Numerical simulations of stone-chipping resistance behaviors of automotive coatings: A CFD-DEM model and a wear prediction method

Abstract

Automotive coatings often suffer from high-speed stone impact wear damage. Currently, it remains a significant challenge to evaluate the stone-chipping resistance performance of automotive coatings. The main purpose of this work is to develop a computational approach combining a numerical model with a prediction method to achieve this end. The numerical model is developed based on the Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM) to account for the moving behaviors of large, irregularly shaped stone chips driven by high-pressure airflow in a multifunctional anti-impact tester. In this model, stone chips are represented using multi-spheres. To address the mismatch issue in the inlet boundary conditions, this study utilizes high-fidelity modeling of the tee pipe in a multi-functional impact tester. Additionally, it takes into account the influence of the high-pressure airflow compressibility on particle behaviors. A wear prediction method is further developed. Within this method, a particle erosion model is utilized to account for short-term coating damage evaluation based on CFD-DEM simulation results. Subsequently, a prediction method is proposed to efficiently estimate long-term damage for a DIN standard multi-particle impact case by using mean-range random functions. With the aid of the developed computational method, single- and multi-particle impact simulations are conducted, and numerical results are found in good agreement with experimental data in terms of the damage distribution trend and impact position distributions.