Xiaohua Bao , Zhizao Bao , Jun Shen , Xiangsheng Chen , Hongzhi Cui
{"title":"基于纤维影响范围的土壤-纤维排水循环加载试验模型的优化 DEM 建模方法","authors":"Xiaohua Bao , Zhizao Bao , Jun Shen , Xiangsheng Chen , Hongzhi Cui","doi":"10.1016/j.compgeo.2024.106846","DOIUrl":null,"url":null,"abstract":"<div><div>The computational cost of discrete element modelling is high owing to the limitations of particle size and contact in fibre modelling. This paper proposes an optimised discrete element method (DEM) for a hybrid model of soil and fibres based on the fibre influence range. First, a relative velocity state function is established based on the relative motion state between the fibres and soil particles under undrained cyclic loading. Subsequently, the influence range of the fibres is determined using the relative velocity function based on the first few cycles of the undrained cyclic loading numerical tests. Cluster and clump models of the fibre are then generated based on the influence range of the fibre. Finally, a symmetrical shape of the optimised model is developed by extracting the distribution length of the edge curve of the influence range along the vertical direction of the axis. In this study, the proposed optimised DEM was validated through a series of undrained cyclic loading numerical tests on fibre-reinforced soil. The results of the optimised model were highly consistent with those of the traditional model, and the computational time was significantly reduced. The cyclic loading timing for determining the range of influence of the fibre was analysed. The optimised model based on the influence range of the 15th cycles not only restored almost the same results but also saved the calculation cost by nearly eight times. The optimised model established based on the influence range after the 15th cycles had a slight influence on the results. In addition, the applicability of the optimised model is discussed. This paper provides new insights into the establishment of a hybrid model of soil and fibres.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106846"},"PeriodicalIF":5.3000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An optimization DEM modelling method for soil-fibre undrained cyclic loading tests model based on the influence range of fibre\",\"authors\":\"Xiaohua Bao , Zhizao Bao , Jun Shen , Xiangsheng Chen , Hongzhi Cui\",\"doi\":\"10.1016/j.compgeo.2024.106846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The computational cost of discrete element modelling is high owing to the limitations of particle size and contact in fibre modelling. This paper proposes an optimised discrete element method (DEM) for a hybrid model of soil and fibres based on the fibre influence range. First, a relative velocity state function is established based on the relative motion state between the fibres and soil particles under undrained cyclic loading. Subsequently, the influence range of the fibres is determined using the relative velocity function based on the first few cycles of the undrained cyclic loading numerical tests. Cluster and clump models of the fibre are then generated based on the influence range of the fibre. Finally, a symmetrical shape of the optimised model is developed by extracting the distribution length of the edge curve of the influence range along the vertical direction of the axis. In this study, the proposed optimised DEM was validated through a series of undrained cyclic loading numerical tests on fibre-reinforced soil. The results of the optimised model were highly consistent with those of the traditional model, and the computational time was significantly reduced. The cyclic loading timing for determining the range of influence of the fibre was analysed. The optimised model based on the influence range of the 15th cycles not only restored almost the same results but also saved the calculation cost by nearly eight times. The optimised model established based on the influence range after the 15th cycles had a slight influence on the results. In addition, the applicability of the optimised model is discussed. This paper provides new insights into the establishment of a hybrid model of soil and fibres.</div></div>\",\"PeriodicalId\":55217,\"journal\":{\"name\":\"Computers and Geotechnics\",\"volume\":\"177 \",\"pages\":\"Article 106846\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Geotechnics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0266352X24007857\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Geotechnics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0266352X24007857","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
An optimization DEM modelling method for soil-fibre undrained cyclic loading tests model based on the influence range of fibre
The computational cost of discrete element modelling is high owing to the limitations of particle size and contact in fibre modelling. This paper proposes an optimised discrete element method (DEM) for a hybrid model of soil and fibres based on the fibre influence range. First, a relative velocity state function is established based on the relative motion state between the fibres and soil particles under undrained cyclic loading. Subsequently, the influence range of the fibres is determined using the relative velocity function based on the first few cycles of the undrained cyclic loading numerical tests. Cluster and clump models of the fibre are then generated based on the influence range of the fibre. Finally, a symmetrical shape of the optimised model is developed by extracting the distribution length of the edge curve of the influence range along the vertical direction of the axis. In this study, the proposed optimised DEM was validated through a series of undrained cyclic loading numerical tests on fibre-reinforced soil. The results of the optimised model were highly consistent with those of the traditional model, and the computational time was significantly reduced. The cyclic loading timing for determining the range of influence of the fibre was analysed. The optimised model based on the influence range of the 15th cycles not only restored almost the same results but also saved the calculation cost by nearly eight times. The optimised model established based on the influence range after the 15th cycles had a slight influence on the results. In addition, the applicability of the optimised model is discussed. This paper provides new insights into the establishment of a hybrid model of soil and fibres.
期刊介绍:
The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.