A Block-based Adaptive Particle Refinement SPH Method for Fluid-Structure Interaction Problems

TL;DR

This paper introduces a novel block-based adaptive particle refinement method for SPH that effectively tracks complex, varying regions of interest in fluid-structure interaction simulations, improving local resolution and solution quality.

Contribution

The paper presents a new BAPR method that adaptively refines particles in targeted regions, handling complex topologies more effectively than traditional APR methods.

Findings

Successfully applied to 2D FSI cases

Enhanced local resolution in targeted regions

Validated performance and adaptability

Abstract

The multi-resolution method, e.g., the Adaptive Particle Refinement (APR) method, has been developed to increase the local particle resolution and therefore the solution quality within a pre-defined refinement zone instead of using a globally uniform resolution for Smoothed Particle Hydrodynamics (SPH). However, sometimes, the targeted zone of interest can be varying, and the corresponding topology is very complex, thus the conventional APR method is not able to track these characteristics adaptively. In this study, a novel Block-based Adaptive Particle Refinement (BAPR) method is developed, which is able to provide the necessary local refinement flexibly for any targeted characteristic, and track it adaptively. In BAPR, the so-called activation status of the block array defines the refinement regions, where the transition and activated zones are determined accordingly. A regularization method for the generated particles in the newly activated blocks is developed to render an isotropic distribution of these new particles. The proposed method has been deployed for simulating Fluid-Structure Interaction (FSI) problems. A set of 2D FSI cases have been simulated with the proposed BAPR method, and the performance of the BAPR method is quantified and validated comprehensively. In a word, the BAPR method is viable and potential for complex multi-resolution FSI simulations by tracking any targeted characteristic of interest.