Hybrid FRP strengthening of reinforced concrete deep beams: Experimental, theoretical and machine learning-based study

IF 6.5 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Case Studies in Construction Materials Pub Date : 2024-12-07 DOI:10.1016/j.cscm.2024.e04057
Phromphat Thansirichaisree , Qudeer Hussain , Mingliang Zhou , Ali Ejaz , Shabbir Ali Talpur , Panumas Saingam
{"title":"Hybrid FRP strengthening of reinforced concrete deep beams: Experimental, theoretical and machine learning-based study","authors":"Phromphat Thansirichaisree ,&nbsp;Qudeer Hussain ,&nbsp;Mingliang Zhou ,&nbsp;Ali Ejaz ,&nbsp;Shabbir Ali Talpur ,&nbsp;Panumas Saingam","doi":"10.1016/j.cscm.2024.e04057","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents experimental findings from testing seventeen reinforced concrete deep beams, categorized into four groups based on the presence and type of openings. A novel and cost-effective hybrid strengthening scheme is proposed comprising glass chopped mat sheets and eco-friendly basalt FRP sheets (GF-BFRP). Group 1 consisted of solid beams without openings, while Group 2 included beams with circular openings, Group 3 with square openings, and Group 4 with rectangular openings of varying dimensions. Each group comprised beams tested in various strengthening configurations using GF-BFRP layers with and without anchor support. Analysis of failure modes revealed initial flexural cracking in control beams, with beams containing openings exhibiting diagonal cracking and reduced shear capacity. Results revealed that beams with openings experienced a significant reduction in shear capacity. Circular, square, and rectangular openings reduced peak capacity by 26.11 %, 30.67 %, and 31.91 %, respectively, while rectangular openings oriented vertically caused the most substantial reduction at 47.46 %. Strengthening using a single GF-BFRP sheet led to debonding, which was mitigated by anchors, enhancing confinement and reducing diagonal cracking. However, strengthened beams did not recover the original strength of the solid beam, which reached a peak load of 245.51 kN. For instance, the C-W1-A beam achieved a peak load of 173.58 kN, which was 4.31 % lower than its control beam due to the extensive anchor installation. Evaluation of predictive models for shear capacity highlighted discrepancies. None of the existing codes provide expressions that account for the shear contributions of externally bonded FRP systems on beams with opening shape and size implicitly defined. To overcome this issue, machine learning approaches were utilized, employing gradient boosting regression and random forest methods. Data on deep beams, both with and without openings (and without strengthening), was collected from eight studies. The models were trained on this dataset, and predictions were made based on the results of this study. While the gradient boosting regression model tended to overestimate the peak capacity of the deep beams, the random forest model provided predictions that were much closer to the experimental results.</div></div>","PeriodicalId":9641,"journal":{"name":"Case Studies in Construction Materials","volume":"22 ","pages":"Article e04057"},"PeriodicalIF":6.5000,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies in Construction Materials","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214509524012099","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

This paper presents experimental findings from testing seventeen reinforced concrete deep beams, categorized into four groups based on the presence and type of openings. A novel and cost-effective hybrid strengthening scheme is proposed comprising glass chopped mat sheets and eco-friendly basalt FRP sheets (GF-BFRP). Group 1 consisted of solid beams without openings, while Group 2 included beams with circular openings, Group 3 with square openings, and Group 4 with rectangular openings of varying dimensions. Each group comprised beams tested in various strengthening configurations using GF-BFRP layers with and without anchor support. Analysis of failure modes revealed initial flexural cracking in control beams, with beams containing openings exhibiting diagonal cracking and reduced shear capacity. Results revealed that beams with openings experienced a significant reduction in shear capacity. Circular, square, and rectangular openings reduced peak capacity by 26.11 %, 30.67 %, and 31.91 %, respectively, while rectangular openings oriented vertically caused the most substantial reduction at 47.46 %. Strengthening using a single GF-BFRP sheet led to debonding, which was mitigated by anchors, enhancing confinement and reducing diagonal cracking. However, strengthened beams did not recover the original strength of the solid beam, which reached a peak load of 245.51 kN. For instance, the C-W1-A beam achieved a peak load of 173.58 kN, which was 4.31 % lower than its control beam due to the extensive anchor installation. Evaluation of predictive models for shear capacity highlighted discrepancies. None of the existing codes provide expressions that account for the shear contributions of externally bonded FRP systems on beams with opening shape and size implicitly defined. To overcome this issue, machine learning approaches were utilized, employing gradient boosting regression and random forest methods. Data on deep beams, both with and without openings (and without strengthening), was collected from eight studies. The models were trained on this dataset, and predictions were made based on the results of this study. While the gradient boosting regression model tended to overestimate the peak capacity of the deep beams, the random forest model provided predictions that were much closer to the experimental results.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
7.60
自引率
19.40%
发文量
842
审稿时长
63 days
期刊介绍: Case Studies in Construction Materials provides a forum for the rapid publication of short, structured Case Studies on construction materials. In addition, the journal also publishes related Short Communications, Full length research article and Comprehensive review papers (by invitation). The journal will provide an essential compendium of case studies for practicing engineers, designers, researchers and other practitioners who are interested in all aspects construction materials. The journal will publish new and novel case studies, but will also provide a forum for the publication of high quality descriptions of classic construction material problems and solutions.
期刊最新文献
Investigating the rheological properties and microstructural analysis of Nano-expanded Perlite modified asphalt binder Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network Study on the workability, strength, durability and environmental performance of alkali-activated electrolytic manganese slag-fly ash-slag grouting materials Energy consumption and carbon emissions of mixing plant in asphalt pavement construction with a case study in China and reduction measures Engineering properties and life cycle assessment of a rapidly clayey soil stabilizer utilizing alkali-activated GFRP waste powder and slag
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1