Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted material contained within this report. Figures Figure 1. Plot of acceleration, velocity, and displacement time series from zoc processing. Note that the grainy appearance is a result of the time series values being replaced by an average value per pixel, thus greatly speeding up the plotting and reducing the file size.. Figure 2. Plot of displacement time series from zoc (top) and filtered processing. The 2nd and 3rd traces are for a 0.02 Hz acausal low-cut filter, with no taper and a taper of 20 s where the training zeros are added to the data; the bottom two traces show the same thing for a 0. Figure 3. Plot of displacement time series from zoc (top) and filtered processing, with and without tapers where the training zeros are added to the data.. Figure 10. FAS for the sample record. The blue line has a slope of 2, as expected from simple source theory; its location was determined by eye.. Figure 11. A suite of displacements from filtered accelerations. The filter frequencies are part of the time series name above each trace (e.g., " alc00.431ns08 " indicates that an acausal low-cut filter with corner frequency of 0.431 Hz and an order such that the filter goes as f 8 at low frequencies was used). For ease of comparison, only pad-stripped time series are shown.. Figure 12. A suite of displacements from filtered accelerations. The filter frequencies are part of the time series name above each trace (e.g., " alc00.431ns08 " indicates that an acausal low-cut filter with corner frequency of 0.431 Hz and an order such that the filter goes as f 8 at low frequencies was used). Tapers of 2 s and 5 s were applied to the beginning and end of the original record, respectively, before adding zero pads and filtering. For ease of comparison, only pad-stripped time series are shown.. Figure 13. Response spectra for the zoc acceleration and for ten filters (only the response specta for three of the filters are distinguished by color). Also shown are the spectra for the tapered and filtered time series-clearly tapering makes little difference in the response spectra..
[1]
D. Boore.
Orientation-independent, nongeometric-mean measures of seismic intensity from two horizontal components of motion
,
2010
.
[2]
Julian J. Bommer,et al.
Processing of strong-motion accelerograms: needs, options and consequences
,
2005
.
[3]
William H. Press,et al.
Numerical recipes in C. The art of scientific computing
,
1987
.
[4]
N. Abrahamson,et al.
Orientation-Independent Measures of Ground Motion
,
2006
.
[5]
David M. Boore,et al.
Long-Period Ground Motions from Digital Acceleration Recordings: A New Era in Engineering Seismology
,
2005
.
[6]
David M. Boore,et al.
Phase Derivatives and Simulation of Strong Ground Motions
,
2003
.
[7]
W. B. Joyner,et al.
Equations for Estimating Horizontal Response Spectra and Peak Acceleration from Western North American Earthquakes: A Summary of Recent Work
,
1997
.
[8]
David M. Boore,et al.
On Pads and Filters: Processing Strong-Motion Data
,
2005
.
[9]
W. B. Joyner,et al.
ESTIMATION OF RESPONSE SPECTRA AND PEAK ACCELERATIONS FROM WESTERN NORTH AMERICAN EARTHQUAKES: AN INTERIM REPORT PART 2
,
1993
.
[10]
T. Ohmachi,et al.
Ground Motion Characteristics Estimated from Spectral Ratio between Horizontal and Verticcl Components of Mietremors.
,
1997
.
[11]
D. Boore,et al.
Effect of causal and acausal filters on elastic and inelastic response spectra
,
2003
.
[12]
David M. Boore.
Analog-to-Digital Conversion as a Source of Drifts in Displacements Derived from Digital Recordings of Ground Acceleration
,
2003
.
[13]
W. Press,et al.
The Art of Scientific Computing Second Edition
,
1998
.
[14]
John Douglas,et al.
Long‐period earthquake ground displacements recorded on Guadeloupe (French Antilles)
,
2007
.