عنوان مقاله [English]
In this paper, we investigate the inverse heat conduction method by a set of data extracted from experimental applications has been studied. Two heat transfer classic problems are designed for this purpose and the measured data are utilized as an input to the inverse heat conduction algorithm. In the first experiment, a stainless steel plate (AISI-304 with length, width, and thickness of 250, 70, and 5 millimeters, respectively) is in proximity to a heater from one surface. Other faces are completely insulated, and the temperature from the bottom insulated surface has been measured with type K thermocouples, which is used to estimate the heater heat flux. There has been low pass Butterworth filter applied to the collected data before the usage in inverse algorithm. These kinds of problems with measurement at the inactive surface are common in inverse heat conduction fields due to the measurement and construction complexities. Second experiment is a bit more sophisticated and designed in order to find the free convection heat transfer coefficient of air adjacent to stainless steel plate. It consists of the previous heater and steel plate, in addition to wood, fiber glass, and elastomer insulation layers. The temperatures inside the steel and wood plates are measured, in addition to the ambient air and the last insulation layer temperatures. The calculation is started from the bottom surface and the heat flux lost into environment is calculated, then heat transfer in each layer is estimated one by one until we reach the steel plate on the top, adjacent to air. Sequential function estimation method, due to its online and fast solution, has been used as an inverse heat conduction technique to solve the problems. The results show that inverse heat conduction algorithm has an acceptable accuracy in situations, in which temperature measurement on active surface comes with difficulties such as high temperatures, harsh environment, construction problems, etc.