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Collaborative Research: ITR/NGS: Multiresolution High Fidelity Earthquake Modeling: Dynamic Rupture, Basin Response, Blind Deconvolution Seismic Inversion, and Ultrascale Computing

$742,109FY2003GEONSF

San Diego State University Foundation, San Diego CA

Investigators

Abstract

This project is aimed at developing a three-dimensional seismic inverse model and then using it to obtain information about the both three-dimensional structure of the Greater Los Angeles Basin and the nature of fault rupture during recent major Southern California earthquakes such as the Landers and Northridge earthquakes. At the end of the project these tools will also be applied to the Kanto Basin and the 1923 Kanto Earthquake. The project will capitalize on both the recent and projected growth in seismic networks deployed in Southern California and the increase in the capabilities of supercomputing systems. The inverse problem is very large. Part of the project involves structuring the inverse model so that it will run well on large parallel systems. Most of this work will be done on single systems such as those available at National Science Foundation and Department of Energy computing centers; however, because the inverse model requires many iterations of forward and adjoint runs, it has a coarse granularity that the investigators plan to exploit by also deploying the inverse model on the distributed computing environment of the Teragrid. The long-term benefits of this work are likely to be a better understanding of the geological structure of the Greater Los Angeles Basin, a better understanding of fault rupture, and improvements in the ability to predict strong ground motion. Sophisticated seismic inversion tools of the sort developed here will help researchers gain maximum benefit from the data that will start to come on-line in the next few years from the United States Array.

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Collaborative Research: ITR/NGS: Multiresolution High Fidelity Earthquake Modeling: Dynamic Rupture, Basin Response, Blind Deconvolution Seismic Inversion, and Ultrascale Computing · GrantIndex