Notice of Intent: Improving the Performance of the Finite Fault Rupture Detector (FinDer) Algorithm in the US West Coast ShakeAlert System

The summary for the Notice of Intent: Improving the Performance of the Finite Fault Rupture Detector (FinDer) Algorithm in the US West Coast ShakeAlert System grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Geological Survey, which is the U.S. government agency offering this grant.

Notice of Intent: Improving the Performance of the Finite Fault Rupture Detector (FinDer) Algorithm in the US West Coast ShakeAlert System: Notice of Intent to award a cooperative agreement to the Swiss Federal Institute of Technology Zurich (ETH Zurich) in support of the project entitled "Improving the Performance of the Finite Fault Rupture Detector (FinDer) Algorithm in the US West Coast ShakeAlert System". The purpose of this cooperative agreement is to continue and further the Earthquake Hazards Program's collaborative research project to operate, support, improve and expand the ability of seismic and geodetic networks in high-risk areas of the U.S. to provide warnings of earthquakes when strong shaking has begun, so that property damage, injury, and loss of life can be reduced in affected areas. ETH Zurich has been directlyresponsible for the FinDer algorithm since its inception and inclusion in theShakeAlert system. ETH Zurich is the only institution that knows the FinDeralgorithm well enough to further develop it to meet the requirements ofShakeAlert. ETH Zurich has also previously collaborated with USGS and the otherShakeAlert institutions, and has demonstrated theirabilities to apply related research and development during the previous phasesof early warning algorithm development.