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Thesis defences

PhD Oral Exam - Mohammed Alsharqawi, Building Engineering

Integrated Decision Support Methodology for Bridge Deck Management under Performance-Based Contracting


Date & time
Monday, June 18, 2018
10 a.m. – 1 p.m.
Cost

This event is free

Organization

School of Graduate Studies

Contact

Mary Appezzato
514-848-2424, ext. 3813

Where

Engineering, Computer Science and Visual Arts Integrated Complex
1515 St. Catherine W.
Room EV 3.309

Accessible location

Yes

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Bridges are vital elements of the civil infrastructure system in terms of mobility, environment, economy, and development of communities. Maintaining bridges at sufficient functional and safety levels is an important mandate to ministries of transportation. The 2016 Canada infrastructure report card alarmed that more than 26% of bridges in Canada have deteriorated and the bridges are mostly rated as fair, poor or very poor (CIRC 2016). In the United States, the report card on America’s infrastructure assigned grade “C+” to bridge infrastructure (ASCE 2017). Hence, developing rational decision support methods that can assist in managing the vast bridge infrastructure is of paramount importance. This research aimed toward developing a decision support methodology for concrete bridges capable for optimizing the Maintenance, Repair and Replacement (MRR) actions under Performance-Based Contracting (PBC) arrangement through implementing the following steps: i) develop an integrated condition assessment and rating model; ii) develop a forecasting model to assess bridge condition reliability and predict future deteriorations/improvements; iii) develop short- and long-term optimized rehabilitation plans; and iv) design a PBC-based framework for rehabilitation decisions. Upon studying bridge inspection standards and current practices, the research introduces the Quality Function Deployment (QFD) theory and Weibull Distribution Function (WDF) to produce novel methods to rate the bridge current conditions and forecast future performance. These methods integrate data extracted from visual inspection and Ground Penetrating Radar (GPR) surveys. The k-means clustering technique is utilized to develop rating index that recommends suitable MRR actions based on an integrated condition rating. The Genetic Algorithm (GA) optimization technique is applied to select the best combinations of rehabilitation strategies under the PBC scheme. The integrated rating along with the GA optimization ultimately develop a recommended work program that considers the identified performance triggers and budget constraints. The research contributes a novel PBC-based decision support framework to the area of bridge management that enhances efficiency in implementing MRR strategies while maintaining the delicate balance between the different stakeholders’ requirements and goals. The developed methodology is implemented and tested on data extracted from bridge inspection reports and GPR scans, mainly on bridges in Quebec, Canada. Ministries of transportation can benefit from the condition rating and deterioration modeling to assess their bridges’ condition and to interfere and do a rehabilitation action before reaching the end of useful service life. The GA-based model provides the maintenance contractors with optimized interventions plans that specifies what type of MRR actions to do and when. Further, it assists the ministries to set the budget in such projects. The PBC framework is expected to assist both the transportation agencies and maintenance contractors in arriving at a fair contract value while maintaining the desired bridge performance.


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