Numerical solutions for general inverse heat conduction problem

Abstract

A family of numerical methods for determining the space-and time-variable heat transfer coefficient, based on experimentally acquired interior temperature-time data, is presented. Newton-type methods are utilized to compute simultaneously the unknown heat transfer coefficient components. To reduce the influence of random errors in the measurement data on the estimated heat transfer coefficients, the noisy data are smoothed using least squares approximation by cubic splines. Three test examples using experimental and random simulated data are used to illustrate the computation efficiency and generality of the present methods.