Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data
Several past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theor...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/5/611 |
| _version_ | 1797501109047132160 |
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| author | Muhammad Kashif Anwar Syyed Adnan Raheel Shah Marc Azab Ibrahim Shah Muhammad Khalid Sharif Chauhan Fahad Iqbal |
| author_facet | Muhammad Kashif Anwar Syyed Adnan Raheel Shah Marc Azab Ibrahim Shah Muhammad Khalid Sharif Chauhan Fahad Iqbal |
| author_sort | Muhammad Kashif Anwar |
| collection | DOAJ |
| description | Several past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theoretical model found in the literature. The objective of the current study is to introduce a novel prediction model for the axial capability of concrete columns made with bars of GFRP. For this purpose, two different approaches, such as data envelopment analysis (DEA) and artificial neural networks (ANNs) modelling, are used on a collected dataset of 266 concrete column specimens made with GFRP bars from previous literature works. Eight parameters were used to predict the axial performance of GFRP-based RC columns. The proposed DEA and ANNs predictions demonstrated a good correlation with the testing dataset, having R<sup>2</sup> values of 0.811 and 0.836, respectively. A comparative analysis of the DEA and ANNs models is undertaken, and it was found that the suggested models are capable of accurately forecasting the structural response of GFRP-made RC column structures. Then, a comprehensive parametric analysis of 266 GFRP-based columns was performed to study the effect of different materials and their geometrical shape. |
| first_indexed | 2024-03-10T03:13:36Z |
| format | Article |
| id | doaj.art-6addc2e9c7ec4bf383366d48f1676006 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-10T03:13:36Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-6addc2e9c7ec4bf383366d48f16760062023-11-23T10:20:35ZengMDPI AGBuildings2075-53092022-05-0112561110.3390/buildings12050611Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile DataMuhammad Kashif Anwar0Syyed Adnan Raheel Shah1Marc Azab2Ibrahim Shah3Muhammad Khalid Sharif Chauhan4Fahad Iqbal5Department of Civil Engineering, Pakistan Institute of Engineering and Technology, Multan 66000, PakistanDepartment of Civil Engineering, Pakistan Institute of Engineering and Technology, Multan 66000, PakistanCollege of Engineering and Technology, American University of the Middle East, KuwaitDepartment of Civil Engineering, Pakistan Institute of Engineering and Technology, Multan 66000, PakistanDepartment of Architecture, Multan College of Arts, Bahauddin Zakariya University, Multan 66000, PakistanDepartment of Mechanical and Structural Engineering and Materials Science, University of Stavanger, NO-4036 Stavanger, NorwaySeveral past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theoretical model found in the literature. The objective of the current study is to introduce a novel prediction model for the axial capability of concrete columns made with bars of GFRP. For this purpose, two different approaches, such as data envelopment analysis (DEA) and artificial neural networks (ANNs) modelling, are used on a collected dataset of 266 concrete column specimens made with GFRP bars from previous literature works. Eight parameters were used to predict the axial performance of GFRP-based RC columns. The proposed DEA and ANNs predictions demonstrated a good correlation with the testing dataset, having R<sup>2</sup> values of 0.811 and 0.836, respectively. A comparative analysis of the DEA and ANNs models is undertaken, and it was found that the suggested models are capable of accurately forecasting the structural response of GFRP-made RC column structures. Then, a comprehensive parametric analysis of 266 GFRP-based columns was performed to study the effect of different materials and their geometrical shape.https://www.mdpi.com/2075-5309/12/5/611sustainabilityaxial capacityconstructionglass fibre-reinforced polymer (GFRP)reinforced concretedata envelopment analysis |
| spellingShingle | Muhammad Kashif Anwar Syyed Adnan Raheel Shah Marc Azab Ibrahim Shah Muhammad Khalid Sharif Chauhan Fahad Iqbal Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data Buildings sustainability axial capacity construction glass fibre-reinforced polymer (GFRP) reinforced concrete data envelopment analysis |
| title | Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data |
| title_full | Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data |
| title_fullStr | Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data |
| title_full_unstemmed | Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data |
| title_short | Structural Performance of GFRP Bars Based High-Strength RC Columns: An Application of Advanced Decision-Making Mechanism for Experimental Profile Data |
| title_sort | structural performance of gfrp bars based high strength rc columns an application of advanced decision making mechanism for experimental profile data |
| topic | sustainability axial capacity construction glass fibre-reinforced polymer (GFRP) reinforced concrete data envelopment analysis |
| url | https://www.mdpi.com/2075-5309/12/5/611 |
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