Parallel adaptive weakly-compressible SPH for complex moving geometries

The use of adaptive spatial resolution to simulate flows of practical interest using Smoothed Particle Hydrodynamics (SPH) is of considerable importance. Recently, Muta and Ramachandran [1] have proposed an efficient adaptive SPH method which is capable of handling large changes in particle resolution. This allows the authors to simulate problems with much fewer particles than was possible earlier. The method was not demonstrated or tested with moving bodies or multiple bodies. In addition, the original method employed a large number of background particles to determine the spatial resolution of the fluid particles. In the present work we establish the formulation's effectiveness for simulating flow around stationary and moving geometries. We eliminate the need for the background particles in order to specify the geometry-based or solution-based adaptivity and we discuss the algorithms employed in detail. We consider a variety of benchmark problems, including the flow past two stationary cylinders, flow past different NACA airfoils at a range of Reynolds numbers, a moving square at various Reynolds numbers, and the flow past an oscillating cylinder. We also demonstrate different types of motions using single and multiple bodies. The source code is made available under an open source license, and our results are reproducible.

采用光滑粒子流体动力学（Smoothed Particle Hydrodynamics, SPH）方法模拟具有实际应用价值的流动问题时，自适应空间分辨率的应用具有重要意义。近期，Muta与Ramachandran[1]提出了一种高效的自适应SPH方法，该方法可应对粒子分辨率的大幅变化，使得研究者能够使用远少于以往的粒子数完成流动模拟。但该方法尚未针对运动体或多体场景开展验证与测试；此外，原始方法需要借助大量背景粒子来确定流体粒子的空间分辨率。本研究验证了该建模方法在定常与运动几何绕流模拟中的有效性：我们无需借助背景粒子即可实现基于几何或基于求解的自适应，并详细阐述了所采用的算法。我们选取了多类基准测试问题，包括双静止圆柱绕流、不同雷诺数下多种NACA翼型绕流、不同雷诺数下运动方柱绕流以及振荡圆柱绕流。同时，我们通过单体与多体场景演示了多种运动形式。本研究的源代码以开源协议公开，所有结果均可复现。