Date of Award

2023-05-01

Degree Name

Doctor of Philosophy

Department

Civil Engineering

Advisor(s)

Jeffrey J. Weidner

Abstract

Bridge Management Systems (BMSs) have been used to support decision-making in bridgeprojects, including maintenance, rehabilitation, and replacement under financial constraints. These decisions are predicated on the ability to estimate bridgesâ?? future condition states to optimize bridge network systems' performance. Deterioration models are commonly used tools to help transportation agencies make predictions of future condition states of infrastructure facilities, schedule capital investments, and make comparative decisions. Numerous deterioration models have been developed over the last few decades. In particular, Markov chain models utilize bridge data collected from the National Bridge Inventory (NBI) database to make predictions. The accuracy of predictions is measured by comparing the estimated future condition states to the ensemble mean of observed condition states. To improve the accuracy, researchers have applied explanatory variables' effect on the deterioration process in modeling. The selection of explanatory variables and application methods in the modeling are different by researchers, creating uncertainty and bias. This research presents the development of a framework for a novel deterioration approach utilizing multiple models through a case study. The Texas concrete decks were collected from the NBI database. Markov chain models, time-based Weibull, and corrosion-induced mechanistic models were collected from the literature review. In the development of the model, the transition probability matrices of each model were estimated. A transition probability matrix (TPM) is a product of the Markov chain models. The same explanatory variables were applied in the modeling process except for the mechanistic-based model. The proposed model was developed by integrating these TPMs. The products of the model were a single deterioration curve which presents the future condition rating of a component over time and a range of possible condition ratings at a given time. The results provided reasonable accuracy. The deterioration model can be utilized to estimate the future condition states of infrastructure facilities more confidently. The estimations can be used to plan more effective and efficient maintenance, rehabilitation, and replacement (MR& amp;R) activities under a limited budget to prevent potential failure and to maintain an acceptable service level.

Language

en

Provenance

Recieved from ProQuest

File Size

p.

File Format

application/pdf

Rights Holder

Jin A Collins

Download

Share

COinS