An asynchronous task-based Eulerian-Lagrangian approach for efficient parallel multi-physics simulations that can scale for arbitrary large number of particles and non-uniformly distributed particles is presented. The parallel methodology is based on a task-based partitioning of the multi-physics problem, where each single-physics problem is considered as a task and carried out using its own set of processes. This allows the two problems to solve their governing equations concurrently; therefore, hiding the computational cost incurred of solving an additional physical solver. Applications to complex breakup mechanism leading to highly dynamic computational loading and three-dimensional swirl combustion chamber with reacting flow/spray with extremely uneven particle distribution demonstrate the improved parallel efficiency and great potential of the presented approach.

提出了一种基于任务的异步欧拉-拉格朗日方法，该方法可进行有效的并行多物理场仿真，可缩放任意数量的粒子和非均匀分布的粒子。并行方法基于多物理问题的基于任务的划分，其中每个单物理问题都被视为一项任务，并使用其自己的一组过程来执行。这使两个问题可以同时求解它们的控制方程。因此，隐藏了求解额外的物理求解器所产生的计算成本。