Jacob Yager, Joshua E. Woods, Neil A. Hoult, Evan C. Bentz
{"title":"表征混凝土张力模量,软化,和加强使用分布式传感","authors":"Jacob Yager, Joshua E. Woods, Neil A. Hoult, Evan C. Bentz","doi":"10.1617/s11527-025-02655-4","DOIUrl":null,"url":null,"abstract":"<div><p>To design and assess reinforced concrete (RC) structures more accurately thus enabling more efficient use of materials, improved material models are required. Distributed sensing technologies have the potential to provide the data to support the development of these improved models. In this study, twelve specimens with varying types of concrete and reinforcement ratios were monitored with distributed fibre optic sensors (DFOS) and digital image correlation (DIC) while being loaded in direct tension. Strain data from DFOS and crack width data from DIC were used to quantify three material models required for accurate analysis: the concrete Young’s modulus prior to cracking, tension softening, and average and distributed tension stiffening. The results showed that the uncracked concrete stress–strain response was non-linear leading to a non-linear Young’s modulus. Reinforcement ratio was found to influence cracking strength, tension stiffening, and tension softening, which many current models do not consider. Tension softening was observed at larger surface crack widths than in plain concrete that form the basis for existing tension softening models. Lastly, crack spacing was found to influence tension stiffening behaviour. Each of these findings suggest that current models do not fully capture the behaviour of RC and that there are opportunities to improve RC analysis techniques.</p></div>","PeriodicalId":691,"journal":{"name":"Materials and Structures","volume":"58 4","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Characterization of concrete tension modulus, softening, and stiffening using distributed sensing\",\"authors\":\"Jacob Yager, Joshua E. Woods, Neil A. Hoult, Evan C. Bentz\",\"doi\":\"10.1617/s11527-025-02655-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>To design and assess reinforced concrete (RC) structures more accurately thus enabling more efficient use of materials, improved material models are required. Distributed sensing technologies have the potential to provide the data to support the development of these improved models. In this study, twelve specimens with varying types of concrete and reinforcement ratios were monitored with distributed fibre optic sensors (DFOS) and digital image correlation (DIC) while being loaded in direct tension. Strain data from DFOS and crack width data from DIC were used to quantify three material models required for accurate analysis: the concrete Young’s modulus prior to cracking, tension softening, and average and distributed tension stiffening. The results showed that the uncracked concrete stress–strain response was non-linear leading to a non-linear Young’s modulus. Reinforcement ratio was found to influence cracking strength, tension stiffening, and tension softening, which many current models do not consider. Tension softening was observed at larger surface crack widths than in plain concrete that form the basis for existing tension softening models. Lastly, crack spacing was found to influence tension stiffening behaviour. Each of these findings suggest that current models do not fully capture the behaviour of RC and that there are opportunities to improve RC analysis techniques.</p></div>\",\"PeriodicalId\":691,\"journal\":{\"name\":\"Materials and Structures\",\"volume\":\"58 4\",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials and Structures\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1617/s11527-025-02655-4\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials and Structures","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1617/s11527-025-02655-4","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Characterization of concrete tension modulus, softening, and stiffening using distributed sensing
To design and assess reinforced concrete (RC) structures more accurately thus enabling more efficient use of materials, improved material models are required. Distributed sensing technologies have the potential to provide the data to support the development of these improved models. In this study, twelve specimens with varying types of concrete and reinforcement ratios were monitored with distributed fibre optic sensors (DFOS) and digital image correlation (DIC) while being loaded in direct tension. Strain data from DFOS and crack width data from DIC were used to quantify three material models required for accurate analysis: the concrete Young’s modulus prior to cracking, tension softening, and average and distributed tension stiffening. The results showed that the uncracked concrete stress–strain response was non-linear leading to a non-linear Young’s modulus. Reinforcement ratio was found to influence cracking strength, tension stiffening, and tension softening, which many current models do not consider. Tension softening was observed at larger surface crack widths than in plain concrete that form the basis for existing tension softening models. Lastly, crack spacing was found to influence tension stiffening behaviour. Each of these findings suggest that current models do not fully capture the behaviour of RC and that there are opportunities to improve RC analysis techniques.
期刊介绍:
Materials and Structures, the flagship publication of the International Union of Laboratories and Experts in Construction Materials, Systems and Structures (RILEM), provides a unique international and interdisciplinary forum for new research findings on the performance of construction materials. A leader in cutting-edge research, the journal is dedicated to the publication of high quality papers examining the fundamental properties of building materials, their characterization and processing techniques, modeling, standardization of test methods, and the application of research results in building and civil engineering. Materials and Structures also publishes comprehensive reports prepared by the RILEM’s technical committees.