A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data

The objective of this article is to provide a comprehensive dataset based on detailed fiber-based dynamic response simulations conducted to select individual and hybrid retrofit techniques for upgrading substandard reinforced concrete (RC) adjacent bridges vulnerable to various damage modes. The dat...

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Main Authors: Jumana Hasina, Aman Mwafy
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Data in Brief
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Online Access:http://www.sciencedirect.com/science/article/pii/S235234092500486X
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author Jumana Hasina
Aman Mwafy
author_facet Jumana Hasina
Aman Mwafy
author_sort Jumana Hasina
collection DOAJ
description The objective of this article is to provide a comprehensive dataset based on detailed fiber-based dynamic response simulations conducted to select individual and hybrid retrofit techniques for upgrading substandard reinforced concrete (RC) adjacent bridges vulnerable to various damage modes. The dataset results from a step-by-step methodology adopted for upgrading existing substandard bridges. Different retrofit techniques are chosen based on the detected damage modes in the existing adjacent bridges, aiming to upgrade their seismic performance and ensure continuous functionality. The fiber-based modeling approaches for the selected retrofit measures are initially validated by comparing their hysteretic responses with those of previous experimental results. The verified retrofit measures are then applied to a benchmark adjacent bridge for preliminary and probabilistic seismic performance assessment using multi-record incremental dynamic analysis and different seismic scenarios. The comprehensive results obtained from the detailed probabilistic seismic evaluation of the existing and retrofitted bridges, including lateral capacity curves, large sets of fragility functions, and damage state probabilities, are collected and presented in the form of spreadsheets. The entire dataset is organized into five folders, containing 28 Excel worksheets, which are further subdivided into 55 spreadsheets. The datasets produced by the present study provide valuable inputs for risk management systems and benchmarking with other existing substandard bridges retrofitted with individual and hybrid alternatives.
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spelling doaj-art-96bea0facbfe437fbe7621cca62339f42025-08-20T03:18:38ZengElsevierData in Brief2352-34092025-08-016111175910.1016/j.dib.2025.111759A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley DataJumana Hasina0Aman Mwafy1Civil and Environmental Engineering Department, United Arab Emirates University, Al Ain, the United Arab EmiratesCorresponding author.; Civil and Environmental Engineering Department, United Arab Emirates University, Al Ain, the United Arab EmiratesThe objective of this article is to provide a comprehensive dataset based on detailed fiber-based dynamic response simulations conducted to select individual and hybrid retrofit techniques for upgrading substandard reinforced concrete (RC) adjacent bridges vulnerable to various damage modes. The dataset results from a step-by-step methodology adopted for upgrading existing substandard bridges. Different retrofit techniques are chosen based on the detected damage modes in the existing adjacent bridges, aiming to upgrade their seismic performance and ensure continuous functionality. The fiber-based modeling approaches for the selected retrofit measures are initially validated by comparing their hysteretic responses with those of previous experimental results. The verified retrofit measures are then applied to a benchmark adjacent bridge for preliminary and probabilistic seismic performance assessment using multi-record incremental dynamic analysis and different seismic scenarios. The comprehensive results obtained from the detailed probabilistic seismic evaluation of the existing and retrofitted bridges, including lateral capacity curves, large sets of fragility functions, and damage state probabilities, are collected and presented in the form of spreadsheets. The entire dataset is organized into five folders, containing 28 Excel worksheets, which are further subdivided into 55 spreadsheets. The datasets produced by the present study provide valuable inputs for risk management systems and benchmarking with other existing substandard bridges retrofitted with individual and hybrid alternatives.http://www.sciencedirect.com/science/article/pii/S235234092500486XSeismic assessmentDamage modesNumerical modelingRetrofitSubstandard structuresTransportation infrastructure
spellingShingle Jumana Hasina
Aman Mwafy
A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
Data in Brief
Seismic assessment
Damage modes
Numerical modeling
Retrofit
Substandard structures
Transportation infrastructure
title A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
title_full A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
title_fullStr A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
title_full_unstemmed A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
title_short A dataset of inelastic response for multi-span RC adjacent bridges with individual and hybrid seismic risk mitigation techniquesMendeley Data
title_sort dataset of inelastic response for multi span rc adjacent bridges with individual and hybrid seismic risk mitigation techniquesmendeley data
topic Seismic assessment
Damage modes
Numerical modeling
Retrofit
Substandard structures
Transportation infrastructure
url http://www.sciencedirect.com/science/article/pii/S235234092500486X
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