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Numerical prediction of effective wake field for a submarine based on a hybrid approach and an RBF interpolation

机译:基于混合方法和RBF插值的潜艇有效唤醒场的数值预测

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A hybrid approach coupled with a surface panel method for the propeller and a Reynolds averaged Navier-Stokes (RANS) model for the hull with the propeller body forces are presented for predicting the self -propulsion performance and the effective wake field of underwater vehicles. To achieve a high accuracy and simplicity, a radial basis function (RBF) based approach is proposed for mapping the force field from the blade surface panels to the RANS model. The effective wake field is evaluated in two ways, i.e., by extrapolation from the flat planes upstream of the propeller disk, and by direct computation in a curved surface upstream of and parallel to the blade leading edges. The hull-propeller system of a real propeller geometry is further simulated with the sliding mesh model to numerically verify the hybrid approach. Numerical simulations are conducted for the fully appended SUBOFF submarine model. The high accuracy of the RBF-based interpolation scheme is confirmed, and the effective wake fraction predicted by the hybrid approach is found consistent with that obtained by the sliding mesh model. The effective wake fractions predicted by the two methods are, respectively, 4.6% and 3% larger than the nominal one.
机译:提出了一种与螺旋桨的表面面板方法连接的混合方法和具有螺旋桨体力的船体的河豚(RANS模型的reynolds(RANS)模型用于预测水下车辆的自实施性能和有效的唤醒领域。为了实现高精度和简单性,提出了一种基于径向基函数(RBF)的方法,用于将力场从刀片表面面板映射到RAN模型。有效唤醒场以两种方式评估,即通过从螺旋桨盘的上游的平面外推,以及通过直接计算在与刀片前缘上游和平行的弯曲表面中的直接计算。使用滑动网格模型进一步模拟实际螺旋桨几何形状的船体螺旋桨系统,以在数值上验证混合方法。为完全附加的超级潜水机模型进行了数值模拟。确认了基于RBF的内插方案的高精度,并且通过滑动网格模型获得的混合方法预测的有效唤醒分数一致。由两种方法预测的有效唤醒级分别分别为4.6%和3%,比标称值大。

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