MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER

Nowadays, the application of carbon fibre reinforced polymer (CFRP) composites in engineering works for strengthening of reinforced concrete structures is increase dramatically. CFRP can be used to strengthen the structural elements to increase its performance in load carrying capacity, and subseque...

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Published in:JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY
Main Authors: Shahrin, Wan Muhammad; Ismail, Ruqayyah; Lee, Hoong Pin; Goh, Lyn Dee; Ahmad, Fariz Aswan; Ahmad, Hazrina; Wahid, Norlizan
Format: Article
Language:English
Published: TAYLORS UNIV SDN BHD 2023
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001154412900017
author Shahrin
Wan Muhammad; Ismail
Ruqayyah; Lee
Hoong Pin; Goh
Lyn Dee; Ahmad
Fariz Aswan; Ahmad
Hazrina; Wahid
Norlizan
spellingShingle Shahrin
Wan Muhammad; Ismail
Ruqayyah; Lee
Hoong Pin; Goh
Lyn Dee; Ahmad
Fariz Aswan; Ahmad
Hazrina; Wahid
Norlizan
MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
Engineering
author_facet Shahrin
Wan Muhammad; Ismail
Ruqayyah; Lee
Hoong Pin; Goh
Lyn Dee; Ahmad
Fariz Aswan; Ahmad
Hazrina; Wahid
Norlizan
author_sort Shahrin
spelling Shahrin, Wan Muhammad; Ismail, Ruqayyah; Lee, Hoong Pin; Goh, Lyn Dee; Ahmad, Fariz Aswan; Ahmad, Hazrina; Wahid, Norlizan
MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY
English
Article
Nowadays, the application of carbon fibre reinforced polymer (CFRP) composites in engineering works for strengthening of reinforced concrete structures is increase dramatically. CFRP can be used to strengthen the structural elements to increase its performance in load carrying capacity, and subsequently delaying the deterioration rate or reducing the impact of damage, if any. This paper aims to provide an analytical model which is capable to predict the CFRP fully confined concrete compressive strength. This analytical model is developed by using artificial neural network (ANN) which utilised the data from a new database created from the previous experimental works in previous literatures. Four input parameters are selected as the training parameters for the ANN, i.e. the tensile strength of CFRP (f(f)), thickness of the CFRP layer (t), CFRP's Young modulus of elasticity (E-f) and compressive strength of unconfined concrete (f(co)). The output of the ANN models is to predict the compressive strength of confined concrete (f(cc)). In addition, a comparison was carried out with the predicted value from the proposed ANN model in this study and the experimental value from literature, and with two other existing mathematical models from previous study. The proposed ANN model showed lowest average error in predicting the experimental results with only a difference of 5.91 MPa as compared to the actual experimental value.
TAYLORS UNIV SDN BHD

1823-4690
2023
18
6

Engineering

WOS:001154412900017
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001154412900017
title MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
title_short MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
title_full MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
title_fullStr MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
title_full_unstemmed MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
title_sort MODEL PREDICTION FOR COMPRESSIVE STRENGTH OF A FULLY CONFINED CONCRETE CYLINDER WITH CARBON FIBRE REINFORCED POLYMER
container_title JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY
language English
format Article
description Nowadays, the application of carbon fibre reinforced polymer (CFRP) composites in engineering works for strengthening of reinforced concrete structures is increase dramatically. CFRP can be used to strengthen the structural elements to increase its performance in load carrying capacity, and subsequently delaying the deterioration rate or reducing the impact of damage, if any. This paper aims to provide an analytical model which is capable to predict the CFRP fully confined concrete compressive strength. This analytical model is developed by using artificial neural network (ANN) which utilised the data from a new database created from the previous experimental works in previous literatures. Four input parameters are selected as the training parameters for the ANN, i.e. the tensile strength of CFRP (f(f)), thickness of the CFRP layer (t), CFRP's Young modulus of elasticity (E-f) and compressive strength of unconfined concrete (f(co)). The output of the ANN models is to predict the compressive strength of confined concrete (f(cc)). In addition, a comparison was carried out with the predicted value from the proposed ANN model in this study and the experimental value from literature, and with two other existing mathematical models from previous study. The proposed ANN model showed lowest average error in predicting the experimental results with only a difference of 5.91 MPa as compared to the actual experimental value.
publisher TAYLORS UNIV SDN BHD
issn
1823-4690
publishDate 2023
container_volume 18
container_issue 6
doi_str_mv
topic Engineering
topic_facet Engineering
accesstype
id WOS:001154412900017
url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001154412900017
record_format wos
collection Web of Science (WoS)
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