Date of Award

Spring 2018

Project Type

Thesis

Program or Major

Civil Engineering

Degree Name

Doctor of Philosophy

First Advisor

Charlie Goodspeed

Second Advisor

Ricardo Medina

Third Advisor

Eshan V Dave

Abstract

Most public transportation agencies (Such as, state department of transportations (DOTs) and department of public works for cities and towns.) in the United States are constantly pursuing ways to improve bridge asset management to optimize their use of limited available funds for rehabilitation, replacement, and preventive maintenance. Given the realities of available funding, there is a significant difference between available funds and funds required for maintaining bridges in good condition. The proper preventative maintenance and treatments should be performed at the right time to be cost effective and extend the life of bridges. Neglecting maintenance can cause higher future costs and further deteriorate the conditions that will increase the risk of bridge closure. This would require complete or partial replacement as well as additional funds needed for detours and traffic control which interrupts services to the motorist and creates more congestion. Development and implementation of a Bridge Management System (BMS) provide states and municipalities with a tool to help identify maintenance repair, prioritize bridge rehabilitation and replacement, develop preservation strategies, and allocate available funds accordingly.

The primary objective of this research is to develop a Bridge Management System (BMS) to manage municipal and state bridge assets. Complete, accurate data in well-designed form is vital to a Bridge Management System (BMS). This system will make available work reports, engineering drawings, photographs, and a forecasting model for management staff use. Inventory and condition data are extracted from the U.S. Federal Highway Administration (FHWA) and National Bridge Inventory System (NBIS) coding guidelines. The proposed model provides: (1) A priority ranking system for Rehabilitation and Replacement projects, which enables the decision-makers to understand and compare the overall state of all the bridges in the network. It embraces seven factors condition, criticality, risk, functionally, bridge type, age, and size. (2) A deterioration model that uses optimized case-based reasoning (CBR) method. A similarity measure of classification is developed to identify how close the characteristics of bridge components are to each other based on a scoring system. (3) A cost model that considers different repair strategies and provide bridge repair recommendations with estimated cost repairs. (4)The model feeds data to a forecasting program that prepares 120-year preservation, maintenance, repair and rehabilitation budgets and schedules to sustain a bridge network at the highest performance level under approved budgets. The forecasting option contains default management costs that are upgraded as work report data yields costs based on locality and individual bridge projects. BMS will give accessibility through linkages to all available municipal, and DOT, bridge data in the state. The data will be available through ArcGIS on tablets, laptops, and smartphones with access to cloud storage.

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