Please join us for NDPTC Third Thursday Webinar
Posted on July 22, 2021
NDPTC hosts the 3rd Thursday webinar featuring Pacific Southwest Regional University Transportation Center Grant Recipients
NDPTC will be hosting its monthly 3rd Thursday lecture on July 22, 2021, at 12:00 PM (HST)/3:00 PM (PST)/6:00 PM (EST). This month features two recipients of our Pacific Southwest Region University Transportation Center grants. To Register go to: https://zoom.us/meeting/register/tJMkceypqjstE9e5EPd015-36ih9UXhg0Lwf
Dr. Chunhee Cho
Bridge monitoring through a hybrid approach leveraging a modal updating technique and an artificial intelligence (AI) method.
An early damage identification process in bridge structures may offer an opportunity to slow down progressive failure and thus prevent catastrophic collapses. With a structural health monitoring system that allows real-time measurement of structural responses, this may be possible if proper techniques are employed to identify early damage in bridge structures. In doing so, the proposed project will integrate two methods (i.e., a model updating technique and artificial intelligence (AI) prediction) that can compensate for each other’s weaknesses that otherwise imposed difficulty in the precise real-time application of health monitoring systems. This project will leverage a mode-updating technique with high-fidelity experimental data to obtain an accurate digital model that represents an actual bridge model. The drawback of the model updating technique (i.e., high computational time) will be overcome by applying an artificial intelligence algorithm such as artificial neural networks that are known to be computationally efficient while perusing high accuracy. The proposed approach will then result in a fast and accurate method (i.e., a model-based data-driven method) for early damage identification of bridge structures.
Dr. DoSoo Moon
Integrated Hazard Vulnerability Assessment and Mitigation Framework with Mixed Reality for Transportation Infrastructures.
Transportation infrastructure deterioration and its impact on lifetime structural performance are the foremost concerns of the USDOT. The structural damage due to physical or chemical causes weakens transportation infrastructures; consequently, the degrading infrastructures are getting more susceptible to various natural hazards and disasters, including coastal hazards (e.g., erosion, storms, sea-level rise). To improve the resilience of such weakening transportation infrastructures, accurate estimations of structural performance under an extreme event and possible performance degradation induced by reported damages from routine infrastructure inspection are required. Also, for proper maintenance and operation of the transportation infrastructure, information about how overall infrastructure performance would be affected by the detected damages should be readily available for decision-makers and stakeholders. Thus, there is a strong need to develop an advanced and interactive hazard risk management framework for transportation infrastructures where users can easily check the location of meaningful damages, their effects on infrastructure vulnerability, and expected economic and life losses caused by a certain hazard. The goal of the proposed research project is to develop an integrated hazard vulnerability assessment and mitigation framework for transportation infrastructures with progressive vulnerability evaluation and mixed reality (MR). The MR technology will help decision-makers better and easily understand the results from the complex structural performance assessment. The proposed framework will enable engineers to manage the damage and degradation propagation over time, mitigate hazard risk, estimate transportation infrastructure lifetime, and optimize maintenance time and cost.