PySPH: A Python-based Framework for Smoothed Particle Hydrodynamics

PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete SPH simulation using pure Python. High-performance code is generated from this high-level Python code and executed on either multiple cores, or on GPUs, seamlessly. It also supports distributed execution using MPI. PySPH supports a wide variety of SPH schemes and formulations. These include, incompressible and compressible fluid flow, elastic dynamics, rigid body dynamics, shallow water equations, and other problems. PySPH supports a variety of boundary conditions including mirror, periodic, solid wall, and inlet/outlet boundary conditions. The package is written to facilitate reuse and reproducibility. This article discusses the overall design of PySPH and demonstrates many of its features. Several example results are shown to demonstrate the range of features that PySPH provides.

Solution-Responsive Particle Size Adaptivity in Lagrangian Vortex Particle Methods

In order to minimize the computational resources necessary for a given level of accuracy in a Lagrangian Vortex Particle Method, a novel particle core size adaptivity scheme has been created. The method adapts locally to the solution while preventing large particle size gradients, and optionally adapts globally to focus effort on important regions. It is implemented in the diffusion solver, which uses the Vorticity Redistribution Method, by allowing and accounting for variations in the core radius of participating particles. We demonstrate the effectiveness of this new method on the diffusion of a δ-function and impulsively started flow over a circular cylinder at Re = 9,500. In each case, the adaptive method provides solutions with marginal loss of accuracy but with substantially fewer computational elements.

An efficient algorithm of the unified stochastic particle Bhatnagar-Gross-Krook method for the simulation of multi-scale gas flows

The unified stochastic particle method based on the Bhatnagar-Gross-Krook model (USP-BGK) has been proposed recently to overcome the low accuracy and efficiency of the traditional stochastic particle methods, such as the direct simulation Monte Carlo (DSMC) method, for the simulation of multi-scale gas flows. However, running with extra virtual particles and space interpolation, the previous USP-BGK method cannot be directly transplanted into the existing DSMC codes. In this work, the implementation of USP-BGK is simplified using new temporal evolution and spatial reconstruction schemes. As a result, the present algorithm of the USP-BGK method is similar to the DSMC method and can be implemented efficiently based on any existing DSMC codes just by modifying the collision module.