Development of Multiobjective Optimization Using Graphics Processing Unit Computing in Fluid-Film Lubrication Analysis (Ii)

This proposal is intended as an extended study of the current NSC project (NSC 101-2221-E-182-023, 2012/8-2013/7, which was planned as a two-year project, but only passed as a one-year project). The proposal is to extend the progress and results obtained in the current project, so as to accomplish the original and more complete objectives set forth by the original two-year proposal. Many applications in tribological and engineering fields require the solution of multiobjective optimization. Parallel computing is commonly applied to reduce the execution of such an optimization. This is due to the fact that most of the global search algorithms are designed to search multiple locations simultaneously. As the performance of the computing power increased daily the lubrication models are becoming more complex as well. For a multi-factor multiobjective optimization problem the execution time is still a practical barrier in engineering practices. The main purpose of the project is to develop an efficient global search algorithm using new parallel computing technique to facilitate the tribological analysis. The main focus of this project is to develop the multi-objective optimization methods by combining the Pareto criterion and the three global search methods (genetic algorithm, particle swarm optimization, edge-search method) for the gap-compensated hydrostatic bearing. The approach proposed in this study should be useful in dealing with many tribological design problems. The effectiveness of graphics processing units in computing and the search efficiency of the proposed optimization method are to be evaluated.

Project ID:PB10207-1907
External Project ID:NSC102-2221-E182-016