Aerodynamic shape optimization using computational fluid dynamics and parallel simulated annealing algorithms

Aerodynamic shape design using stochastic optimization methods, such as simulated annealing method to optimize objective functions evaluated by modern state-of-the-art computational fluid dynamics salvers, normally requires enormous computation time to search for the global optimal design. Aerodynamic shape optimization of internal flow systems is studied using Euler/Navier-Stokes salvers and parallel simulated annealing algorithm, which is implemented on parallel computing platforms. A variety of inverse and direct design of internal flow systems are carried out to examine the efficiency and speedup of the parallel simulated annealing algorithms. The results demonstrate that parallel simulated annealing can be a feasible global optimizer for aerodynamic shape design resulting in considerable reductions in wall-clock time on multiple processors.