Document Type

Thesis - Open Access

Award Date

2017

Degree Name

Master of Science (MS)

Department

Civil and Environmental Engineering

First Advisor

Junwon Seo

Keywords

Bridge Inspection, Damage Quantification, Finite Element Analyis, Finite Element Updating, Load-Carrying Capacity, UAV

Abstract

The use of Unmanned Aerial Vehicles (UAV), commonly known as drones, has significantly increased in the field of civil engineering due to the poor condition of the United States’ infrastructure. The American Society of Civil Engineers (ASCE) recently reported that more than 9.1% of the United States’ bridges were structurally deficient and required attention and maintenance to ensure appropriate structural performance. Meanwhile, current practices are expensive and unsafe for bridge inspectors, requiring innovative and safer methods for the study of bridges. The goal of this paper was to identify better techniques to not only inspect, quantify, and determine the effect of damage on bridges to minimize the risk for inspectors, but also to determine their live-load performance using UAV-based computational simulation updating techniques. To accomplish the objective, an extensive literature review and survey to state departments of transportation (DOTs) was conducted to gain technical knowledge on current UAV-based inspection practices. To evaluate the efficiency of the UAV, the Keystone Interchange Bridges (i.e., Keystone Wye timber arch bridge and timber girder bridge) in the Black Hills National Forest near the city of Keystone, South Dakota (SD), were studied. To provide a more systematical and efficient UAV-enabled bride inspection method, a five-stage recommended bridge inspection protocol was developed. A UAV-image-based bridge damage quantification protocol involving image quality assessment and image-based damage measurement was recommended. Finally, using the damage information form the inspection and quantification of the bridges, a Finite Element (FE) model to determine the live-load performance of the Keystone Wye timber arch bridge in terms of Distribution Factors (DF) and Load Rating Factors (RF) was developed. It was concluded that the UAV served as an effective tool to supplement current inspection practices and provide damage information that can be used to update FE models to rationally estimate bridge performance.

Library of Congress Subject Headings

Bridges -- Inspection.
Bridges -- Inspection -- Simulation methods.
Drone aircraft.
Finite element method.
Structural health monitoring.

Description

Includes bibliographical references (pages 150-157)

Format

application/pdf

Number of Pages

168

Publisher

South Dakota State University

Rights

In Copyright - Non-Commercial Use Permitted
http://rightsstatements.org/vocab/InC-NC/1.0/

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