A new bond-slip model for NSM FRP systems using cement-based adhesives through artificial neural networks (ANN)

Sareh Akbarpoor; Mohammadali Rezazadeh; Bahman Ghiassi; Fazel Khayatian; Keerthan Poologanathan; Honeyeh Ramezan Sefat; Marco Corradi

doi:10.1016/j.conbuildmat.2024.136034

A new bond-slip model for NSM FRP systems using cement-based adhesives through artificial neural networks (ANN)

Sareh Akbarpoor^*, Mohammadali Rezazadeh, Bahman Ghiassi, Fazel Khayatian, Keerthan Poologanathan, Honeyeh Ramezan Sefat, Marco Corradi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

42 Downloads (Pure)

Abstract

This paper introduced a novel Artificial Neural Networks (ANN)-based bond–slip model for the Near-surface mounted (NSM) FRP system using cement-based adhesives, as an alternative to epoxy adhesives due to their high-temperature resistance and moisture-durability problems, employing experimental data. Therefore, closed-form formulas were presented for key components of the bond-slip law, including maximum bond stress, corresponding slip, fracture energy, and post-peak branch, while taking important factors into account. Compared to available bond-slip laws, this innovative model demonstrates promising potential in predicting the bond behaviour, thereby enabling more efficient and reliable designs for the NSM FRP strengthening applications using cement-based adhesives.

Original language	English
Article number	136034
Pages (from-to)	1-28
Number of pages	28
Journal	Construction and Building Materials
Volume	427
Early online date	17 Apr 2024
DOIs	https://doi.org/10.1016/j.conbuildmat.2024.136034
Publication status	Published - 10 May 2024

Keywords

NSM FRP
Bond-slip law
Cement-based adhesives
Artificial Neural Networks
Concrete structures

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10.1016/j.conbuildmat.2024.136034Licence: CC BY

1-s2.0-S0950061824011759-mainFinal published version, 16.5 MBLicence: CC BY

Cite this

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title = "A new bond-slip model for NSM FRP systems using cement-based adhesives through artificial neural networks (ANN)",

abstract = "This paper introduced a novel Artificial Neural Networks (ANN)-based bond–slip model for the Near-surface mounted (NSM) FRP system using cement-based adhesives, as an alternative to epoxy adhesives due to their high-temperature resistance and moisture-durability problems, employing experimental data. Therefore, closed-form formulas were presented for key components of the bond-slip law, including maximum bond stress, corresponding slip, fracture energy, and post-peak branch, while taking important factors into account. Compared to available bond-slip laws, this innovative model demonstrates promising potential in predicting the bond behaviour, thereby enabling more efficient and reliable designs for the NSM FRP strengthening applications using cement-based adhesives.",

keywords = "NSM FRP, Bond-slip law, Cement-based adhesives, Artificial Neural Networks, Concrete structures",

author = "Sareh Akbarpoor and Mohammadali Rezazadeh and Bahman Ghiassi and Fazel Khayatian and Keerthan Poologanathan and Sefat, \{Honeyeh Ramezan\} and Marco Corradi",

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month = may,

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doi = "10.1016/j.conbuildmat.2024.136034",

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journal = "Construction and Building Materials",

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AU - Akbarpoor, Sareh

AU - Rezazadeh, Mohammadali

AU - Ghiassi, Bahman

AU - Khayatian, Fazel

AU - Poologanathan, Keerthan

AU - Sefat, Honeyeh Ramezan

AU - Corradi, Marco

PY - 2024/5/10

Y1 - 2024/5/10

N2 - This paper introduced a novel Artificial Neural Networks (ANN)-based bond–slip model for the Near-surface mounted (NSM) FRP system using cement-based adhesives, as an alternative to epoxy adhesives due to their high-temperature resistance and moisture-durability problems, employing experimental data. Therefore, closed-form formulas were presented for key components of the bond-slip law, including maximum bond stress, corresponding slip, fracture energy, and post-peak branch, while taking important factors into account. Compared to available bond-slip laws, this innovative model demonstrates promising potential in predicting the bond behaviour, thereby enabling more efficient and reliable designs for the NSM FRP strengthening applications using cement-based adhesives.

AB - This paper introduced a novel Artificial Neural Networks (ANN)-based bond–slip model for the Near-surface mounted (NSM) FRP system using cement-based adhesives, as an alternative to epoxy adhesives due to their high-temperature resistance and moisture-durability problems, employing experimental data. Therefore, closed-form formulas were presented for key components of the bond-slip law, including maximum bond stress, corresponding slip, fracture energy, and post-peak branch, while taking important factors into account. Compared to available bond-slip laws, this innovative model demonstrates promising potential in predicting the bond behaviour, thereby enabling more efficient and reliable designs for the NSM FRP strengthening applications using cement-based adhesives.

KW - NSM FRP

KW - Bond-slip law

KW - Cement-based adhesives

KW - Artificial Neural Networks

KW - Concrete structures

UR - https://www.scopus.com/pages/publications/85190816107

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DO - 10.1016/j.conbuildmat.2024.136034

M3 - Article

SN - 0950-0618

VL - 427

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EP - 28

JO - Construction and Building Materials

JF - Construction and Building Materials

M1 - 136034

ER -

A new bond-slip model for NSM FRP systems using cement-based adhesives through artificial neural networks (ANN)

Abstract

Keywords

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