Scalable adaptive algorithms for next-generation multiphase flow simulations

K. Saurabh, Masado Ishii, Makrand A. Khanwale, H. Sundar, B. Ganapathysubramanian
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Abstract

High-fidelity flow simulations are indispensable when analyzing systems exhibiting multiphase flow phenomena. The accuracy of multiphase flow simulations is strongly contingent upon the finest mesh resolution used to represent the fluid-fluid interfaces. However, the increased resolution comes at a higher computational cost. In this work, we propose algorithmic advances that aim to reduce the computational cost without compromising on the physics by selectively detecting key regions of interest (droplets/filaments) that require significantly higher resolution. The framework uses an adaptive octree–based meshing framework that is integrated with PETSc’s linear algebra solvers. We demonstrate scaling of the framework up to 114,688 processes on TACC’s Frontera. Finally, we deploy the framework to simulate one of the most resolved simulations of primary jet atomization. This simulation – equivalent to 35 trillion grid points on a uniform grid – is 64× larger than current state–of–the–art simulations and provides unprecedented insights into an important flow physics problem with a diverse array of engineering applications.
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下一代多相流模拟的可扩展自适应算法
在分析具有多相流动现象的系统时,高保真的流动模拟是必不可少的。多相流模拟的准确性很大程度上取决于用于表示流体-流体界面的最佳网格分辨率。然而,提高的分辨率带来了更高的计算成本。在这项工作中,我们提出了算法的进步,旨在通过选择性地检测需要更高分辨率的关键区域(液滴/细丝)来降低计算成本,同时不影响物理特性。该框架使用了一个基于八叉树的自适应网格框架,该框架与PETSc的线性代数求解器相结合。我们在TACC的Frontera上演示了将框架扩展到114,688个进程。最后,我们部署了该框架来模拟一次射流雾化的最精确的模拟之一。该模拟相当于统一网格上的35万亿个网格点,比目前最先进的模拟大64倍,并为各种工程应用的重要流动物理问题提供了前所未有的见解。
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