Abstract

This research aims to utilize available technologies to assess the structural performance of prestressed concrete bridges. The structural performance is investigated at the local level in the form of delamination and spalling and at the global level in the form of strength and serviceability load rating and reliability index. At the local level, Infrared scanning combined with high-definition image scanning is utilized to provide a rapid condition assessment of the bridge components (deck, superstructure, and substructure). Two scans are performed, a year apart. The results of the two scans are compared to each other and to the bridge element level inspection report. A new approach is developed to identify areas where further evaluation is recommended. At the global level, A novel approach is introduced to assess the impact of girders' deterioration on the load rating, component reliability index, and system reliability index of the bridge. The impact of repairs to the girders is also assessed while accounting for uncertainties in the loading, capacity terms, and repair procedures. Computer vision-based load test, validated and supplemented by strain gauge and potentiometers sensors, is utilized to measure deflection under static and dynamic loading conditions. The effect of field-derived distribution factors and dynamic impact factors is investigated for the load rating and component and system reliability indices. The findings of this investigation are used to develop a decision tree for recommending the utilization computer vision-based load test to explore possible increases in load rating or target component reliability.

Notes

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Graduation Date

2023

Semester

Summer

Advisor

Catbas, Necati

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Civil, Environmental, and Construction Engineering

Degree Program

Civil Engineering

Identifier

CFE0009709; DP0027816

URL

https://purls.library.ucf.edu/go/DP0027816

Language

English

Release Date

August 2024

Length of Campus-only Access

1 year

Access Status

Doctoral Dissertation (Campus-only Access)

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