Project Grant 2242590

Award Date 1/1/24
Completion Date 12/31/25
Dollars Obligated $392K
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Baltimore, MD 21218, USA
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The National Science Foundation (NSF) Directorate for Engineering has awarded a $391,951 Project Grant to The Johns Hopkins University to develop a novel system for rapidly and accurately assessing cascading seismic hazards and impacts using satellite imagery and causal modeling. The project, funded under the NSF Engineering program (CFDA 47.041), aims to integrate satellite data with existing geophysical and structural fragility models to jointly estimate the occurrence and location of multi-hazard events like ground shaking, landslides, and building damage in near real-time after an earthquake.

Key components of the project include:

  1. Establishing a causal Bayesian network model to capture the complex dependencies among seismic hazards and impacts
  2. Developing an online variational Bayesian inference framework to efficiently update hazard and impact estimates using satellite data
  3. Updating local hazard and fragility models based on the causal patterns learned from the Bayesian network

The research will be demonstrated on multiple global earthquake events. The project also includes a $54,789 sub-award to Stanford University to work on the causal modeling and inference aspects. Overall, this NSF-funded project aims to enhance the accuracy, timeliness, and scalability of post-earthquake disaster response and resilience planning through advanced data integration and analysis techniques.

Generated 8/13/24, 5:57 AM