A Solution Method of Inverse Heat Conduction Problem by a Integral Form of Non-steady Heat Conduction Equation for a Slab and its Application to the Calculation of Surface Temperature-dependent Heat Transfer Coefficient.

The inverse heat conduction problem (IHCP) in a one-dimensional composite slab with rate-dependent pyrolysis chemical reaction and outgassing flow effects is investigated using the iterative regularization approach. The thermal properties of the composites are considered to be temperature-dependent. A nonlinear conjugate gradient method formulation is developed and applied to solve the IHCP in an organic composite slab whose front-surface is subjected to high intensity periodic laser heating.

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A fundamental solution method for inverse heat conduction problem

Engineering Analysis with Boundary Elements ◽

10.1016/s0955-7997(03)00102-4 ◽

2004 ◽

Vol 28 (5) ◽

pp. 489-495 ◽

Cited By ~ 147

Author(s):

Y.C. Hon ◽

T. Wei

Keyword(s):

Heat Conduction ◽

Fundamental Solution ◽

Solution Method ◽

Heat Conduction Problem ◽

Inverse Heat Conduction Problem ◽

Inverse Heat Conduction ◽

Fundamental Solution Method

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The Steady Inverse Heat Conduction Problem: A Comparison of Methods With Parameter Selection

Journal of Heat Transfer ◽

10.1115/1.1372193 ◽

2001 ◽

Vol 123 (4) ◽

pp. 633-644 ◽

Cited By ~ 11

Author(s):

Robert Throne ◽

Lorraine Olson

Keyword(s):

Heat Conduction ◽

Tikhonov Regularization ◽

Heat Conduction Problem ◽

Regularization Parameter ◽

Inverse Heat Conduction Problem ◽

Inverse Heat Conduction ◽

True Solution ◽

Sensitivity Method ◽

Inverse Boundary Value Problems ◽

Steady Heat Conduction

In the past we have developed the Generalized Eigensystem GESL techniques for solving inverse boundary value problems in steady heat conduction, and found that these vector expansion methods often give superior results to those obtained with standard Tikhonov regularization methods. However, these earlier comparisons were based on the optimal results for each method, which required that we know the true solution to set the value of the regularization parameter (t) for Tikhonov regularization and the number of mode clusters Nclusters for GESL. In this paper we introduce a sensor sensitivity method for estimating appropriate values of Nclusters for GESL. We compare those results with Tikhonov regularization using the Combined Residual and Smoothing Operator (CRESO) to estimate the appropriate values of t. We find that both methods are quite effective at estimating the appropriate parameters, and that GESL often gives superior results to Tikhonov regularization even when Nclusters is estimated from measured data.

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Numerical Solution of the General Two-Dimensional Inverse Heat Conduction Problem (IHCP)

Journal of Heat Transfer ◽

10.1115/1.2824098 ◽

1997 ◽

Vol 119 (1) ◽

pp. 38-45 ◽

Cited By ~ 45

Author(s):

A. M. Osman ◽

K. J. Dowding ◽

J. V. Beck

Keyword(s):

Experimental Data ◽

Heat Conduction ◽

Heat Conduction Problem ◽

Regularization Parameter ◽

Simulated Data ◽

Inverse Heat Conduction Problem ◽

Transient Temperature ◽

Two Dimensional ◽

Inverse Heat Conduction ◽

Temperature Dependent

This paper presents a method for calculating the heat flux at the surface of a body from experimentally measured transient temperature data, which has been called the inverse heat conduction problem (IHCP). The analysis allows for two-dimensional heat flow in an arbitrarily shaped body and orthotropic temperature dependent thermal properties. A combined function specification and regularization method is used to solve the IHCP with a sequential-in-time concept used to improve the computational efficiency. To enhance the accuracy, the future information used in the sequential-in-time method and the regularization parameter are variable during the analysis. An example using numerically simulated data is presented to demonstrate the application of the method. Finally, a case using actual experimental data is presented. For this case, the boundary condition was experimentally measured and hence, it was known. A good comparison is demonstrated between the known and estimated boundary conditions for the analysis of the numerical, as well as the experimental data.

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