Informing Predictions from Above with Data and Below: AI-Driven Seismic Ground-Failure Model for Rapid Response and Scenario Planning
| 项目名称： | Informing Predictions from Above with Data and Below: AI-Driven Seismic Ground-Failure Model for Rapid Response and Scenario Planning |
| 摘要： | 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. |
| 状态： | Active |
| 资金： | 50000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Maurer, Brett W |
| 执行机构： | University of Washington, Seattle |
| 开始时间： | 20200916 |
| 预计完成日期： | 20220915 |
| 主题领域： | Geotechnology；Planning and Forecasting；Transportation (General) |
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