论文标题

在大规模平行系统上进行高保真粒子跟踪的框架

A framework for high-fidelity particle tracking on massively parallel systems

论文作者

Kopper, Patrick, Schwarz, Anna, Copplestone, Stephen M., Ortwein, Philip, Staudacher, Stephan, Beck, Andrea

论文摘要

从大气流到可再生能量到涡轮机械的范围内,充满粒子的流量发生在广泛的学科中。由于它们通常复杂的几何形状和高度的机构流场,它们通常为粒子诱导现象的数值预测带来了一个具有挑战性的环境,该环境涵盖了广泛的空间和时间尺度。同时,对颗粒相的演变的信心对于可靠的非线性效应(例如侵蚀和结垢)的可靠预测至关重要。结果,多尺度要求流场和分散阶段的时间准确的整合,尤其是在过渡和分离的情况下。在这项工作中,我们介绍了开源高阶准确的CFD框架flexi flexi flexi flexi的扩展。 FlexI是可压缩的Navier-Stokes-stokes Quier方程的大规模并行求解器,该方程在(未)结构化的网格上运行,包括弯曲元件和悬挂节点。基于射线追踪方法的物理空间中的有效粒子跟踪方法用于处理具有弯曲边界的交叉点。我们描述了一个单向和双向耦合的分散阶段及其数值处理的模型,其中特别重点是讨论背景和动机,从而导致特定的实施选择。在完整的工具链过程中,特别注意将FlexI在高性能计算基础架构上保留出色的缩放属性,包括高阶准确的后处理。最后,我们证明了扩展框架对大规模问题的适用性。

Particle-laden flows occur in a wide range of disciplines, from atmospheric flows to renewable energy to turbomachinery. They generally pose a challenging environment for the numerical prediction of particle-induced phenomena due to their often complex geometry and highly instationary flow field which covers a wide range of spatial and temporal scales. At the same time, confidence in the evolution of the particulate phase is crucial for the reliable prediction of non-linear effects such as erosion and fouling. As a result, the multiscale nature requires the time-accurate integration of the flow field and the dispersed phase, especially in the presence of transition and separation. In this work, we present the extension of the open-source high-order accurate CFD framework FLEXI towards particle-laden flows. FLEXI is a massively parallel solver for the compressible Navier-Stokes-Fourier equations which operates on (un-)structured grids including curved elements and hanging nodes. An efficient particle tracking approach in physical space based on methods from ray-tracing is employed to handle intersections with curved boundaries. We describe the models for a one- and two-way coupled dispersed phase and their numerical treatment, where particular emphasis is placed on discussing the background and motivation leading to specific implementation choices. Special care is taken to retain the excellent scaling properties of FLEXI on high performance computing infrastructures during the complete tool chain including high-order accurate post-processing. Finally, we demonstrate the applicability of the extended framework to large-scale problems.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源