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A ship propeller design methodology of multi-objective optimization considering fluid–structure interaction

机译:考虑流固耦合的多目标优化的船舶螺旋桨设计方法

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This paper presents a multi-objective optimization methodology that applies the Non-dominated Sorting Genetic Algorithm-II(NSGA-II) to propeller design, and realizes Fluid-Structure Interaction (FSI) weak-coupling based on Panel Method (PM) and the Finite Element Method (FEM). The FSI iterative process and the convergent pressure coefficient distribution and pressure fluctuation of HSP (a propeller installed on a Japanese bulk freighter – Seiun-Maru) are numerical calculated. The FSI results turn out to have higher precision than those without FSI. The appropriate optimization parameters are chosen after studying five cases. The Sobol method, a global Sensitivity Analysis (SA) algorithm, is used to quantify the dependence of objectives and constraints on the input parameters. In the multi-objective optimization methodology, efficiency, unsteady force, and mass are chosen as optimum objectives under certain constraints. Effectiveness and robustness of the methodology are validated by running the pr...
机译:本文提出了一种多目标优化方法,该方法将非支配排序遗传算法-II(NSGA-II)应用于螺旋桨设计,并基于面板法(PM)和流域法实现了流固耦合(FSI)弱耦合。有限元方法(FEM)。计算了FSI的迭代过程以及HSP(安装在日本散货船Seiun-Maru上的螺旋桨)的收敛压力系数分布和压力波动。事实证明,FSI结果比没有FSI的结果具有更高的精度。通过研究五种情况选择适当的优化参数。 Sobol方法是一种全局敏感性分析(SA)算法,用于量化目标和约束条件对输入参数的依赖性。在多目标优化方法中,在某些约束条件下,将效率,不稳定力和质量选择为最佳目标。通过运行程序验证了该方法的有效性和鲁棒性。

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