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基于遗传算法的回转体头部线型低噪优化设计

Genetic algorithm based low flow-noise optimization design for bodies of revolution

  • 摘要: 基于边界层理论和转捩区声辐射理论,利用Krane偶极子声源模型对Liepmann单极子声源模型进行改进,结合回转体头部线型设计理论,采用标准遗传算法,建立了一套完整的回转体头部线型低噪优化设计的方法和模型。优化结果表明:找到了全局最优解,最大降噪量约为11.8%。

     

    Abstract: Based on boundary layer theory and radiated noise theory from boundary layer transition,the monopole sound source model of Liepmann analogy on displacement thickness is improved by using Krane dipole sound source model.The basic theory and method of genetic algorithms are investigated,based on the investigation,the optimization problem of flow-noise combined with genetic algorithms is discussed,and a complete optimization method and models are established for the flow-noise optimization design of the body of revolution.The results show that the overall optimal solution is found,and the greatest noise reduction attains 11.8%.

     

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