{"title":"Simulation of solid particle erosion wear using discrete element method: Comparison of experimental and analysis results","authors":"Mehmet Esat Aydin , Veysel Firat , Mehmet Bagci","doi":"10.1016/j.partic.2025.10.003","DOIUrl":null,"url":null,"abstract":"<div><div>The Discrete Element Method (DEM) stands out as an effective computational tool for modeling complex mechanical wear processes such as solid particle erosion. The DEM method offers significant advantages in terms of providing realistic results, particularly when it comes to examining particle and surface interactions over time and predicting surface deformations. In this study, the effectiveness of DEM in determining the solid particle erosion wear behavior was evaluated by comparing it with experimental data. In the experimental phase, aluminum oxide (Al<sub>2</sub>O<sub>3</sub>) particles were impacted onto St37 structural steel samples at different impact angles (30°, 60°, 90°) and different quantities (1, 2, 3 kg) to calculate erosion rates. DEM based simulation analyses were performed using the same parameters, and surface deformations were modelled. When compared with experimental data, the simulation results showed high convergence, particularly at high impact angles such as 60° and 90° (5–15 % deviation). However, deviations increased at low impact angles such as 30°. While DEM analyses can successfully predict surface embedment deformations, they have not been able to adequately reflect damage caused by ductile behavior such as sliding. The surface embedment effect has shown a similarity of around 5 % at high impact angles compared to experimental data. In addition, ANOVA tests were applied to the erosion rates found in experiments and simulations to statistically evaluate the results. The test results statistically revealed that the most effective variable on the erosion rate was the angle of impact (p < 0.0001). The results demonstrate that the discrete element method is a reliable approach for modeling solid particle erosion wear behavior and, when used in conjunction with experimental data, can provide effective solutions for predicting and preventing erosion-induced damage during the design phase in systems such as jet engine turbines, space applications, and dust particle interaction engineering problems.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"107 ","pages":"Pages 134-156"},"PeriodicalIF":4.7000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Particuology","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1674200125002688","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/10/17 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The Discrete Element Method (DEM) stands out as an effective computational tool for modeling complex mechanical wear processes such as solid particle erosion. The DEM method offers significant advantages in terms of providing realistic results, particularly when it comes to examining particle and surface interactions over time and predicting surface deformations. In this study, the effectiveness of DEM in determining the solid particle erosion wear behavior was evaluated by comparing it with experimental data. In the experimental phase, aluminum oxide (Al2O3) particles were impacted onto St37 structural steel samples at different impact angles (30°, 60°, 90°) and different quantities (1, 2, 3 kg) to calculate erosion rates. DEM based simulation analyses were performed using the same parameters, and surface deformations were modelled. When compared with experimental data, the simulation results showed high convergence, particularly at high impact angles such as 60° and 90° (5–15 % deviation). However, deviations increased at low impact angles such as 30°. While DEM analyses can successfully predict surface embedment deformations, they have not been able to adequately reflect damage caused by ductile behavior such as sliding. The surface embedment effect has shown a similarity of around 5 % at high impact angles compared to experimental data. In addition, ANOVA tests were applied to the erosion rates found in experiments and simulations to statistically evaluate the results. The test results statistically revealed that the most effective variable on the erosion rate was the angle of impact (p < 0.0001). The results demonstrate that the discrete element method is a reliable approach for modeling solid particle erosion wear behavior and, when used in conjunction with experimental data, can provide effective solutions for predicting and preventing erosion-induced damage during the design phase in systems such as jet engine turbines, space applications, and dust particle interaction engineering problems.
期刊介绍:
The word ‘particuology’ was coined to parallel the discipline for the science and technology of particles.
Particuology is an interdisciplinary journal that publishes frontier research articles and critical reviews on the discovery, formulation and engineering of particulate materials, processes and systems. It especially welcomes contributions utilising advanced theoretical, modelling and measurement methods to enable the discovery and creation of new particulate materials, and the manufacturing of functional particulate-based products, such as sensors.
Papers are handled by Thematic Editors who oversee contributions from specific subject fields. These fields are classified into: Particle Synthesis and Modification; Particle Characterization and Measurement; Granular Systems and Bulk Solids Technology; Fluidization and Particle-Fluid Systems; Aerosols; and Applications of Particle Technology.
Key topics concerning the creation and processing of particulates include:
-Modelling and simulation of particle formation, collective behaviour of particles and systems for particle production over a broad spectrum of length scales
-Mining of experimental data for particle synthesis and surface properties to facilitate the creation of new materials and processes
-Particle design and preparation including controlled response and sensing functionalities in formation, delivery systems and biological systems, etc.
-Experimental and computational methods for visualization and analysis of particulate system.
These topics are broadly relevant to the production of materials, pharmaceuticals and food, and to the conversion of energy resources to fuels and protection of the environment.