Experimental estimation of temperature-dependent thermal conductivity coefficient by using inverse method and remote boundary condition

Abstract

This article seeks to experimentally estimate the variation of temperature-dependent thermal conductivity. While utilized cylindrical samples for this purpose are subjected to an impinging hot air jet from a surface, the time-history of temperature is recorded at two points of the samples. When studying the thermal modeling of this problem, the thermal conductivity coefficient and the convective heat transfer coefficient are unknown. Based on the proposed inverse algorithm for predicting the thermal conductivity coefficient, a K-type thermocouple is used as a boundary condition instead of evaluating the heat transfer coefficient of impinging jet. Heat transfer search method is the utilized inverse method. The effect of existing noise in measured temperatures, jet velocity and the number of thermal conductivity coefficient components in terms of temperature on the accuracy of the proposed algorithm are studied. Estimation error is minimum when the number of estimation components is 10. To investigate the capability of developed method, a number of commercial polymeric materials are considered and the results are compared with the findings of laser flash method and the average relative difference is found to be 7%–12%. The suggested method can properly predict the variations of temperature-dependent thermal conductivity while being simple and more cost-effective.