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Goals
In order to develop a solid Earth science framework for understanding and studying active tectonic and earthquake processes, we are developing simulation and analysis tools to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to the simulations. These codes must be adapted to high-performance computers because the solid Earth system is extremely complex and nonlinear, resulting in computationally intensive problems with millions of unknowns. Without these tools it will be impossible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.
Aside from studying tectonic and earthquake processes, the QuakeSim team will also be studying volcanic eruptions, landslides, and climate change. By studying these natural hazards and changes, we plan to expand our knowledge and abilities not only with earthquakes but other physical changes to the Earth and its environment.
Our objective...
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Develop real-time, large-scale, data assimilation grid implementation for the study of earthquakes.
- Assimilate distributed data sources and complex models into a parallel high-performance earthquake simulation and forecasting system.
- Simplify data discovery, access, and usage from the scientific user point of view.
- Provide capabilities for efficient data mining.
- Establish the necessary infrastructure and develop optimal techniques to understand the relationship between the observable space-time patterns of earthquakes and the underlying, nonlinear stress-strain dynamics that are inaccessible or unobservable in nature.
- Fully three-dimensional finite element code (FEM) with adaptive mesh generator capable of running on workstations and supercomputers for carrying out earthquake simulations
- Inversion algorithms and assimilation codes for constraining the models and simulations with data
- Visualization codes for interpretation of data and models
- Pattern recognizers capable of running on workstations and supercomputers for analyzing data and simulations
- Improve forecasting and prediction of earthquakes, volcanic eruptions, and landslides
- Earthquake risk estimation
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Characterize the effects of changing climate and land use on species habitats and carbon budget
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Predict the response of ice sheets to climate change and impact on sea level
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Monitor the migration of fluids associated with hydrocarbon production and groundwater resources
Approach...
- Integrate real-time and archival sensor data with high-performance computing applications for data mining and assimilation to improve earthquake forecasts, ultimately leading to earthquake damage mitigation
- Federate sensor data sources, focusing on InSAR, LIDAR, and GPS, for an improved modeling environment for forecasting earthquakes, volcanic eruptions, and landslides as well as understand the effects of climate change on Earth and its environment.
- Extend QuakeSim to interact with high-end computing resources at Ames Research Center and JPL
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