Zesen Peng, Qing-feng Liu, Xuan Gao, Xin-Yu Zhao, Jin Xia, Qing-xiang Xiong
{"title":"Effects of aggregate distribution on the cracking behavior of concrete: A discrete element method study","authors":"Zesen Peng, Qing-feng Liu, Xuan Gao, Xin-Yu Zhao, Jin Xia, Qing-xiang Xiong","doi":"10.1016/j.cemconcomp.2025.106119","DOIUrl":null,"url":null,"abstract":"The aggregate distribution in concrete significantly influences the location of Interfacial Transition Zones (ITZs), impacting the initiation and propagation paths of cracks and complicating the prediction of concrete’s cracking behavior. To figure out the effects of aggregate distribution on concrete crack features, this study constructs a porosity-based heterogeneous model using the Discrete Element Method (DEM), considering the weak mechanical properties within the ITZs to accurately represent concrete crack evolution. Statistical analysis is then conducted to investigate the effects of aggregate distribution on the uniaxial compressive performance of concrete. The results indicate a linear relationship between the average compressive stress increment and the cracking proportion during the inelastic stage of concrete. Cracks are less likely to form between aggregates that are distributed along the loading direction. Furthermore, the length and endpoint positions of cracks between each pair of aggregates are determined within a specific range. Based on these statistical results, a crack prediction algorithm is proposed, and its key parameters are determined. Comparing the predicted crack patterns with those obtained from DEM modeling results demonstrates the algorithm’s accuracy in predicting the primary cracks in concrete subjected to uniaxial compression. This study hopes to provide a reference for predicting crack features in concrete with different aggregate distributions, facilitating more accurate assessments of structural damage and enhancing the safety and service life of concrete structures.","PeriodicalId":519419,"journal":{"name":"Cement and Concrete Composites","volume":"117 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cement and Concrete Composites","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cemconcomp.2025.106119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The aggregate distribution in concrete significantly influences the location of Interfacial Transition Zones (ITZs), impacting the initiation and propagation paths of cracks and complicating the prediction of concrete’s cracking behavior. To figure out the effects of aggregate distribution on concrete crack features, this study constructs a porosity-based heterogeneous model using the Discrete Element Method (DEM), considering the weak mechanical properties within the ITZs to accurately represent concrete crack evolution. Statistical analysis is then conducted to investigate the effects of aggregate distribution on the uniaxial compressive performance of concrete. The results indicate a linear relationship between the average compressive stress increment and the cracking proportion during the inelastic stage of concrete. Cracks are less likely to form between aggregates that are distributed along the loading direction. Furthermore, the length and endpoint positions of cracks between each pair of aggregates are determined within a specific range. Based on these statistical results, a crack prediction algorithm is proposed, and its key parameters are determined. Comparing the predicted crack patterns with those obtained from DEM modeling results demonstrates the algorithm’s accuracy in predicting the primary cracks in concrete subjected to uniaxial compression. This study hopes to provide a reference for predicting crack features in concrete with different aggregate distributions, facilitating more accurate assessments of structural damage and enhancing the safety and service life of concrete structures.