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Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams

This research proposes a novel method that considers the optimal reliability-based design of reinforced concrete haunched beams subjected to probabilistic concrete properties and complementary strain energy values. The theory is applied twice, once to evaluate a deterministic solution, where the pla...

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Autores principales: Khaleel Ibrahim, Sarah, Movahedi Rad, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932058/
https://www.ncbi.nlm.nih.gov/pubmed/36792715
http://dx.doi.org/10.1038/s41598-023-29930-0
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author Khaleel Ibrahim, Sarah
Movahedi Rad, Majid
author_facet Khaleel Ibrahim, Sarah
Movahedi Rad, Majid
author_sort Khaleel Ibrahim, Sarah
collection PubMed
description This research proposes a novel method that considers the optimal reliability-based design of reinforced concrete haunched beams subjected to probabilistic concrete properties and complementary strain energy values. The theory is applied twice, once to evaluate a deterministic solution, where the plastic behaviour is constrained by the complementary strain energy of residual stresses induced within steel bars. Secondly, the same method is considered for a probabilistic solution where the concrete characteristics—compressive strength and modulus of elasticity—and complementary strain energy value vary randomly. The reliability index acts as a bound for the solution. It is important to mention that the model utilised in this publication is derived from recent research after being calibrated using Abaqus. This work represents an extension of that recent research that exclusively considered deterministic work. This research led deterministically to new estimates for the complementary strain energy, which will be interpreted as reflecting the behaviour of plastic thresholds and quantifying the associated loads. Afterwards, uncertainty is studied when probability interferes, showing various load values and damage in concrete and steel when the complementary strain energy and concrete properties are probabilistically evaluated, giving a less reliable solution as the load reduces. These effects are reflected in the varying plastic behaviour of the investigated haunched beams.
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spelling pubmed-99320582023-02-17 Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams Khaleel Ibrahim, Sarah Movahedi Rad, Majid Sci Rep Article This research proposes a novel method that considers the optimal reliability-based design of reinforced concrete haunched beams subjected to probabilistic concrete properties and complementary strain energy values. The theory is applied twice, once to evaluate a deterministic solution, where the plastic behaviour is constrained by the complementary strain energy of residual stresses induced within steel bars. Secondly, the same method is considered for a probabilistic solution where the concrete characteristics—compressive strength and modulus of elasticity—and complementary strain energy value vary randomly. The reliability index acts as a bound for the solution. It is important to mention that the model utilised in this publication is derived from recent research after being calibrated using Abaqus. This work represents an extension of that recent research that exclusively considered deterministic work. This research led deterministically to new estimates for the complementary strain energy, which will be interpreted as reflecting the behaviour of plastic thresholds and quantifying the associated loads. Afterwards, uncertainty is studied when probability interferes, showing various load values and damage in concrete and steel when the complementary strain energy and concrete properties are probabilistically evaluated, giving a less reliable solution as the load reduces. These effects are reflected in the varying plastic behaviour of the investigated haunched beams. Nature Publishing Group UK 2023-02-15 /pmc/articles/PMC9932058/ /pubmed/36792715 http://dx.doi.org/10.1038/s41598-023-29930-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Khaleel Ibrahim, Sarah
Movahedi Rad, Majid
Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title_full Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title_fullStr Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title_full_unstemmed Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title_short Reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
title_sort reliability‑based probabilistic numerical plastically limited analysis of reinforced concrete haunched beams
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932058/
https://www.ncbi.nlm.nih.gov/pubmed/36792715
http://dx.doi.org/10.1038/s41598-023-29930-0
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