基于神经网络和遗传算法的潜艇声场边界元/有限元仿真及形状优化

Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869) Pub Date : 2004-04-20 DOI:10.1109/UT.2004.1405578

M. Durali, A. Delnavaz

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引用次数: 2

摘要

对潜艇进行形状优化以使噪声最小化是本研究的目标。边界元法和有限元法已被用于确定物体周围的声场。提出了一种神经网络和遗传算法相结合的方案，以寻找潜艇在某些参考点上发射声能最小的最佳外部几何比。所得的最优几何值在最小水动力的正常范围内，与模型投产后的变化趋势基本一致。

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BEM/FEM simulation of acoustic field and shape optimization of submarine using neural network and genetic algorithm

Shape optimization of a submarine for minimized noise emission has been the objective of this work. Boundary element method and finite element methods have been employed to determine the acoustic field around the object. A combined neural network and genetic algorithm scheme is developed to find the optimum external geometric ratios of the submarine for a minimized emitted acoustic energy in certain reference points. The obtained optimum geometric values stay in normal range for minimum hydrodynamic forces and show a close agreement with the trend of change for models coming to operation.

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Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)

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