Simulation of micro-flow dynamics at low capillary numbers using adaptive interface compression
Simulation of micro-flow dynamics at low capillary numbers using adaptive interface compression
复制标题
DOI：
10.1016/j.compfluid.2018.01.009
复制
发表时间：
2018-03-30
影响因子：
2.8
通讯作者：
Vogiatzaki, K.
中科院分区：
文献类型：
--
作者：
Aboukhedr, M.;Georgoulas, A.;Vogiatzaki, K.
已经开发出用于模拟具有尖锐界面的微尺度多相流的数值框架。建议的方法旨在有效且严格地模拟毛细管主导流动（低毛细管数）下的复杂界面运动。这种流动在从微型设备到天然多孔介质的各种配置中都会遇到。该方法以流体体积 (VoF) 方法为基础，结合额外的锐化、平滑和过滤算法来捕获界面。当粘性力和表面张力主导惯性力时（例如在多孔介质中），这些算法有助于最大限度地减少流动模拟中存在的寄生电流。该框架是在有限体积代码 (OpenFOAM) 中实现的，使用带有显式解 (MULES) 隐式公式的有限多维通用限制器，这允许在低毛细管数下使用更大的时间步长。此外，首次引入了自适应界面压缩方案，以便仅在感兴趣的区域动态估计压缩速度，从而具有避免使用先验定义的参数的优点。发现自适应方法可以提高数值精度并降低方法对调整参数的敏感性。针对五个不同的基准测试用例验证了所提出模型的准确性和稳定性。此外，还将数值结果与解析解以及可用的实验数据进行了比较，揭示了相对于标准 VoF 求解器的改进解。皇冠版权所有 (C) 2018 由 Elsevier Ltd 出版。保留所有权利。
A numerical framework for modelling micro-scale multiphase flows with sharp interfaces has been developed. The suggested methodology is targeting the efficient and yet rigorous simulation of complex interface motion at capillary dominated flows (low capillary number). Such flows are encountered in various configurations ranging from micro-devices to naturally occurring porous media. The methodology uses as a basis the Volume-of-Fluid (VoF) method combined with additional sharpening smoothing and filtering algorithms for the interface capturing. These algorithms help the minimisation of the parasitic currents present in flow simulations, when viscous forces and surface tension dominate inertial forces, like in porous media. The framework is implemented within a finite volume code (OpenFOAM) using a limited Multidimensional Universal Limiter with Explicit Solution (MULES) implicit formulation, which allows larger time steps at low capillary numbers to be utilised. In addition, an adaptive interface compression scheme is introduced for the first time in order to allow for a dynamic estimation of the compressive velocity only at the areas of interest and thus has the advantage of avoiding the use of a-priori defined parameters. The adaptive method is found to increase the numerical accuracy and to reduce the sensitivity of the methodology to tuning parameters. The accuracy and stability of the proposed model is verified against five different benchmark test cases. Moreover, numerical results are compared against analytical solutions as well as available experimental data, which reveal improved solutions relative to the standard VoF solver. Crown Copyright (C) 2018 Published by Elsevier Ltd. All rights reserved.