Date of Award

2019-01-01

Degree Name

Master of Science

Department

Civil Engineering

Advisor(s)

Jeffrey Weidner

Abstract

The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) marked the start of a new era in transportation in the United States. ISTEA required transportation agencies to take a proactive approach to planning and management of their assets. This included requirements for managing pavement, bridges, safety, congestion, public transportation, and intermodal systems. For horizontal transportation assets (i.e., bridges and pavement), deterioration modeling is an essential tool (Yanev and Chen 1993). Since ISTEA, Bridge Management Systems (BMS) have been utilized to inform decision-making regarding bridge projects such as maintenance, rehabilitation, and replacement (MR&R) under financial limitations (Agrawal, Kawaguchi, and Chen 2010). The goal of a BMS is to optimize the performance of bridge networks by implementing planned MR&R events to the selected bridges in the correct manner and at the correct time. Reliable predictions of future condition states are critical for optimizing MR&R activities. The condition rating of bridges is the most vital variable to predict the future performance of bridges (Jiang 2010). Deterioration models are used to estimate a future condition ratings. There are numerous approaches to develop deterioration models such as deterministic, stochastic, mechanistic, artificial intelligent, reliability-based approaches. Each of these approaches is defensible but is based on different assumptions and could potentially provide different results. A stochastic approach using Markov chains was the focus of this research.

Language

en

Provenance

Received from ProQuest

File Size

67 pages

File Format

application/pdf

Rights Holder

JIN A COLLINS

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