A local adaptive discretization algorithm for Smoothed Particle Hydrodynamics: For the inaugural issue

25Citations
Citations of this article
31Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this paper, an extension to the Smoothed Particle Hydrodynamics (SPH) method is proposed that allows for an adaptation of the discretization level of a simulated continuum at runtime. By combining a local adaptive refinement technique with a newly developed coarsening algorithm, one is able to improve the accuracy of the simulation results while reducing the required computational cost at the same time. For this purpose, the number of particles is, on the one hand, adaptively increased in critical areas of a simulation model. Typically, these are areas that show a relatively low particle density and high gradients in stress or temperature. On the other hand, the number of SPH particles is decreased for domains with a high particle density and low gradients. Besides a brief introduction to the basic principle of the SPH discretization method, the extensions to the original formulation providing such a local adaptive refinement and coarsening of the modeled structure are presented in this paper. After having introduced its theoretical background, the applicability of the enhanced formulation, as well as the benefit gained from the adaptive model discretization, is demonstrated in the context of four different simulation scenarios focusing on solid continua. While presenting the results found for these examples, several properties of the proposed adaptive technique are discussed, e.g. the conservation of momentum as well as the existing correlation between the chosen refinement and coarsening patterns and the observed quality of the results.

Cite

CITATION STYLE

APA

Spreng, F., Schnabel, D., Mueller, A., & Eberhard, P. (2014). A local adaptive discretization algorithm for Smoothed Particle Hydrodynamics: For the inaugural issue. Computational Particle Mechanics, 1(2), 131–145. https://doi.org/10.1007/s40571-014-0015-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free