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.

中文翻译：

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使用验证数据的粗网格 CFD 两相流模拟中的深度学习界面动量闭合

多相流动现象已在工业应用中广泛观察到，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) 方法在更精细的空间和时间尺度上解析流场，可以补充专门的实验研究。但是，必须引入闭包以反映多相流中的基础物理。其中，界面力，包括阻力、升力、湍流分散力和壁面润滑力，在气液两相流中气泡分布和迁移中起重要作用。这些封闭装置的开发传统上依赖于实验数据和分析推导以及简化假设，这些假设通常无法在广泛的流动条件下提供通用解决方案。在本文中，一种数据驱动的方法，被称为特征相似性测量（FSM），被开发并应用于提高粗网格 CFD 方法的两相流模拟能力。绝热气泡流中的界面动量传递是本研究的重点。成熟和简化的界面闭合集都被视为低保真数据。验证数据（包括相关实验数据和经过验证的细网格 CFD 模拟结果）被用作高保真数据。本文进行了定性和定量分析。这些表明 FSM 可以显着提高粗网格 CFD 模型的预测，而不管界面闭合的选择如何，并且它提供跨不连续流态的可扩展性和一致性。