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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Thermal simulation in multiphase incompressible flows using coupled meshfree and particle level set methods
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Thermal simulation in multiphase incompressible flows using coupled meshfree and particle level set methods

机译：使用无网格和粒子水平集的耦合方法对多相不可压缩流进行热模拟

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摘要

A particle-based numerical solver is presented, applicable to the simulation of heat transfer in multiphase immiscible flows including surface tension. In the context of meshfree methods, the Laplacian operator is recognized as the most numerically challenging ingredient of the heat equation. The well-known difficulty of approximating higher-order spatial derivatives with meshfree methods is herein addressed by adopting two advanced schemes in order to ensure second-order accuracy. In addition, a Lagrangian particle level set method with second-order reinitialization is introduced, for the first time in thermal simulations, to capture the location of the interface, i.e., moving and/or deformable boundaries of the continuum at each time-step. This leads to a more conservative solution, alleviating the mass loss during the simulation. Furthermore, a narrow band of the exterior geometric particles is exploited to form physical ghost particles to enforce the required boundary conditions. This novel approach ensures solver performance without the necessity of defining extra dummy particles for treating boundary conditions in meshfree simulations. Three benchmark problems are considered for evaluating the performance of the proposed solver against a reference analysis performed in COMSOL Multiphysics (R). (c) 2018 Elsevier B.V. All rights reserved.
机译：提出了一种基于粒子的数值求解器，适用于模拟包括表面张力在内的多相不混溶流动中的传热。在无网格方法的上下文中，拉普拉斯算子被认为是热方程中最具数字挑战性的成分。为了确保二阶精度，本文通过采用两种高级方案解决了用无网格方法逼近高阶空间导数的众所周知的困难。另外，在热模拟中首次引入具有二阶重新初始化的拉格朗日粒子能级设置方法，以捕获界面的位置，即，每个时间步长的连续体的移动和/或可变形边界。这导致了更为保守的解决方案，从而减轻了仿真过程中的质量损失。此外，利用外部几何粒子的窄带来形成物理幻影粒子，以强制执行所需的边界条件。这种新颖的方法可确保求解器性能，而无需定义额外的虚拟粒子来处理无网格模拟中的边界条件。考虑了三个基准问题，以根据COMSOL Multiphysics（R）中进行的参考分析评估所提出的求解器的性能。 （c）2018 Elsevier B.V.保留所有权利。

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