Solving inverse problems of radiative heat transfer and phase change in semitransparent medium by using Improved Quantum Particle Swarm Optimization

In the present study, the Quantum Particle Swarm Optimization (QPSO) algorithm is applied to solve the inverse problems of radiative heat transfer and phase change in laser heating semitransparent medium. To increase the efficiency and the accuracy of the original QPSO algorithm, an Improved Quantum Particle Swarm Optimization (IQPSO) algorithm is developed based on the original QPSO algorithm. To illustrate the performance of the proposed IQPSO algorithm, the Stefan number or/and conduction to radiation number of the one-dimensional semitransparent phase change medium are retrieved by measuring the transient boundary temperatures. The Finite Volume Method approximation is treated as the forward model and the sensitivity and measurement error are also analyzed. By the IQPSO algorithm presented, the thermophysical parameters can be estimated accurately, even with noisy data. In conclusion, the IQPSO algorithm is demonstrated to be more effective and robust compared with the Basic Particle Swarm Optimization and QPSO algorithms through function estimation and parameter estimation, it is thus has the potential to be implemented in various fields of inverse heat transfer problems.