标题： 适用于可压缩多相流的波或物理适当多维迎风方法 显示英文标题

标题： Wave or Physics-Appropriate Multidimensional Upwinding Approach for Compressible Multiphase Flows

摘要： 本文介绍了用于模拟多相流的多维算法，利用欧拉方程在特征空间中的波结构以及物理空间中变量的物理特性。 该算法在特征空间中对声学波、涡度波和熵波应用不同的重构方案，以提高精度并最小化数值伪像。 在特征空间中，使用迎风格式处理声学波，使用中心格式处理涡度波和熵波，并使用切线超几何界面捕捉（THINC）重构处理材料界面和接触间断（熵波的一个子集）。 这种方法可防止周期性剪切层中的虚假涡旋，准确捕捉气体-气体和气体-液体相互作用中的涡旋结构，并提高激波-熵波相互作用的精度。 在物理空间中，接触间断和材料界面区域的相密度使用THINC计算，而切向速度则使用中心格式以改善涡旋结构。 还引入了一种自适应重构技术，通过结合原始变量和特征变量重构，并利用强化气体参数识别液相，以减轻由原始变量重构引起的激波附近的振荡。 所提出的多维迎风方法优于传统方案，在捕捉物理现象、减少数值伪像以及在复杂测试案例中更好地匹配实验结果方面表现出更高的精度。 显示英文摘要

摘要： This paper introduces multidimensional algorithms for simulating multiphase flows, leveraging the wave structure of the Euler equations in characteristic space and the physical properties of variables in physical space. The algorithm applies different reconstruction schemes to acoustic, vorticity, and entropy waves in characteristic space to enhance accuracy and minimize numerical artifacts. In characteristic space, upwind schemes are used for acoustic waves, central schemes for vorticity and entropy waves, and Tangent of Hyper-bola for INterface Capturing (THINC) reconstruction for material interfaces and contact discontinuities (a subset of entropy waves). This approach prevents spurious vortices in periodic shear layers, accurately captures vortical structures in gas-gas and gas-liquid interactions, and improves the accuracy of shock-entropy wave interactions. In physical space, phasic densities are computed using THINC in regions of contact discontinuities and material interfaces, while tangential velocities are calculated with central schemes to improve vortical structures. An adaptive reconstruction technique is also introduced to mitigate oscillations near shocks, which arise from primitive variable reconstruction, by combining primitive and characteristic variable reconstructions with the liquid phase being identified using the stiffened gas parameter. The proposed multidimensional upwinding approach outperforms traditional schemes, demonstrating superior accuracy in capturing physical phenomena, reducing numerical artifacts, and better matching experimental results across complex test cases.