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Community seismic network and localized earthquake situational awareness

Kohler, M. D. and Guy, R. and Bunn, J. and Massari, A. and Clayton, R. and Heaton, T. and Chandy, K. M. and Ebrahimian, H. and Dorn, C. (2018) Community seismic network and localized earthquake situational awareness. In: Eleventh U.S. National Conference on Earthquake Engineering, 25-29 June 2018, Los Angeles, CA. http://resolver.caltech.edu/CaltechAUTHORS:20180713-133233514

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Abstract

Community-hosted seismic networks are a solution to the need for large numbers of sensors to operate over a seismically active region in order to accurately measure the size and location of an earthquake, assess resulting damage, and provide alerts. The Community Seismic Network is one such strong-motion network, currently comprising hundreds of elements located in California. It consists of low-cost, three-component, MEMS accelerometers capable of recording accelerations up to twice the level of gravity. The primary product of the network is to produce measurements of shaking of the ground and multiple locations of every upper floor in buildings, in the seconds during and following a major earthquake. Each sensor uses a small, dedicated ARM processor computer running Linux, and analyzes time series data in real time at hundreds of samples per second. The network reports on shaking parameters that indicate intensity of the structural response levels such as maximum floor acceleration and velocity, displacement of a floor in a building, as well as data products that depend on the response time histories. To do this, Cloud computing has been expanded through the use of statically defined subsets of sensors called cloudlets. These are smaller subsets of similar sensors that carry out customized calculations for those locations. The measurements are reported as rapidly as possible following an earthquake so that they may be incorporated into structural diagnosis and prognosis applications that can be used by first responders to prioritize their initial disaster management efforts. The cloudlet displays are customized for specific buildings and they show in real time: instantaneous displacement, inter-story drift, and resonant frequency and mode shapes using system identification software tools. The real-time display products are useful for decision-making about whether the potential for damage exists, what level of damage may have occurred and where, and whether total business disruption is necessary. City-wide dense monitoring makes it possible for emergency response managers to prioritize the target locations requiring first response on a block-by-block scale based on reports of shaking intensity.


Item Type:Conference or Workshop Item (Paper)
ORCID:
AuthorORCID
Massari, A.0000-0002-6561-4674
Clayton, R.0000-0003-3323-3508
Heaton, T.0000-0003-3363-2197
Additional Information:This study was partially funded by a Caltech-JPL Research and Technology Development Fund grant. We also thank the Betty and Gordon Moore Foundation, the Terrestrial Hazard Observation and Reporting Center at Caltech, and the Divisions of Geological and Planetary Science, and Engineering and Applied Science at Caltech for funding the development of the Community Seismic Network.
Group:Earthquake Engineering Research Laboratory, Seismological Laboratory
Funders:
Funding AgencyGrant Number
Caltech-JPL Research and Technology Development FundUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Terrestrial Hazard Observation and Reporting CenterUNSPECIFIED
Caltech Division of Geological and Planetary ScienceUNSPECIFIED
Caltech Division of Engineering and Applied ScienceUNSPECIFIED
Other Numbering System:
Other Numbering System NameOther Numbering System ID
EERL Report2018-04
Record Number:CaltechAUTHORS:20180713-133233514
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180713-133233514
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:87838
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:13 Jul 2018 21:32
Last Modified:03 Apr 2019 18:31

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