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Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams
This work experimentally and numerically explored how varied steel-polypropylene fibre mixtures affected simply supported reinforced concrete deep beams. Due to their better mechanical qualities and durability, fibre-reinforced polymer composites are becoming more popular in construction, with hybri...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224283/ https://www.ncbi.nlm.nih.gov/pubmed/37242915 http://dx.doi.org/10.3390/polym15102340 |
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author | Khaleel Ibrahim, Sarah Abbas Hadi, Noor Movahedi Rad, Majid |
author_facet | Khaleel Ibrahim, Sarah Abbas Hadi, Noor Movahedi Rad, Majid |
author_sort | Khaleel Ibrahim, Sarah |
collection | PubMed |
description | This work experimentally and numerically explored how varied steel-polypropylene fibre mixtures affected simply supported reinforced concrete deep beams. Due to their better mechanical qualities and durability, fibre-reinforced polymer composites are becoming more popular in construction, with hybrid polymer-reinforced concrete (HPRC) promising to increase the strength and ductility of reinforced concrete structures. The study evaluated how different combinations of steel fibres (SF) and polypropylene fibres (PPF) affected beam behaviour experimentally and numerically. The study’s focus on deep beams, research of fibre combinations and percentages, and integration of experimental and numerical analysis provide unique insights. The two experimental deep beams were the same size and were composed of hybrid polymer concrete or normal concrete without fibres. Fibres increased deep beam strength and ductility in experiments. The calibrated concrete damage plasticity model in ABAQUS was used to numerically calibrate HPRC deep beams with different fibre combinations at varied percentages. Based on six experimental concrete mixtures, calibrated numerical models of deep beams with different material combinations were investigated. The numerical analysis confirmed that fibres increased deep beam strength and ductility. HPRC deep beams with fibre performed better than those without fibres in numerical analysis. The study also determined the best fibre percentage to improve deep beam behaviour where a combination of 0.75% SF and 0.25% PPF was recommended to enhance load-bearing capacity and crack distribution, while a higher content of PPF was suggested for reducing deflection. |
format | Online Article Text |
id | pubmed-10224283 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102242832023-05-28 Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams Khaleel Ibrahim, Sarah Abbas Hadi, Noor Movahedi Rad, Majid Polymers (Basel) Article This work experimentally and numerically explored how varied steel-polypropylene fibre mixtures affected simply supported reinforced concrete deep beams. Due to their better mechanical qualities and durability, fibre-reinforced polymer composites are becoming more popular in construction, with hybrid polymer-reinforced concrete (HPRC) promising to increase the strength and ductility of reinforced concrete structures. The study evaluated how different combinations of steel fibres (SF) and polypropylene fibres (PPF) affected beam behaviour experimentally and numerically. The study’s focus on deep beams, research of fibre combinations and percentages, and integration of experimental and numerical analysis provide unique insights. The two experimental deep beams were the same size and were composed of hybrid polymer concrete or normal concrete without fibres. Fibres increased deep beam strength and ductility in experiments. The calibrated concrete damage plasticity model in ABAQUS was used to numerically calibrate HPRC deep beams with different fibre combinations at varied percentages. Based on six experimental concrete mixtures, calibrated numerical models of deep beams with different material combinations were investigated. The numerical analysis confirmed that fibres increased deep beam strength and ductility. HPRC deep beams with fibre performed better than those without fibres in numerical analysis. The study also determined the best fibre percentage to improve deep beam behaviour where a combination of 0.75% SF and 0.25% PPF was recommended to enhance load-bearing capacity and crack distribution, while a higher content of PPF was suggested for reducing deflection. MDPI 2023-05-17 /pmc/articles/PMC10224283/ /pubmed/37242915 http://dx.doi.org/10.3390/polym15102340 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Khaleel Ibrahim, Sarah Abbas Hadi, Noor Movahedi Rad, Majid Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title | Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title_full | Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title_fullStr | Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title_full_unstemmed | Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title_short | Experimental and Numerical Analysis of Steel-Polypropylene Hybrid Fibre Reinforced Concrete Deep Beams |
title_sort | experimental and numerical analysis of steel-polypropylene hybrid fibre reinforced concrete deep beams |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224283/ https://www.ncbi.nlm.nih.gov/pubmed/37242915 http://dx.doi.org/10.3390/polym15102340 |
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