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

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Article number136034
Number of pages28
JournalConstruction and Building Materials
Volume427
Early online date17 Apr 2024
DOIs
Publication statusPublished - 10 May 2024

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