Grace Alexandra Parker
Eric M. Thompson
Scott J. Brandenberg
Meibai Li
Okan Ilhan
Youssef Hashash
Ellen Rathje
Jonathan P. Stewart
María E. Ramos-Sepulveda
2023
<div id="texttabcontent" class="tab-pane no-scroll show-content left-sided" aria-labelledby="texttab"><div class="NLM_sec NLM_sec_level_1 hlFld-Abstract"><p>Earthquake ground motion processing for next-generation attenuation (NGA) projects required human inspection to select high-pass corner frequencies (<i>f</i><sub><i>cHP</i></sub>), which is time-intensive and subjective. With growth in the number of recordings per event and interest in enhancing repeatability, we sought to develop automated procedures for<span> </span><i>f</i><sub><i>cHP</i></sub><span> </span>selection. These procedures consider signal-to-noise ratio (SNR) and non-physical features in the displacement time series that indicate high- and/or low-frequency noise effects. The procedures are implemented in a US Geological Survey software package (gmprocess). We extend previous procedures for SNR-based corner frequency selection to also check for low-frequency artifacts in the displacement record using a polynomial fit to improve<span> </span><i>f</i><sub><i>cHP</i></sub><span> </span>selection. We evaluate the performance of the SNR and polynomial fit criteria using recordings from the 2020 M5.1 North Carolina and the 2013 M4.7 Southern Ontario earthquakes. Data processed with the SNR-only criteria can have low<span> </span><i>f</i><sub><i>cHP</i></sub><span> </span>and displacement drift; the displacement check increases<span> </span><i>f</i><sub><i>cHP</i></sub><span> </span>and reduces displacement drift.</p></div></div>
application/pdf
10.1061/9780784484692.034
en
ASCE Library
High-pass corner frequency selection for implementation in the USGS automated ground motion processing tool
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