Solution of 2-D Inverse Heat Conduction Problem with Graphic Accelerator

Abstract

The parallelized particle swarm optimization (PSO) method has been developed to solve inverse heat transfer problems. Temporal- and spatial-dependent heat transfer coefficient functions obtained on the surfaces of axis-symmetrical work pieces are estimated by applying the novel technique. The goal function to be minimized by the PSO approach is defined by the deviation of the measurements and the calculated temperatures. The PSO algorithm has been parallelized and implemented on a graphic processing unit (GPU) architecture. Numerical results demonstrate that the determination of heat transfer coefficient functions can be performed by using the parallelized PSO method as well as the GPU implementation and that they provide a less time-consuming and more accurate estimation.