论文标题

下一代多相模拟的可扩展自适应算法

Scalable adaptive algorithms for next-generation multiphase flow simulations

论文作者

Saurabh, Kumar, Ishii, Masado, Khanwale, Makrand A., Sundar, Hari, Ganapathysubramanian, Baskar

论文摘要

分析表现出多相流现象的系统时,高保真流量模拟是必不可少的。多相流仿真的精度强烈取决于用于表示流体流体界面的最优质的网状分辨率。但是,提高的分辨率以较高的计算成本有所增加。在这项工作中,我们提出了算法进步,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)来降低计算成本而不损害物理学。该框架使用基于自适应OCTREE的网络趋化框架,该框架与PETSC的线性代数求解器集成在一起。我们在TACC的Frontera上演示了该框架的规模最高为114,688个过程。最后,我们部署了框架,以模拟主要喷气雾化最清晰的模拟之一。该模拟(相当于均匀网格上的35万亿个网格点)比当前的最新模拟大64倍,并提供了对重要流体物理问题的前所未有的见解,并具有各种工程应用程序。

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 times larger than the 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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