Date of Award

12-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Civil Engineering

Committee Member

Dr. Weichiang Pang, Committee Chair

Committee Member

Dr. Vincent Blouin

Committee Member

Dr. Mashrur Chowdhury

Abstract

A significant number of bridges in the Central and Southeastern United States (CSUS) are known to have a design that is lacking or no seismic consideration. In an article by Wong et al., Charleston is considered an active seismic zone, and the economic loss from the Charleston region could reach over $14 billion if 1886 Charleston’s earthquake would happen again in the near future. Due to lack of present consideration in seismic design for bridges in CSUS, there has been emerging research that studies retrofit strategies for CSUS region such as in Charleston. However, most of the retrofit program, including the expected damage method used by the Federal Highway Administration (FHWA), ignore the simultaneous aspects of bridges’ importance such as bridge’s centrality, bridges’ historical significance, and traffic capacity. Bridges’ centrality measures the influence of each bridge over the flow of the traffic. Historical significance, as coded in NBI, considers the value of the bridge associated with significant events or circumstance. This research develops the tool that combines those three aspects with the expected damage of the bridge to optimize the network performance. In addition, this research develops a tool that implements the consideration of a directed path (dipath) and travel distance in optimizing traveling capacity and retrofitting cost with respect to bridge retrofit methods. One of the main goal of the research is to account for technological transfer, with the Department of Transportation as the potential target users. Instead of having to rely on multi-platform software integration, the tool was developed and run on a single platform, Matlab, which results in efficiency with respect to software accessibility and computational time. The functionalities include network and seismic demand visualization, with the development of fragility curves and Monte Carlo simulation for estimating the failure probability of bridges. Genetic Algorithm was developed and validated, and incorporated into the tool to solve the models as, but not limited to, integer programming problems. Pareto frontier can be generated which results in various candidates of optima. This results in ranges of retrofitting program solutions instead of a single optimum, allowing for other external factors to be involved during the post-optimization and decision making process. To account for the usability aspect, a multi-window graphical user interface (GUI) is developed which negates the necessity for the user to be confused with the programming flow and syntax. Therefore, the goal of the project is to develop an innovative and connected solution to address real-time decision making during an extreme using the study case that includes the greater Charleston area. The project can be divided into three steps: (1) to create a small tool in Matlab that can automatically model a network consisting of roads and bridges with the least amount of user’s efforts, (2) to develop and incorporate new optimizations schemes for retrofitting program (3) to deploy a GUI-implemented beta version of an optimization system to improve the highway network performance and resiliency under seismic hazards.

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