A genetic algorithm for optimization design of thermoacoustic refrigerators

In the recent years extensive research efforts have been made to develop alternative refrigeration technologies that are environmentally safe. Among of these are thermoacoustic refrigeration and pulse-tube technologies. The thermoacoustic refrigerators are devices which use acoustic power to pump heat. However, the efficiency of the thermoacoustic refrigerators currently is not competitive the conventional refrigerators. In this paper we present an alternative optimization design approach based on the multi-population genetic algorithms to maximize the efficiency of the thermoacoustic refrigerators. Since the governing equation of the thermoacoustic refrigerators is a system of two-point boundary-value differential equations, we impose a two-point boundary-value problem solver into the genetic algorithm such that the algorithm can solve the governing equation and do optimization at the same time. The results show that the modified genetic algorithm is able to obtain the design variables that maximize.