Temperature-Driven Structural Identification for Bridge Performance Evaluation
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Bridges serve as integral components of infrastructure all around the world. Their direct impact to society is substantial, and their reliability is paramount. As such, confidence in the integrity of these structures is important not only for individuals who utilize these structures but also for the bridge owners and engineers who operate and maintain them. In order to develop a comprehensive understanding of the structural behavior, evaluations are conducted to assess the structure’s performance. By utilizing input-output relationships between loads and responses, structural performance evaluations provide an opportunity to assess unique bridge behavior such as complex mechanisms or deterioration. The research presented herein investigates a novel, temperature-driven concept for bridge performance evaluation wherein thermal behavior in response to environmental temperature changes is used to assess the structure. Within this research, two bridges are evaluated using a probabilistic approach of single and multiple model updating within the temperature-driven structural identification process. This technique utilizes Latin Hypercube Sampling as well as Bayesian calibration to identify unknown bridge parameters and evaluate the structural performance. Then, these studies are compiled into a synthesis of temperature-driven evaluations from nineteen bridge studies throughout the world to develop a comprehensive framework and to provide guidance for using thermal behavior for performance evaluations. The intellectual merit from each study illuminates various motivations, methods, successes, and challenges of temperature-driven evaluations. Guidance regarding structure details, monitoring criteria, as well as data and analysis is provided to assist bridge owners, engineers, and researchers who utilize this temperature-driven technique to conduct evaluations. Based on the research presented herein, temperature-driven performance evaluations provide extensive insight, not only to the thermal behavior of the bridge, but the overall structural health.
Murphy, Brittany Rene (2019). Temperature-Driven Structural Identification for Bridge Performance Evaluation. Doctoral dissertation, Texas A & M University. Available electronically from