论文标题
深度学习界面动量封闭，用验证数据进行粗晶格CFD CFD CFD两相流量模拟
Deep Learning Interfacial Momentum Closures in Coarse-Mesh CFD Two-Phase Flow Simulation Using Validation Data
论文作者
论文摘要
多相流现象已在工业应用中被广泛观察到，但它仍然是一个具有挑战性的未解决问题。三维计算流体动力学（CFD）方法可以在更细的时空尺度上解决流场的解决方案，这可以补充专用的实验研究。但是，必须引入封闭以反映多相流中的潜在物理。其中，界面力，包括阻力，提升，湍流分散和壁润滑力，在液态蒸气两相流中的气泡分布和迁移中起着重要作用。传统上，这些封闭的开发依赖于实验数据和分析推导，并具有简化的假设，这些假设通常无法在各种流动条件上提供通用解决方案。在本文中，开发并应用了一种数据驱动的方法，称为特征相似度测量（FSM），以提高使用粗线CFD方法的两相流量的模拟能力。绝热气泡流中的界面动量转移是本研究的重点。成熟和简化的界面封闭都被视为低保真数据。验证数据（包括相关的实验数据和经过验证的Fine-Mesh CFD模拟结果）被用作高保真数据。在本文中进行了定性和定量分析。这些揭示了FSM可以基本上改善粗线CFD模型的预测，而不管界面闭合的选择如何，并且可以在不连续的流动范围内提供可扩展性和一致性。它表明，数据驱动的方法可以通过探索本地物理特征和仿真错误之间的连接来帮助多相流建模。
Multiphase flow phenomena have been widely observed in the industrial applications, yet it remains a challenging unsolved problem. Three-dimensional computational fluid dynamics (CFD) approaches resolve of the flow fields on finer spatial and temporal scales, which can complement dedicated experimental study. However, closures must be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent-dispersion and wall-lubrication forces, play an important role in bubble distribution and migration in liquid-vapor two-phase flows. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions that usually cannot deliver a universal solution across a wide range of flow conditions. In this paper, a data-driven approach, named as feature-similarity measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low-fidelity data. Validation data (including relevant experimental data and validated fine-mesh CFD simulations results) are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper. These reveal that FSM can substantially improve the prediction of the coarse-mesh CFD model, regardless of the choice of interfacial closures, and it provides scalability and consistency across discontinuous flow regimes. It demonstrates that data-driven methods can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.
