Date: 5/2/2018, 1:00 PM-2:00 PM EDT
Location: 1200 New Jersey Ave, SE, Washington, DC, (West Building) Conference Center Room 6
Speaker: Frank L. Moon, Ph.D., Professor, Civil and Environmental Engineering
Organization: Center for Advanced Infrastructure and Transportation (CAIT), Rutgers, The State University of New Jersey
OST-R Office: Office of the Assistant Secretary for Research and Technology (OST-R), University Transportation Centers Program
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While additional funding is a necessary condition to meet the challenges posed by the aging U.S. bridge population, funding alone will not be sufficient. Rather, realizing a sustainable approach to our transportation infrastructure will require new assessment strategies that better quantify risks, diagnose performance problems, and inform decisions related to infrastructure interventions. In addition, more accurate means of forecasting future condition and identifying new and effective intervention approaches is also needed.
The objective of this presentation is to provide a high-level overview of three emerging technologies that aim to fill these critical roles. In particular, the presentation will provide an overview of (a) the state-of-the-art in nondestructive evaluation of reinforced concrete bridge decks, (b) a self-contained vehicle capable of performing rapid modal testing and refined load rating of highway bridges, and (c) the newly commissioned Bridge Evaluation and Accelerated Structural Testing (BEAST) Laboratory at Rutgers (view lecture poster).
Dr. Frank Moon is a Professor of Civil and Environmental Engineering at Rutgers University and as a leader in infrastructure performance and vulnerability, he has particular expertise in sensing technologies, structural identification, structural health monitoring, numerical modeling, and estimation of service life. His research has resulted in a unique system (termed THMPER) capable of performing rapid structural safety assessment of highway bridges; a novel temperature-driven response approach to structural concerns; and various model-experiment correlation strategies to assess infrastructure vulnerability with a focus on multiple model techniques.
DISCLAIMER: The views, opinions, findings and conclusions reflected in this presentation are the responsibility of the authors only and do not represent the official policy or position of the USDOT/OST-R, or any State or other entity.
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