Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces

A Master of Science thesis in Mechatronics Engineering by Ibrahim Javed Choudhary entitled, "Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces," submitted in March 2013. Thesis advisor is Dr. Khaled Assaleh and co-advisor is Dr. Mohammad AlHamay...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Choudhary, Ibrahim Javed (author)
التنسيق: doctoralThesis
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/5840
الوسوم: إضافة وسم
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author Choudhary, Ibrahim Javed
author_facet Choudhary, Ibrahim Javed
author_role author
dc.contributor.none.fl_str_mv Assaleh, Khaled
AlHamaydeh, Mohammad
dc.creator.none.fl_str_mv Choudhary, Ibrahim Javed
dc.date.none.fl_str_mv 2013-04-22T10:58:12Z
2013-04-22T10:58:12Z
2013-03
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2013.13
http://hdl.handle.net/11073/5840
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv buckling-restrained braces
artificial neural network
TDNN
NARX
GMM
ANFIS
polynomial classifier
Artificial intelligence
Mathematical models
Buckling (Mechanics)
Building, Iron and steel
Design and construction
Steel framing (Building)
dc.title.none.fl_str_mv Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Mechatronics Engineering by Ibrahim Javed Choudhary entitled, "Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces," submitted in March 2013. Thesis advisor is Dr. Khaled Assaleh and co-advisor is Dr. Mohammad AlHamayde. Available are both soft and hard copies of the thesis.
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network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/5840
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spelling Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained BracesChoudhary, Ibrahim Javedbuckling-restrained bracesartificial neural networkTDNNNARXGMMANFISpolynomial classifierArtificial intelligenceMathematical modelsBuckling (Mechanics)Building, Iron and steelDesign and constructionSteel framing (Building)A Master of Science thesis in Mechatronics Engineering by Ibrahim Javed Choudhary entitled, "Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces," submitted in March 2013. Thesis advisor is Dr. Khaled Assaleh and co-advisor is Dr. Mohammad AlHamayde. Available are both soft and hard copies of the thesis.The present research attempts to investigate and compare various artificial intelligence techniques to model the dynamic nonlinear behavior of Buckling Restrained Braces (BRBs). The various intelligent models are developed using normalized time-delayed inputs and outputs to predict normalized brace forces during load reversals. The values of brace forces are denormalized via an auxiliary intelligent (MLP) model. The training and testing of the proposed models are performed using experimental data from BRB specimens tested at the Pacific Earthquake Engineering Research (PEER) Center, University of California, Berkley. Experimental data from one specimen is used in the model development (training) stage. In addition, three sets of data are used to test the model's learning and generalizing abilities. Brace extensions are used as the network input to estimate the resulting brace forces in a longitudinal direction only. The network performance with different parameters is evaluated in order to arrive at an optimized architecture that best models the phenomenon. The nonlinear hysteretic behavior predicted by the majority of the employed models shows excellent agreement with the experimental results for the training sample. The generalization and prediction capability of the several proposed models is further demonstrated by predicting the hysteretic behavior of the testing samples with noticeable and vivid accuracy. The presented models represent a powerful tool for virtually testing BRB specimens. Such a tool supplements the traditionally available experimental tools for BRB performance investigation. A comparison on the basis of RMSE and Coefficient of Determination (R^2) is carried out to quantify and judge the performance of each implemented model. Further, the estimated peak response quantities and the energy dissipation during hysteretic cycles are also evaluated for precise comparison. The developed modeling techniques facilitate the BRB design and performance investigation processes by minimizing the need for, and extent of, experimental testing. Keywords: Buckling-Restrained Brace, Artificial Neural Network, TDNN, NARX, GMM, ANFIS, Polynomial Classifier.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Assaleh, KhaledAlHamaydeh, Mohammad2013-04-22T10:58:12Z2013-04-22T10:58:12Z2013-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2013.13http://hdl.handle.net/11073/5840en_USoai:repository.aus.edu:11073/58402025-06-26T12:30:55Z
spellingShingle Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
Choudhary, Ibrahim Javed
buckling-restrained braces
artificial neural network
TDNN
NARX
GMM
ANFIS
polynomial classifier
Artificial intelligence
Mathematical models
Buckling (Mechanics)
Building, Iron and steel
Design and construction
Steel framing (Building)
status_str publishedVersion
title Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
title_full Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
title_fullStr Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
title_full_unstemmed Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
title_short Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
title_sort Artificial Intelligence-Based Modeling of the Nonlinear Behavior of Buckling-Restrained Braces
topic buckling-restrained braces
artificial neural network
TDNN
NARX
GMM
ANFIS
polynomial classifier
Artificial intelligence
Mathematical models
Buckling (Mechanics)
Building, Iron and steel
Design and construction
Steel framing (Building)
url http://hdl.handle.net/11073/5840