Informing Predictions from Above with Data and Below: AI-Driven Seismic Ground-Failure Model for Rapid Response and Scenario Planning
Soil liquefaction is a significant threat to post-earthquake mobility across nearly all modes of transportation. This Small Project will develop an open source, high-resolution model to probabilistically predict liquefaction regionally - at no cost to the user - both in future scenario earthquakes (to inform mitigation and planning) or immediately following an event (to inform response and recovery). This model will: (1) predict subsurface test measurements via remotely-sensed predictor variables and machine- and/or deep-learning models; (2) be anchored to a mechanics-based framework for predicting liquefaction via subsurface test data, thus physically constraining the predictions; (3) have rapid capabilities, providing regional predictions minutes after an earthquake. The model would first be implemented in PacTrans Region 10 using PNW data, but would be scalable to a larger study, and transferrable globally. In addition to providing the model to the transportation industry (via matlab and python code, and as windows-executable software), the project will use the model to simulate Region 10 events.
Language
- English
Project
- Status: Active
- Funding: $50000
-
Contract Numbers:
69A3551747110
-
Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Pacific Northwest Transportation Consortium
University of Washington
More Hall Room 112
Seattle, WA United States 98195-2700 -
Project Managers:
Maurer, Brett
-
Performing Organizations:
University of Washington, Seattle
Civil and Environmental Engineering Department
201 More Hall, Box 352700
Seattle, WA United States 98195-2700 -
Principal Investigators:
Maurer, Brett
- Start Date: 20200916
- Expected Completion Date: 20220915
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Artificial intelligence; Earthquakes; Forecasting; Liquefaction; Machine learning; Seismicity; Simulation
- Geographic Terms: Pacific Northwest
- Subject Areas: Geotechnology; Planning and Forecasting; Transportation (General);
Filing Info
- Accession Number: 01764504
- Record Type: Research project
- Source Agency: Pacific Northwest Transportation Consortium
- Contract Numbers: 69A3551747110
- Files: UTC, RiP
- Created Date: Feb 5 2021 5:10PM