Article(id=1320090311930532683, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1320090269345755891, articleNumber=null, orderNo=null, doi=10.14062/j.issn.0454-5648.20240474, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1721318400000, receivedDateStr=2024-07-19, revisedDate=1725724800000, revisedDateStr=2024-09-08, acceptedDate=null, acceptedDateStr=null, onlineDate=1792663656455, onlineDateStr=2026-10-22, pubDate=1737302400000, pubDateStr=2025-01-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792663656455, onlineIssueDateStr=2026-10-22, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792663656455, creator=13701087609, updateTime=1792663656455, updator=13701087609, issue=Issue{id=1320090269345755891, tenantId=1146029695717560320, journalId=1263187385517883426, year='2025', volume='53', issue='1', pageStart='1', pageEnd='240', issueExtLink='null', onlineDate='null', pubDate='1737302400000', pubDateStr='2025-01-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792663646303, creator='13701087609', updateTime=1792663867433, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320091196899307738, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1320090269345755891, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320091196899307739, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1320090269345755891, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=173, endPage=189, ext={EN=ArticleExt(id=1320090312144442188, articleId=1320090311930532683, tenantId=1146029695717560320, journalId=1263187385517883426, language=EN, title=Progress on Multi-Scale Simulation on Tensile Cracking Behavior of Engineered Cementitious Composites, columnId=1263922772401635899, journalTitle=Journal of the Chinese Ceramic Society, columnName=Review, runingTitle=null, highlight=null, articleAbstract=

Engineered cementitious composites (ECC) are widely used in masonry structure reinforcement, bridge deck connection and structural repair due to the strain hardening and multi-crack cracking characteristics, which can overcome some shortcomings as poor ductility and weak crack control ability from ordinary concrete. The existing mechanism analysis for concrete fracture mechanics is mainly based on the micro- and macro-experimental results. Although a research can obtain experimental data, the experimental process and result analysis are time-consuming and labor-intensive, and there is a huge deviation between the experimental results and the intended target. Computer simulation provides an effective research tool for accurately analyzing the working mechanism of cement-based composites. Computer simulation can accurately predict and deeply analyze the experiment results due to the advantages of high efficiency, visualization and low cost, which helps to better understand the achievement criteria of special properties for cement-based composites. The related research on the nano-, meso-, and macro-scopic cracking characteristics during the tensile process of ECC by computer simulation technologies in different scales becomes popular. However, there are a few systematic work for the characteristics, differences and correlations of different scale simulation methods on ECC.

In the nano-scale simulation of ECC, the molecular dynamics (MD) can analyze the influence mechanism of unmodified fiber and modified fiber on the bonding performance at fiber-matrix interface during ECC deformation from the molecular or atomic level. MD can be used to establish the fiber/C-S-H interface molecular model, which can visually display the fiber-matrix interface bonding, and reveal that the interface bonding between unmodified/modified fibers, and C-S-H gel can be achieved via forming polymer, electrostatic interaction, chemical bond, hydrogen bond and the van der Waals force.

In the mesoscopic scale simulation of ECC, the numerical (finite element) simulation can analyze the influence of macroscopic and mesoscopic factors such as fiber, matrix and their interface on the tensile strain hardening behavior of ECC. Firstly, the mesoscopic scale model-the lattice discrete particle model can analyze the influences fiber type and dosage. Secondly, crack propagation mode I can simulate the influence of matrix characteristics such as matrix internal pore structure and matrix fracture toughness. A numerical (finite element) model is established to simulate the single fiber pullout process to analyze the influence of fiber-matrix interface parameters on the tensile properties of ECC. The ECC tensile finite element model is proposed to analyze the influence of sample shape and size on the tensile properties of ECC.

In the macroscale simulation of ECC, there are a few studies on the multi-crack cracking characteristics of ECC from peridynamic (PD) simulation. The fiber-matrix interaction using PD is simulated to investigate the discontinuous cracking process of ECC, or predict the maximum tensile strain of fiber reinforced cementitious composites, indicating the feasibility of PD simulation in this aspect. In addition, this review introduces how to establish an artificial neural network (ANN) prediction model to achieve concrete mix ratio design, predict the correlation between relevant parameters and mechanical properties, and extend the ANN model to the prediction of ECC micro-mechanical properties indicators.

Summary and prospects

This review represents the research status of four types of simulation technologies according to nano-, meso-, and macro-scale in tensile cracking behavior of ECC. In the nanoscale simulation of ECC, MD can be used to analyze the bonding performance of fiber-matrix interface by virtue of its visualization advantage for molecular/atomic interaction. Using MD model in the molecular or atomic level for investigation of the interface interaction between unmodified/modified fibers and C-S-H gel is enhanced via forming hydrogen bonds, the van der Waals forces, etc., or filling nanopores and bridging nanocracks with nanomaterials, thus improving the tensile properties of ECC. However, the MD simulation on the fiber-matrix interface performance after ECC cracking and the crack propagation behavior is lack. For the mesoscopic scale simulation of ECC, the numerical (finite element) model based on meso-mechanics shows that the uneven dispersion of fibers can reduce the ultimate tensile strain and ultimate tensile strength of ECC, and show that the tensile strain and tensile strength of ECC decrease with the increase of sample width and thickness. However, there is a lack on numerical (finite element) simulation for the tensile strain of ECC from the perspective of the close packing of mortar matrix particles. In the macroscale simulation of ECC, PD can be used to solve the discontinuous cracking problem of micro-/macro-mechanics of cement-based materials. However, the stress transfer between fiber and matrix during ECC multi-cracks cracking and the prediction of crack propagation path after loading are rarely involved. The ANN model can predict the basic mechanical property indexes of ECC and the stress-strain curve of FRC, and optimize the concrete mix proportion. When it is combined with a genetic algorithm to predict the compressive strength, slump and interfacial bond strength of concrete, the prediction accuracy becomes greater. However, the ANN prediction model on ECC micro-mechanical indicators is not reported. In addition, it is also crucial for the improvement of the prediction accuracy and efficiency of computer models to explore how to achieve two-path intelligent optimization of input parameters and prediction targets.

, authors=Dongyi LEI1, Zhiying WU1, Haoxuan JIA1, Long YU1, Bing WANG1, Jinhui TANG2, Ying LI1, Yanlong LI3, Jiaping LIU2, authorsList=Dongyi LEI, Zhiying WU, Haoxuan JIA, Long YU, Bing WANG, Jinhui TANG, Ying LI, Yanlong LI, Jiaping LIU, authorCompany=null, correspAuthors=Ying LI, authorNote=

LEI Dongyi (1986-), male, Ph.D., Associate Professor. E-mail:

, correspAuthorsNote=
LI Ying (1988-), female, Ph.D., Associate Professor. E-mail:
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高延性水泥基复合材料(ECC)克服了普通混凝土延性差、裂缝控制能力弱的缺点,当前针对混凝土断裂力学的机理分析主要依据微、宏观试验数据进行,但该过程耗时耗力且无法直观展示开裂过程中纤维-基体间的应力传递及异相物质间的分子或原子交互作用,而计算机模拟技术凭借高效、可视化、低成本的优势为精准预测、深入分析试验结果提供了强力支撑。为全面了解当前ECC拉伸开裂行为多尺度模拟的研究现状,将分子动力学、数值模拟(有限元模拟)、近场动力学和人工神经网络按纳、介、宏观3类尺度、4类方法分类概述其对ECC拉伸开裂行为的模拟。纳观尺度方面,分子动力学从分子或原子层面出发,着重分析未改性及改性纤维对ECC变形过程中纤维-基体界面结合性能的影响机理。介观尺度方面,数值(有限元)模拟重点关注纤维、基体及其界面特性等宏、细观因素对ECC拉伸应变硬化行为的影响规律。宏观尺度方面:近场动力学模拟针对ECC多缝开裂特性研究较少,其主要基于非局部作用分析了普通及纤维增强混凝土在不同方向荷载下的开裂演化行为;人工神经网络对ECC的力学性能预测有一定研究,但该方法主要通过建立预测模型,实现混凝土配合比设计并预测相关参数与力学性能之间的关联性。同时,论述了4种模拟技术在ECC拉伸开裂行为中的不足及发展趋势。

, authors=雷东移1, 武志盈1, 贾昊瑄1, 于龙1, 王冰1, 汤金辉2, 李莹1, 李炎隆3, 刘加平2, authorsList=雷东移, 武志盈, 贾昊瑄, 于龙, 王冰, 汤金辉, 李莹, 李炎隆, 刘加平, authorCompany=null, correspAuthors=李莹, authorNote=

雷东移(1986—),男,博士,副教授。

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李莹(1988—),女,博士,副教授。
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高延性水泥基复合材料拉伸开裂行为多尺度模拟研究进展
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雷东移 1 , 武志盈 1 , 贾昊瑄 1 , 于龙 1 , 王冰 1 , 汤金辉 2 , 李莹 1 , 李炎隆 3 , 刘加平 2
硅酸盐学报 | 综合评述 2025,53(1): 173-189
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硅酸盐学报 |综合评述 2025 , 53 (1) : 173 -189
高延性水泥基复合材料拉伸开裂行为多尺度模拟研究进展
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雷东移1 , 武志盈1, 贾昊瑄1, 于龙1, 王冰1, 汤金辉2, 李莹1 , 李炎隆3, 刘加平2
作者信息
  • 1.青岛理工大学土木工程学院,海洋环境混凝土技术教育部工程研究中心,山东 青岛 266520
  • 2.东南大学材料科学与工程学院,南京 211189
  • 3.西安理工大学水利水电学院,西安 710048
通讯作者:
李莹(1988—),女,博士,副教授。
作者简介:

雷东移(1986—),男,博士,副教授。

Progress on Multi-Scale Simulation on Tensile Cracking Behavior of Engineered Cementitious Composites
Dongyi LEI1 , Zhiying WU1, Haoxuan JIA1, Long YU1, Bing WANG1, Jinhui TANG2, Ying LI1 , Yanlong LI3, Jiaping LIU2
Affiliations
  • 1.Department of Civil Engineering, Engineering Research Center of Concrete Technology under Marine Environment, Ministry of Education, Qingdao University of Technology, Qingdao 266520, Shandong, China
  • 2.School of Materials Science and Engineering, Southeast University, Nanjing 211189, China
  • 3.School of Water Resources and Hydropower, Xi'an University of Technology, Xi'an 710048, China
  • Corresponding Author:
    LI Ying (1988-), female, Ph.D., Associate Professor. E-mail:

    LEI Dongyi (1986-), male, Ph.D., Associate Professor. E-mail:

出版时间: 2025-01-20 doi: 10.14062/j.issn.0454-5648.20240474
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高延性水泥基复合材料(ECC)克服了普通混凝土延性差、裂缝控制能力弱的缺点,当前针对混凝土断裂力学的机理分析主要依据微、宏观试验数据进行,但该过程耗时耗力且无法直观展示开裂过程中纤维-基体间的应力传递及异相物质间的分子或原子交互作用,而计算机模拟技术凭借高效、可视化、低成本的优势为精准预测、深入分析试验结果提供了强力支撑。为全面了解当前ECC拉伸开裂行为多尺度模拟的研究现状,将分子动力学、数值模拟(有限元模拟)、近场动力学和人工神经网络按纳、介、宏观3类尺度、4类方法分类概述其对ECC拉伸开裂行为的模拟。纳观尺度方面,分子动力学从分子或原子层面出发,着重分析未改性及改性纤维对ECC变形过程中纤维-基体界面结合性能的影响机理。介观尺度方面,数值(有限元)模拟重点关注纤维、基体及其界面特性等宏、细观因素对ECC拉伸应变硬化行为的影响规律。宏观尺度方面:近场动力学模拟针对ECC多缝开裂特性研究较少,其主要基于非局部作用分析了普通及纤维增强混凝土在不同方向荷载下的开裂演化行为;人工神经网络对ECC的力学性能预测有一定研究,但该方法主要通过建立预测模型,实现混凝土配合比设计并预测相关参数与力学性能之间的关联性。同时,论述了4种模拟技术在ECC拉伸开裂行为中的不足及发展趋势。

高延性  /  拉伸应变硬化  /  分子动力学  /  数值(有限元)  /  近场动力学  /  人工神经网络

Engineered cementitious composites (ECC) are widely used in masonry structure reinforcement, bridge deck connection and structural repair due to the strain hardening and multi-crack cracking characteristics, which can overcome some shortcomings as poor ductility and weak crack control ability from ordinary concrete. The existing mechanism analysis for concrete fracture mechanics is mainly based on the micro- and macro-experimental results. Although a research can obtain experimental data, the experimental process and result analysis are time-consuming and labor-intensive, and there is a huge deviation between the experimental results and the intended target. Computer simulation provides an effective research tool for accurately analyzing the working mechanism of cement-based composites. Computer simulation can accurately predict and deeply analyze the experiment results due to the advantages of high efficiency, visualization and low cost, which helps to better understand the achievement criteria of special properties for cement-based composites. The related research on the nano-, meso-, and macro-scopic cracking characteristics during the tensile process of ECC by computer simulation technologies in different scales becomes popular. However, there are a few systematic work for the characteristics, differences and correlations of different scale simulation methods on ECC.

In the nano-scale simulation of ECC, the molecular dynamics (MD) can analyze the influence mechanism of unmodified fiber and modified fiber on the bonding performance at fiber-matrix interface during ECC deformation from the molecular or atomic level. MD can be used to establish the fiber/C-S-H interface molecular model, which can visually display the fiber-matrix interface bonding, and reveal that the interface bonding between unmodified/modified fibers, and C-S-H gel can be achieved via forming polymer, electrostatic interaction, chemical bond, hydrogen bond and the van der Waals force.

In the mesoscopic scale simulation of ECC, the numerical (finite element) simulation can analyze the influence of macroscopic and mesoscopic factors such as fiber, matrix and their interface on the tensile strain hardening behavior of ECC. Firstly, the mesoscopic scale model-the lattice discrete particle model can analyze the influences fiber type and dosage. Secondly, crack propagation mode I can simulate the influence of matrix characteristics such as matrix internal pore structure and matrix fracture toughness. A numerical (finite element) model is established to simulate the single fiber pullout process to analyze the influence of fiber-matrix interface parameters on the tensile properties of ECC. The ECC tensile finite element model is proposed to analyze the influence of sample shape and size on the tensile properties of ECC.

In the macroscale simulation of ECC, there are a few studies on the multi-crack cracking characteristics of ECC from peridynamic (PD) simulation. The fiber-matrix interaction using PD is simulated to investigate the discontinuous cracking process of ECC, or predict the maximum tensile strain of fiber reinforced cementitious composites, indicating the feasibility of PD simulation in this aspect. In addition, this review introduces how to establish an artificial neural network (ANN) prediction model to achieve concrete mix ratio design, predict the correlation between relevant parameters and mechanical properties, and extend the ANN model to the prediction of ECC micro-mechanical properties indicators.

Summary and prospects

This review represents the research status of four types of simulation technologies according to nano-, meso-, and macro-scale in tensile cracking behavior of ECC. In the nanoscale simulation of ECC, MD can be used to analyze the bonding performance of fiber-matrix interface by virtue of its visualization advantage for molecular/atomic interaction. Using MD model in the molecular or atomic level for investigation of the interface interaction between unmodified/modified fibers and C-S-H gel is enhanced via forming hydrogen bonds, the van der Waals forces, etc., or filling nanopores and bridging nanocracks with nanomaterials, thus improving the tensile properties of ECC. However, the MD simulation on the fiber-matrix interface performance after ECC cracking and the crack propagation behavior is lack. For the mesoscopic scale simulation of ECC, the numerical (finite element) model based on meso-mechanics shows that the uneven dispersion of fibers can reduce the ultimate tensile strain and ultimate tensile strength of ECC, and show that the tensile strain and tensile strength of ECC decrease with the increase of sample width and thickness. However, there is a lack on numerical (finite element) simulation for the tensile strain of ECC from the perspective of the close packing of mortar matrix particles. In the macroscale simulation of ECC, PD can be used to solve the discontinuous cracking problem of micro-/macro-mechanics of cement-based materials. However, the stress transfer between fiber and matrix during ECC multi-cracks cracking and the prediction of crack propagation path after loading are rarely involved. The ANN model can predict the basic mechanical property indexes of ECC and the stress-strain curve of FRC, and optimize the concrete mix proportion. When it is combined with a genetic algorithm to predict the compressive strength, slump and interfacial bond strength of concrete, the prediction accuracy becomes greater. However, the ANN prediction model on ECC micro-mechanical indicators is not reported. In addition, it is also crucial for the improvement of the prediction accuracy and efficiency of computer models to explore how to achieve two-path intelligent optimization of input parameters and prediction targets.

high ductility  /  tensile strain hardening  /  molecular dynamics  /  numerical (finite element)  /  peridynamics  /  artificial neural network
雷东移, 武志盈, 贾昊瑄, 于龙, 王冰, 汤金辉, 李莹, 李炎隆, 刘加平. 高延性水泥基复合材料拉伸开裂行为多尺度模拟研究进展. 硅酸盐学报, 2025 , 53 (1) : 173 -189 . DOI: 10.14062/j.issn.0454-5648.20240474
Dongyi LEI, Zhiying WU, Haoxuan JIA, Long YU, Bing WANG, Jinhui TANG, Ying LI, Yanlong LI, Jiaping LIU. Progress on Multi-Scale Simulation on Tensile Cracking Behavior of Engineered Cementitious Composites[J]. Journal of the Chinese Ceramic Society, 2025 , 53 (1) : 173 -189 . DOI: 10.14062/j.issn.0454-5648.20240474
  • 国家自然科学基金(U23A20673; 52478261; U22A20244)
  • 中国博士后科学基金面上项目(2024M750580)
  • 青岛西海岸新区科技计划惠民专项(2022-41; 2021-102)
  • 青创科技支持计划(2021KJ045)
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doi: 10.14062/j.issn.0454-5648.20240474
  • 接收时间:2024-07-19
  • 首发时间:2026-10-22
  • 出版时间:2025-01-20
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  • 收稿日期:2024-07-19
  • 修回日期:2024-09-08
基金
国家自然科学基金(U23A20673; 52478261; U22A20244)
中国博士后科学基金面上项目(2024M750580)
青岛西海岸新区科技计划惠民专项(2022-41; 2021-102)
青创科技支持计划(2021KJ045)
作者信息
    1.青岛理工大学土木工程学院,海洋环境混凝土技术教育部工程研究中心,山东 青岛 266520
    2.东南大学材料科学与工程学院,南京 211189
    3.西安理工大学水利水电学院,西安 710048

通讯作者:

李莹(1988—),女,博士,副教授。
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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