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Parallel Computing for Numerical Analysis of a Fan Assembly Subjected to a SPH Bird

机译:平行计算用于对SPH鸟进行风扇组件的数值分析

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Smoothed Particle Hydrodynamics (SPH) is widely adopted to predict bird strike events. To improve the parallel computing efficiency of the SPH approach, parallel computing was performed on the process of a bird striking the fan assembly. Since the cube-shaped domains aligned along the coordinate axes that are inherent in the decomposition algorithm may result in low computational efficiency, the effect of customized data partitioning on the efficiency is investigated. The results show that customized decompositions can minimize communication between processors and ensure the load balance during the simulation process. Besides, distributed computing with domain decompositions can present reasonable predictions at soft-impact damage, achieving consistent results within a range of less than 7% of the reference data derived from shared memory computing.
机译:广泛采用平滑的粒子流体动力学(SPH)来预测鸟类罢工事件。 为了提高SPH方法的平行计算效率,对捕获风扇组件的鸟的过程执行并行计算。 由于沿着分解算法中固有的坐标轴对准的立方形域可能导致低计算效率,因此研究了定制数据划分对效率的影响。 结果表明,定制分解可以最大限度地减少处理器之间的通信,并确保在仿真过程中的负载平衡。 此外,具有域分解的分布式计算可以在软碰撞损坏下呈现合理的预测,在少于7%的参考数据的范围内实现一致的结果,该参考数据来自共享存储器计算的范围。

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