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Optimizing bridge decks maintenance strategies based on probabilistic performance prediction using genetic algorithm

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Optimizing bridge decks maintenance strategies based on probabilistic performance prediction using genetic algorithm

Pakniat, Parinaz (2008) Optimizing bridge decks maintenance strategies based on probabilistic performance prediction using genetic algorithm. Masters thesis, Concordia University.

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Abstract

Bridges are important structures in transportation networks, and their maintenance is essential to public safety. Therefore, there is a critical need for research about evaluating the condition of existing bridges, investigating rehabilitation methods and organizing a management model for these bridges. Bridge Management Systems offer an effective decision-making tool for prioritizing maintenance, repair and rehabilitation (MR&R) activities taking into consideration such factors as budget constraints, suitability of MR&R methods, type and severity of bridge damages, safety, and user cost. In this research a multi-objective Genetic Algorithm is proposed to find the optimal long-term MR&R strategies for a set of reinforced concrete bridge decks based on the current status of the bridges, the applicability of several MR&R methods and their recovering effects, safety of the network, and the available budget. In this process, uncertainties associated with performance and safety have been modeled. The proposed methodology is demonstrated using a case study about bridges in Montreal partially based on real data obtained from the Ministry of Transportation of Quebec.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Pakniat, Parinaz
Pagination:x, 129 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Building, Civil and Environmental Engineering
Date:2008
Thesis Supervisor(s):Hammad, Amin
ID Code:975931
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:17
Last Modified:18 Jan 2018 17:41
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