Analysis of Order of the Sequential Regularization Solutions of Inverse Heat Conduction Problems

[+] Author and Article Information
E. P. Scott, J. V. Beck

Heat Transfer Group, Department of Mechanical Engineering, Michigan State University, East Lansing, MI 48824

J. Heat Transfer 111(2), 218-224 (May 01, 1989) (7 pages) doi:10.1115/1.3250665 History: Received January 29, 1988; Online October 20, 2009


Various methods have been proposed to solve the inverse heat conduction problem of determining a boundary condition at the surface of a body from discrete internal temperature measurements. These include function specification and regularization methods. This paper investigates the various components of the regularization method using the sequential regularization method proposed by Beck and Murio (1986). Specifically, the effects of the regularization order and the influence of the regularization parameter are analyzed. It is shown that as the order of regularization increases, the bias errors decrease and the variance increases. Comparatively, the zeroth regularization has higher bias errors and the second-order regularization is more sensitive to random errors. As the regularization parameter decreases, the sensitivity of the estimator to random errors is shown to increase; on the other hand, the bias errors are shown to decrease.

Copyright © 1989 by ASME
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