Name
Abstract | ||
|---|---|---|
A new efficient parallelization strategy for optimization of aerodynamic shapes is proposed. The optimization method employs a full Navier-Stokes solver for accurate estimation of the objective function. As such it requires huge computational resources which makes efficient parallelization crucial for successful promotion of the method to an engineering environment. The algorithm is based on a multilevel embedded parallelization approach, which includes (1) parallelization of the multiblock full Navier-Stokes solver with parallel CFD evaluation of objective function, (2) parallelization of optimization process with parallel optimal search on multiple search domains and, finally, (3) parallel grid generation. Applications (implemented on a 144-processors distributed memory cluster) include various transonic profile optimizations in the presence of nonlinear constraints. The results demonstrate that the approach combines high accuracy of optimization with high parallel efficiency. The proposed multilevel parallelization which efficiently makes use of computational power supplied by multiprocessor systems, leads to a significant computational time-saving and allows application of the method to practical aerodynamic design in the aircraft industry. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1023/B:SUPE.0000032780.68664.1b | The Journal of Supercomputing |
Keywords | Field | DocType |
embedded parallelization,CFD,aerodynamic design,otimization,genetic algorithms | Computer science,Parallel computing,Distributed memory,Multiprocessing,Computational fluid dynamics,Solver,Mesh generation,Genetic algorithm,Aerodynamics,Automatic parallelization | Journal |
Volume | Issue | ISSN |
29 | 3 | 1573-0484 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. Peigin | 1 | 2 | 0.88 |
| Boris Epstein | 2 | 2 | 0.73 |