湍流
物理
雷诺平均Navier-Stokes方程
弗劳德数
空气动力学
非线性系统
阻力
机械
流量(数学)
K-omega湍流模型
Kε湍流模型
湍流模型
统计物理学
计算流体力学
应用数学
领域(数学分析)
空气动力阻力
空气动力
经典力学
阻力系数
纳维-斯托克斯方程组
流量控制(数据)
拉格朗日相干结构
晴空湍流
流动分离
攻角
参数化(大气建模)
参数统计
夹带空气
作者
Hang Ren,Rui Deng,Bing Zheng,Qiaowen Yu,Zhiyuan Geng,Dapeng Jiang
摘要
Accurate prediction of aerodynamic and hydrodynamic loads, as well as attitude, during high-speed seaplane taxiing is hindered by the strong nonlinear interaction between air and water flows across the free surface and the multiphase nature of the problem. To address this challenge, we propose a hybrid turbulence framework (SRH, Spalart–Allmaras + Realizable k–ε hybrid turbulence model) based on Reynolds-averaged Navier–Stokes (RANS)/RANS coupling, in which the computational domain is partitioned into a liquid-dominant region, a gas-dominant region, and an interfacial transitional zone. Distinct turbulence closures are assigned to the single-phase regions, while a phase-volume-fraction-based transition scheme ensures smooth parameter exchange across the interface. Validation against experimental measurements and single-model RANS simulations demonstrates that the SRH model achieves comparable accuracy at low speeds, and at high speeds reduces the mean prediction error by ∼5% relative to the single-model baseline, with up to 30% improvement in drag prediction accuracy at the highest volume Froude number (Fr▽) considered. This framework improves both aerodynamic force estimation and the resolution of aerodynamic–hydrodynamic interactions, offering a computationally efficient and physically consistent approach for high-speed multiphase flow prediction in aeronautical and marine engineering applications.
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