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Estimation of Heat Transfer Coefficient in Two-Dimensional Inverse Heat Conduction Problems

The finite-difference method in conjunction with the least-squares scheme, cubic spline, and temperature measurements is applied to predict the distribution of the heat transfer coefficient on a surface exposed to a moving fluid. In the present study, the functional form of the heat transfer coefficient is unknown a priori. The whole space domain of the unknown heat transfer coefficient can be divided into several analysis subintervals and then the cubic spline is introduced to estimate the unknown values. In order to show the accuracy of the present inverse method, a comparison among the present estimates, previous results, and exact solution is made. The results show that the present inverse scheme not only can reduce the number of the thermocouples but also can increase the accuracy of the estimated results. Also, the present estimates are not very sensitive to the measurement locations. Good estimation of the heat transfer coefficient can be obtained from the knowledge of the temperature recordings even for the case with measurement errors.