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Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique

This study proposes an energy absorption model for predicting the effect of loading rates, concrete compressive strength, shear span-to-depth ratio, and longitudinal and transverse reinforcement ratio of reinforced concrete (RC) beams using the particle swarm optimization (PSO) technique. This techn...

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Main Authors: Hanoon, Ammar Nasiri, Jaafar, Mohd Saleh, Hejazi, Farzad, Abd Aziz, Farah Nora Aznieta
Format: Article
Language:English
Published: Taylor & Francis 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61715/1/Energy%20absorption%20evaluation%20of%20reinforced%20concrete%20beams%20.pdf
http://psasir.upm.edu.my/id/eprint/61715/
https://www.tandfonline.com/doi/abs/10.1080/0305215X.2016.1256729
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spelling my.upm.eprints.617152019-01-08T07:49:31Z http://psasir.upm.edu.my/id/eprint/61715/ Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique Hanoon, Ammar Nasiri Jaafar, Mohd Saleh Hejazi, Farzad Abd Aziz, Farah Nora Aznieta This study proposes an energy absorption model for predicting the effect of loading rates, concrete compressive strength, shear span-to-depth ratio, and longitudinal and transverse reinforcement ratio of reinforced concrete (RC) beams using the particle swarm optimization (PSO) technique. This technique avoids the exhaustive traditional trial-and-error procedure for obtaining the coefficient of the proposed model. Fifty-six RC slender and deep beams are collected from the literature and used to build the proposed model. Three performance measures, namely, mean absolute error, mean absolute percentage error and root mean square error, are investigated in the proposed model to increase its accuracy. The design procedure and accuracy of the proposed model are illustrated and analysed via simulation tests in a MATLAB/Simulink environment. The results indicate the minimal effect of swarm size on the convergence of the PSO algorithm, as well as the ability of PSO to search for an optimum set of coefficients from within the solution space. Taylor & Francis 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61715/1/Energy%20absorption%20evaluation%20of%20reinforced%20concrete%20beams%20.pdf Hanoon, Ammar Nasiri and Jaafar, Mohd Saleh and Hejazi, Farzad and Abd Aziz, Farah Nora Aznieta (2017) Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique. Engineering Optimization, 49 (9). 1483 - 1501. ISSN 0305-215X; ESSN: 1029-0273 https://www.tandfonline.com/doi/abs/10.1080/0305215X.2016.1256729 10.1080/0305215X.2016.1256729
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This study proposes an energy absorption model for predicting the effect of loading rates, concrete compressive strength, shear span-to-depth ratio, and longitudinal and transverse reinforcement ratio of reinforced concrete (RC) beams using the particle swarm optimization (PSO) technique. This technique avoids the exhaustive traditional trial-and-error procedure for obtaining the coefficient of the proposed model. Fifty-six RC slender and deep beams are collected from the literature and used to build the proposed model. Three performance measures, namely, mean absolute error, mean absolute percentage error and root mean square error, are investigated in the proposed model to increase its accuracy. The design procedure and accuracy of the proposed model are illustrated and analysed via simulation tests in a MATLAB/Simulink environment. The results indicate the minimal effect of swarm size on the convergence of the PSO algorithm, as well as the ability of PSO to search for an optimum set of coefficients from within the solution space.
format Article
author Hanoon, Ammar Nasiri
Jaafar, Mohd Saleh
Hejazi, Farzad
Abd Aziz, Farah Nora Aznieta
spellingShingle Hanoon, Ammar Nasiri
Jaafar, Mohd Saleh
Hejazi, Farzad
Abd Aziz, Farah Nora Aznieta
Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
author_facet Hanoon, Ammar Nasiri
Jaafar, Mohd Saleh
Hejazi, Farzad
Abd Aziz, Farah Nora Aznieta
author_sort Hanoon, Ammar Nasiri
title Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
title_short Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
title_full Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
title_fullStr Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
title_full_unstemmed Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
title_sort energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique
publisher Taylor & Francis
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61715/1/Energy%20absorption%20evaluation%20of%20reinforced%20concrete%20beams%20.pdf
http://psasir.upm.edu.my/id/eprint/61715/
https://www.tandfonline.com/doi/abs/10.1080/0305215X.2016.1256729
_version_ 1643837579647254528
score 13.244368

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