ORCID Identifier(s)

ORCID 0000-0002-0051-5034

Graduation Semester and Year

Summer 2024

Language

English

Document Type

Thesis

Degree Name

Master of Science in Civil Engineering

Department

Civil Engineering

First Advisor

Dr. Nur Yazdani

Second Advisor

Dr. RAAD AZZAWI

Third Advisor

Dr. ANTONIO JUAN BALDERREMA

Fourth Advisor

DR EYOSIAS SOLOMON BENEBERU

Abstract

The development of predictive models for bridge deterioration is crucial for ensuring the longevity and safety of transportation infrastructure. Bridge condition degradation is heavily influenced by environmental conditions. This research integrates various environmental variables such as rainfall, humidity, air temperature, coastal influence, and freezing effects to generate environmental risk scores. These scores help in developing environmental risk zones within the Texas region. Deck condition ratings from the National Bridge Inventory (NBI) database are used to develop deterioration models using linear regression and the Markov method. The results highlight the impact of different environmental risk zones on bridge degradation patterns and provide insights into optimizing resource allocation for maintenance.

Keywords

Bridge Deterioration, Environmental Factors, Regression Analysis, Markov Method, Predictive Models, TxDOT, Natonal Bridge Inventory (NBI)

Disciplines

Civil Engineering | Structural Engineering

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Comments

I'm deeply grateful to my advisor, Dr. Nur Yazdani, for his unwavering support and guidance throughout my research and academic journey. His mentorship has been invaluable. I would also like to thank my committee members, Dr. Raad Azzawi and Dr. Antonio Balderrema, for their consistent reviews and essential support.

A special thanks to my supervisor, Dr. Eyosias Beneberu, whose inspiration and guidance helped lay the groundwork for my research from the very beginning.

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