Problem ◽  
Inverse Heat Conduction Problem ◽  
Least Square ◽  
Inhomogeneous Distribution ◽  
Inverse Heat Conduction ◽  
Numerical Examples ◽  
Inverse Heat Conduction Problems ◽  
Direct Problems

This paper presents a general numerical model to solve non-linear inverse heat conduction problems with multi-variables which include thermal parameters and boundary conditions, and can be identified singly or simultaneously. The direct problems are numerically modeled via FEM, facilitating to sensitivity analysis that is required in solving inverse problems via a least-square based CGM (Conjugate Gradient Method). Inhomogeneous distribution of parameters is considered, and a number of numerical examples are given to illustrate the work proposed.

scholarly journals A Meshless Method Based on the Fundamental Solution and Radial Basis Function for Solving an Inverse Heat Conduction Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Arghand ◽  
Majid Amirfakhrian
Keyword(s):  
Heat Conduction ◽  
Fundamental Solution ◽  
Meshless Method ◽  
Heat Conduction Problem ◽  
Regularization Parameter ◽  
Linear Equations ◽  
Inverse Heat Conduction Problem ◽  
Inverse Heat Conduction ◽  
Radial Basis ◽  
The Stability

We propose a new meshless method to solve a backward inverse heat conduction problem. The numerical scheme, based on the fundamental solution of the heat equation and radial basis functions (RBFs), is used to obtain a numerical solution. Since the coefficients matrix is ill-conditioned, the Tikhonov regularization (TR) method is employed to solve the resulted system of linear equations. Also, the generalized cross-validation (GCV) criterion is applied to choose a regularization parameter. A test problem demonstrates the stability, accuracy, and efficiency of the proposed method.

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