A study on bridge inspections: identifying barriers to new practices and providing strategies for change
| dc.contributor.author | Abdallah, Abdelrahman M., author | |
| dc.contributor.author | Atadero, Rebecca A., advisor | |
| dc.contributor.author | Ozbek, Mehmet E., advisor | |
| dc.contributor.author | Jia, Gaofeng, committee member | |
| dc.contributor.author | Chai, Dae Seok, committee member | |
| dc.date.accessioned | 2021-09-06T10:25:58Z | |
| dc.date.available | 2021-09-06T10:25:58Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Bridge inspections are one of the key elements required for a successful bridge management process to ensure adequate bridge performance. Inspections significantly inform maintenance decisions and can help in managing maintenance activities to achieve a reliable bridge network. In the United States (U.S.) routine visual inspections are required for most bridges at a maximum interval of 24-months regardless of the bridge condition. However, limitations of current bridge inspection practices impact the quality of information provided about bridge condition and the subsequent decisions made based on that information. Accordingly, the overarching goal of this research project is to support bridge inspection practices by providing a systematic and rational framework for bridge inspection planning and identifying the factors that can facilitate innovation and research transfer in the bridge inspection field. To do so, this dissertation includes three separate yet related studies; each focusing on essential aspects of bridge inspection planning. Much research in bridge inspection has been conducted to improve the inspection planning process. The first study provides an overview of current bridge inspection practices in the U.S. and conducts a systematic literature review on innovations in the field of bridge inspection planning to identify research gaps and future needs. This study provides a background on the history of bridge inspection in the U.S., including current bridge inspection practices and their limitations, and analyzes the connections between nondestructive evaluation techniques, deterioration models and bridge inspection management. The primary emphasis of the first study is a thorough analysis of research proposing and investigating different methodologies for inspection planning. Studies were analyzed and categorized into three main types of inspection planning approaches; methods that are based on: reliability, risk analysis, and optimization approaches. This study found that one of the main barriers that may be preventing the implementation of new inspection planning frameworks in practice is that the approaches presented focus on a single bridge element or deterioration mechanism in the decision-making process. Additionally, it was concluded that approaches in the literature are either complex to apply or depend solely on expert judgement. Limitations of the uniform calendar-based approach used to schedule routine inspections have been reported in the literature. Accordingly, the objective of the second study is to provide a new systematic approach for inspection planning that integrates information from bridge condition prediction models, inspection data, and expert opinion using Bayesian analysis to enhance inspection efficiency and maintenance activities. The proposed uncertainty-based inspection framework can help bridge owners avoid unnecessary or delayed inspections and repair actions, determine the inspection method, and consider more than one deterioration process or bridge component during the inspection planning process. The inspection time and method are determined based on the uncertainty and risks associated with the bridge condition. As uncertainty in the bridge condition reaches a defined threshold, an inspection is scheduled utilizing nondestructive techniques to reduce the uncertainty level. The framework was demonstrated on a new and on an existing reinforced concrete bridge deck impacted by corrosion deterioration. The results showed that the framework can reduce the number of inspections compared to conventional scheduling methods, while also reducing the uncertainty regarding the transition in the bridge deck condition and repair time. As identified through the first study, over the last two decades many researchers have focused on providing new ideas to improve conventional bridge inspection practices, however, little guidance is provided for implementing these new research products in practice. This, along with resistance to change and complexity of the proposed ideas, resulted in a lack of consistency and success in applying new technologies in bridge inspection programs across state departments of transportation (DOTs). Accordingly, the third paper presents a qualitative study set out to identify the factors that can help improve research products and accelerate change and research transfer in bridge inspection departments. This study used semi-structured interviews, written interviews, and questionnaires for data collection and engaged with twenty-six bridge staff members from different DOTs. The findings of this study are expected to be both specific to changes in bridge inspection practice and have some generalizability to other significant changes to engineering practice at DOTs. To improve research products, this study suggested that researchers need to collaborate more with DOT staff members and provide relevant research products that are not specific to certain bridge cases and can be applied on different bridges. Also, to facilitate change in transportation organizations, change leaders should focus on showing the need for change, gaining support from the FHWA, allocating the required resources, and enhancing the capacity of DOT staff members through training and effective communication. The investigation also presented participants' opinions on some of the aspects related to conventional inspection practices such as their support of a uniform inspection interval over a variable interval, and the main barriers limiting the use of NDE methods. This study contributes to the body of knowledge in the bridge inspection field by providing a new inspection planning approach that depends on the uncertainty and the risks associated with the bridge condition and uses both computational methods and expert judgment allowing bridge owners select inspection time and method while considering more than one deterioration process or bridge element. In addition, this study presents some of the factors that can help reduce the gap between research and practice and facilitate innovation and change in transportation organizations. | |
| dc.format.medium | born digital | |
| dc.format.medium | doctoral dissertations | |
| dc.identifier | Abdallah_colostate_0053A_16639.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/233793 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2020- | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | bridge inspection | |
| dc.subject | qualitative analysis | |
| dc.subject | uncertainty quantification | |
| dc.subject | nondestructive evaluation | |
| dc.subject | Bayesian updating | |
| dc.subject | systematic review | |
| dc.title | A study on bridge inspections: identifying barriers to new practices and providing strategies for change | |
| dc.type | Text | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Civil and Environmental Engineering | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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