{"title":"从微观结构生成到氯离子扩散预测的混凝土氯离子迁移模型","authors":"Liang‐yu Tong, Qing‐feng Liu, Qingxiang Xiong, Zhaozheng Meng, Ouali Amiri, Mingzhong Zhang","doi":"10.1111/mice.13331","DOIUrl":null,"url":null,"abstract":"Pore structure characteristics of cementitious materials play a critical role in the transport properties of concrete structures. This paper develops a novel framework for modeling chloride penetration in concrete, considering the pore structure‐dependent model parameters. In the framework, a multi‐scale transport model was derived by linking the chloride diffusivities with pore size distributions (PSDs). Based on the three‐dimensional (3D) microstructure generated by “porous growth” and “hard core‐soft shell” methods, two sub‐models were computationally developed for determining the multi‐modal PSDs and pore size‐related chloride diffusivities. The predicted results by these series of models were compared with corresponding experimental data. The results indicated that by adopting pore size‐related diffusivities, even if the total porosities were the same, the proposed multi‐scale chloride transport model could better capture the effect of different PSDs on chloride penetration profiles, while the model without pore structure‐depended parameters would ignore the differences. Compared with the reference transport models, which adopt averaged chloride diffusivities, the chloride penetration depths predicted by the proposed multi‐scale model are in better agreement with experimental data, with 10%–25% reduced prediction error. This multi‐scale transport model is hoped to provide a novel computational approach on 3D microstructure generation and better reveal the underlying mechanism of the chloride penetration process in concrete from a microscopic perspective.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"29 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling the chloride transport in concrete from microstructure generation to chloride diffusivity prediction\",\"authors\":\"Liang‐yu Tong, Qing‐feng Liu, Qingxiang Xiong, Zhaozheng Meng, Ouali Amiri, Mingzhong Zhang\",\"doi\":\"10.1111/mice.13331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pore structure characteristics of cementitious materials play a critical role in the transport properties of concrete structures. This paper develops a novel framework for modeling chloride penetration in concrete, considering the pore structure‐dependent model parameters. In the framework, a multi‐scale transport model was derived by linking the chloride diffusivities with pore size distributions (PSDs). Based on the three‐dimensional (3D) microstructure generated by “porous growth” and “hard core‐soft shell” methods, two sub‐models were computationally developed for determining the multi‐modal PSDs and pore size‐related chloride diffusivities. The predicted results by these series of models were compared with corresponding experimental data. The results indicated that by adopting pore size‐related diffusivities, even if the total porosities were the same, the proposed multi‐scale chloride transport model could better capture the effect of different PSDs on chloride penetration profiles, while the model without pore structure‐depended parameters would ignore the differences. Compared with the reference transport models, which adopt averaged chloride diffusivities, the chloride penetration depths predicted by the proposed multi‐scale model are in better agreement with experimental data, with 10%–25% reduced prediction error. This multi‐scale transport model is hoped to provide a novel computational approach on 3D microstructure generation and better reveal the underlying mechanism of the chloride penetration process in concrete from a microscopic perspective.\",\"PeriodicalId\":156,\"journal\":{\"name\":\"Computer-Aided Civil and Infrastructure Engineering\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer-Aided Civil and Infrastructure Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1111/mice.13331\",\"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":"Computer-Aided Civil and Infrastructure Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1111/mice.13331","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}
Modeling the chloride transport in concrete from microstructure generation to chloride diffusivity prediction
Pore structure characteristics of cementitious materials play a critical role in the transport properties of concrete structures. This paper develops a novel framework for modeling chloride penetration in concrete, considering the pore structure‐dependent model parameters. In the framework, a multi‐scale transport model was derived by linking the chloride diffusivities with pore size distributions (PSDs). Based on the three‐dimensional (3D) microstructure generated by “porous growth” and “hard core‐soft shell” methods, two sub‐models were computationally developed for determining the multi‐modal PSDs and pore size‐related chloride diffusivities. The predicted results by these series of models were compared with corresponding experimental data. The results indicated that by adopting pore size‐related diffusivities, even if the total porosities were the same, the proposed multi‐scale chloride transport model could better capture the effect of different PSDs on chloride penetration profiles, while the model without pore structure‐depended parameters would ignore the differences. Compared with the reference transport models, which adopt averaged chloride diffusivities, the chloride penetration depths predicted by the proposed multi‐scale model are in better agreement with experimental data, with 10%–25% reduced prediction error. This multi‐scale transport model is hoped to provide a novel computational approach on 3D microstructure generation and better reveal the underlying mechanism of the chloride penetration process in concrete from a microscopic perspective.
期刊介绍:
Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms.
Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.