Abstract:
Recent effort was presented on multi-objective wing shape optimization of NASA Common Research Model (CRM) in wing-body-nacelle-pylon (WBNP) configuration. The performance of a large number of designs was evaluated by solving Reynolds Averaged Navier-Stokes (RANS) equations. Parallel computations and supercomputer resources were employed to make the optimization process completed in acceptable time cycle. An automated optimization framework was integrated, which consists of CST-based wing parameterization, mesh deformation, flow solving, post processing, and genetic-algorithm-based global optimization. When running the framework on supercomputer, hundreds of designs can be evaluated at the same time. By using a multi-block mesh with 8 million cells, the solution of CRM WBNP configuration can be obtained within 15 minutes with the help of parallel computation and convergence acceleration techniques. In a typical 3-objective optimization application, the evaluation of 128 candidates was carried out simultaneously with computational fluid dynamics on Tianhe-2 supercomputer. Total 90 design variables were used to represent camber line shapes and twist angles of 9 control sections. It took 60 hours to complete the evolution for near 40 generations. The drag reduction of 2 to 10 counts for each objective is achieved comparing with the baseline shape.