Author ORCID Identifier
Semester
Spring
Date of Graduation
2025
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Civil and Environmental Engineering
Committee Chair
Yoojung Yoon
Committee Co-Chair
Fei Dai
Committee Member
James Bryce
Abstract
State Departments of Transportation (DOTs) are responsible for maintaining approximately 623,000 bridges across the United States. Effective bridge management requires a comprehensive understanding of the factors influencing structural deterioration. Numerous studies have explored the effects of average daily traffic (ADT) and deck area (DA) on bridge deck deterioration. Given the interdependence between bridge decks and superstructures, it is plausible that ADT and DA significantly influence superstructure condition ratings and deterioration trends. However, their impact on superstructures remains insufficiently studied. In addition, existing studies primarily focus on overall bridge deterioration without adequately differentiating between superstructure designs and materials and maintenance authorities. This gap in knowledge limits the ability to develop targeted maintenance strategies for bridge superstructures.
To address this gap, this study aims to systematically analyze the effects of ADT and DA on bridge superstructures, categorized by maintenance authority and structural design and material types. National Bridge Inventory (NBI) dataset for Ohio bridges was selected for its availability through an ODOT-funded research project, providing comprehensive and high-quality bridge data from 1980 to 2023. This research develops deterioration models to assess the degradation patterns of four primary superstructure types: Stringer, Slab, Frame, and Box Beam. For more granular insights, the Box Beam category is further divided into Box Beam with Concrete Wearing Surface and Box Beam with Asphalt Wearing Surface. The Stringer category is split into Stringer with Steel Beams and Stringer with Reinforced Concrete (RC) or Prestressed Concrete (PS) Beams. The dataset is further segmented based on primary maintenance authorities (County and State-owned) and grouped into three ADT and three DA categories for a comprehensive evaluation.
The research employs a multifaceted methodological approach. The age reset technique is implemented to generate pure deterioration curves by eliminating the influence of major repairs and rehabilitations, and outliers are removed to enhance model accuracy and reliability. Regression Nonlinear Optimization (RNO) modeling is applied to develop deterioration models, with Python used for plotting best-fit polynomial regression curves and MS Excel for optimizing Markovian transition probability matrices. Additionally, the Dynamic Time Warping (DTW) method is utilized to analyze variations in deterioration patterns across different ADT and DA groups for each superstructure type.
The findings reveal distinct deterioration patterns across superstructure types for state- and county-owned bridges. In county bridges, RC or PS stringers and box beams with concrete wearing surfaces deteriorate faster under higher ADT, while asphalt-wearing box beams show greater deterioration under lower ADT, likely due to limited maintenance. Smaller deck areas also correlate with faster early deterioration, especially in RC/PS stringers and concrete box beams. Slab and frame types remain relatively stable across ADT and DA groups. In state bridges, higher ADT leads to faster deterioration in RC/PS stringers, frame structures, and box beams with both wearing surfaces, though high-ADT bridges often stabilize in later years. Slab and steel stringers show minimal sensitivity. Larger deck areas (DA > 12000) contribute to faster early deterioration in RC/PS stringers, frames, and concrete box beams, while asphalt-wearing box beams show some DA-based variation in later years.
This research advances the knowledge of the influence of ADT and DA on superstructure deterioration, leading to reliable superstructure deterioration models. While Ohio’s bridge network serves as the focus of this study, this research motivates other state DOTs to conduct similar studies to better understand how ADT and DA influence deterioration trends in their specific contexts. These findings enable bridge maintenance authorities to recognize the significance of customizing maintenance strategies according to the ADT and DA, thereby aiding allocate resources effectively and improving the long-term longevity of bridge infrastructure.
Recommended Citation
Ahamed, Faysal, "INFLUENCE OF DECK AREA AND AVERAGE DAILY TRAFFIC ON THE DETERIORATION OF BRIDGE SUPERSTRUCTURES." (2025). Graduate Theses, Dissertations, and Problem Reports. 12866.
https://researchrepository.wvu.edu/etd/12866