Ground motion time series to accompany "A predictive model for fling-step in near-fault ground motions based on recordings and simulations"
Abstract/Contents
- Abstract
- We identify potential data sources for fling-step and discuss their value, compile a dataset of simulated and recorded ground motions containing fling, extract fling pulses from these ground motions, and derive a predictive model for fling amplitude and period that is compared to existing empirical models. Fling is the result of permanent static offset of the ground during an earthquake, but is usually ignored because ground motion records from accelerometers contain errors that make it difficult to measure static offsets. However, some data sources include fling, such as specially processed recordings, ground motion simulations, and high-rate global positioning systems (GPS). From this data, we extract fling pulses using the pattern search global optimization algorithm. The resulting displacement amplitudes and periods are used to create a new predictive equation for fling parameters, are compared to existing empirical models for pulse period, fling amplitude, and surface displacement along the fault, and are found to match reasonably well.
Description
Type of resource | software, multimedia |
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Date created | 2015 |
Creators/Contributors
Author | Burks, Lynne |
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Author | Baker, Jack |
Subjects
Subject | Ground motion |
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Subject | earthquake |
Subject | time series |
Genre | Dataset |
Bibliographic information
Related Publication | Lynne S. Burks and Jack W. Baker (2016). A predictive model for fling-step in near-fault ground motions based on recordings and simulations. Soil Dynamics and Earthquake Engineering. 80, 119–126. |
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Related item | |
Location | https://purl.stanford.edu/pz055cs5875 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
Preferred citation
- Preferred Citation
- Burks, Lynne and Baker, Jack. (2016). Ground motion time series to accompany "A predictive model for fling-step in near-fault ground motions based on recordings and simulations". Stanford Digital Repository. Available at: http://purl.stanford.edu/pz055cs5875
Collection
Software and data produced by Baker Research Group
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- Contact
- bakerjw@stanford.edu
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