UTC 2022 Funding - Cycle 2 Research Projects

Project No.: CY3-OSU-03
Title: A Framework for Rapid Performance Assessment of Bridges Under Flood Hazard Using Machine Learning
Performing Institution: Oklahoma State University
Principal Investigator: Mohamed Soliman, Oklahoma State University
Start and Anticipated Completion Dates: 01/01/2026 to 01/15/2027
Abstract: Recent heavy rainfall and flood events highlight the growing threat to transportation infrastructure and their surrounding communities. Floods can severely damage bridges through pier scour, hydraulic loads, or debris impact. These effects may lead to sudden failures and impede critical emergency response and recovery operations. Traditional flood risk assessment methods often rely on expert opinion or visual inspection results, which may not accurately capture the true structural condition. Additionally, conventional stochastic approaches, while more robust, are computationally expensive and impractical for time-sensitive applications. To address these challenges, the proposed research develops a framework for rapid fragility quantification of bridges under flood conditions. The framework utilizes machine learning models that are trained to capture complex flood-structure interactions and generate predictive fragility curves for failure assessment and/or risk-based decision-making. The framework considers flood and bridge attributes to generate the fragility profile directly in real-time. Accordingly, this approach enables faster, more reliable, and computationally efficient assessment compared to traditional methods. Rather than focusing on a single bridge, the framework will be trained using high-fidelity finite element analysis results from an ensemble of models that covers a particular class of bridges. After training, the framework can generate the fragility profiles of any bridge within the class given the bridge attributes (e.g., span length, number of lanes, foundation type, etc.). At this stage, focus will be placed on single- or multi-span, simply supported girder bridges (steel or concrete). Other bridge types may be considered in subsequent studies. 
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