Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models
Textile reinforced mortars (TRMs) are new composite materials which were considered as a proper alternative for fiber reinforced polymers (FRPs) to strengthen various structural elements. In comparison to FRPs, the TRMs have more fire resistance, more environmental consistency and are safer the stru...
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Format: | Article |
Language: | English |
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Pouyan Press
2023-01-01
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Series: | Journal of Soft Computing in Civil Engineering |
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Online Access: | https://www.jsoftcivil.com/article_160799_61f58dc178858db7588e9afb76705a5a.pdf |
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author | Hashem Jahangir Zahra Nikkhah Danial Rezazadeh Eidgahee Mohammad Reza Esfahani |
author_facet | Hashem Jahangir Zahra Nikkhah Danial Rezazadeh Eidgahee Mohammad Reza Esfahani |
author_sort | Hashem Jahangir |
collection | DOAJ |
description | Textile reinforced mortars (TRMs) are new composite materials which were considered as a proper alternative for fiber reinforced polymers (FRPs) to strengthen various structural elements. In comparison to FRPs, the TRMs have more fire resistance, more environmental consistency and are safer the structural elements because of their better bond to substrate and various failure modes. There are a lot of existing models to calculate the bond strength between TRMs and concrete substrate. But, most of them originated from the FRP-concrete bond models and are not accurate enough to estimate the TRM-concrete bond strength. In this paper, new TRM-concrete bond models were calibrated to predict the bond strength between various TRM composites and the concrete substrate. To achieve this goal, a database including 221 experimental direct shear tests were compiled and a simple existing model was selected to be calibrated via soft computing techniques. It was found that the presented novel models could be accurately utilized to anticipate the TRM-concrete bond strength with various types of fibers and different geometrical features with R value of 0.6909 and NMAE error value of 12.62%. |
first_indexed | 2024-03-13T03:52:56Z |
format | Article |
id | doaj.art-809b116287bc44808e0483818158f561 |
institution | Directory Open Access Journal |
issn | 2588-2872 |
language | English |
last_indexed | 2024-03-13T03:52:56Z |
publishDate | 2023-01-01 |
publisher | Pouyan Press |
record_format | Article |
series | Journal of Soft Computing in Civil Engineering |
spelling | doaj.art-809b116287bc44808e0483818158f5612023-06-22T09:24:16ZengPouyan PressJournal of Soft Computing in Civil Engineering2588-28722023-01-0171435510.22115/scce.2022.349483.1476160799Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing ModelsHashem Jahangir0Zahra Nikkhah1Danial Rezazadeh Eidgahee2Mohammad Reza Esfahani3Assistant Professor, Department of Civil Engineering, University of Birjand, Birjand, IranM.Sc. Student, Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, IranProfessor of Structural Engineering, Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, IranTextile reinforced mortars (TRMs) are new composite materials which were considered as a proper alternative for fiber reinforced polymers (FRPs) to strengthen various structural elements. In comparison to FRPs, the TRMs have more fire resistance, more environmental consistency and are safer the structural elements because of their better bond to substrate and various failure modes. There are a lot of existing models to calculate the bond strength between TRMs and concrete substrate. But, most of them originated from the FRP-concrete bond models and are not accurate enough to estimate the TRM-concrete bond strength. In this paper, new TRM-concrete bond models were calibrated to predict the bond strength between various TRM composites and the concrete substrate. To achieve this goal, a database including 221 experimental direct shear tests were compiled and a simple existing model was selected to be calibrated via soft computing techniques. It was found that the presented novel models could be accurately utilized to anticipate the TRM-concrete bond strength with various types of fibers and different geometrical features with R value of 0.6909 and NMAE error value of 12.62%.https://www.jsoftcivil.com/article_160799_61f58dc178858db7588e9afb76705a5a.pdftextile reinforced mortar (trm)fiber reinforced polymer (frp)bond strengthcalibration processsoft computing techniques |
spellingShingle | Hashem Jahangir Zahra Nikkhah Danial Rezazadeh Eidgahee Mohammad Reza Esfahani Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models Journal of Soft Computing in Civil Engineering textile reinforced mortar (trm) fiber reinforced polymer (frp) bond strength calibration process soft computing techniques |
title | Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models |
title_full | Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models |
title_fullStr | Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models |
title_full_unstemmed | Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models |
title_short | Performance Based Review and Fine-Tuning of TRM-Concrete Bond Strength Existing Models |
title_sort | performance based review and fine tuning of trm concrete bond strength existing models |
topic | textile reinforced mortar (trm) fiber reinforced polymer (frp) bond strength calibration process soft computing techniques |
url | https://www.jsoftcivil.com/article_160799_61f58dc178858db7588e9afb76705a5a.pdf |
work_keys_str_mv | AT hashemjahangir performancebasedreviewandfinetuningoftrmconcretebondstrengthexistingmodels AT zahranikkhah performancebasedreviewandfinetuningoftrmconcretebondstrengthexistingmodels AT danialrezazadeheidgahee performancebasedreviewandfinetuningoftrmconcretebondstrengthexistingmodels AT mohammadrezaesfahani performancebasedreviewandfinetuningoftrmconcretebondstrengthexistingmodels |