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Ground-motion variability for single site and single source through deterministic stochastic method simulations: implications for PSHA
Author(s)
Language
English
Obiettivo Specifico
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Issue/vol(year)
2/107 (2017)
Pages (printed)
966-983
Issued date
April 2017
Alternative Location
Subjects
Abstract
The ground-motion median and standard deviation of empirical groundmotion
prediction equations (GMPEs) are usually poorly constrained in the nearsource
region due to the general lack of strong-motion records. Here we explore the
use of a deterministic–stochastic simulation technique, specifically tailored to reproduce
directivity effects, to evaluate the expected ground motion and its variability at a
near-source site, and seek a strategy to overcome the known GMPEs limitations.
To this end, we simulated a large number of equally likely scenario events for three
earthquake magnitudes (Mw 7.0, 6.0, and 5.0) and various source-to-site distances. The
variability of the explored synthetic ground motion is heteroscedastic, with smaller
values for larger earthquakes. The standard deviation is comparable with empirical
estimates for smaller events and reduces by 30%–40% for stronger earthquakes.
We then illustrate how to incorporate directivity effects into probabilistic seismichazard
analysis (PSHA). This goal is pursued by calibrating a set of synthetic GMPEs
and reducing their aleatory variability (∼50%) by including a predictive directivity
term that depends on the apparent stress parameter obtained through the simulation
method. Our results show that, for specific source-to-site configurations, the nonergodic
PSHA is very sensitive to the additional epistemic uncertainty that may augment
the exceedance probabilities when directivity effects are maximized.
The proposed approach may represent a suitable way to compute more accurate
hazard estimates.
prediction equations (GMPEs) are usually poorly constrained in the nearsource
region due to the general lack of strong-motion records. Here we explore the
use of a deterministic–stochastic simulation technique, specifically tailored to reproduce
directivity effects, to evaluate the expected ground motion and its variability at a
near-source site, and seek a strategy to overcome the known GMPEs limitations.
To this end, we simulated a large number of equally likely scenario events for three
earthquake magnitudes (Mw 7.0, 6.0, and 5.0) and various source-to-site distances. The
variability of the explored synthetic ground motion is heteroscedastic, with smaller
values for larger earthquakes. The standard deviation is comparable with empirical
estimates for smaller events and reduces by 30%–40% for stronger earthquakes.
We then illustrate how to incorporate directivity effects into probabilistic seismichazard
analysis (PSHA). This goal is pursued by calibrating a set of synthetic GMPEs
and reducing their aleatory variability (∼50%) by including a predictive directivity
term that depends on the apparent stress parameter obtained through the simulation
method. Our results show that, for specific source-to-site configurations, the nonergodic
PSHA is very sensitive to the additional epistemic uncertainty that may augment
the exceedance probabilities when directivity effects are maximized.
The proposed approach may represent a suitable way to compute more accurate
hazard estimates.
Sponsors
This work was supported by the project MASSIMO—Cultural Heritage
Monitoring in Seismic Area, PON01/02710—coordinated by Istituto
Nazionale di Geofisica e Vulcanologia (INGV) and funded by the Italian
Ministry of Education, University and Research and by the Seismic Hazard
Center of Istituto Nazionale di Geofisica e Vulcanologia (Centro per la Pericolosità
Sismica [CPS]).
Monitoring in Seismic Area, PON01/02710—coordinated by Istituto
Nazionale di Geofisica e Vulcanologia (INGV) and funded by the Italian
Ministry of Education, University and Research and by the Seismic Hazard
Center of Istituto Nazionale di Geofisica e Vulcanologia (Centro per la Pericolosità
Sismica [CPS]).
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Dynam. 36, 1275–1301, doi: 10.1002/eqe.679.
Al Atik, L., N. Abrahamson, J. J. Bommer, F. Scherbaum, F. Cotton, and N.
Kuehn (2010). The variability of ground-motion prediction models and
its components, Seismol. Res. Lett. 81, 794–801, doi: 10.1785/
gssrl.81.5.794.
Ambraseys, N. N., J. Douglas, S. K. Sarma, and P. M. Smit (2005). Equations
for the estimation of strong ground motions from shallow crustal
earthquakes using data from Europe and the Middle East: Vertical peak
ground acceleration and spectral acceleration, Bull. Earthq. Eng. 3,
55–73, doi: 10.1007/s10518-005-0186-x.
Ameri, G., A. Emolo, F. Pacor, and F. Gallovic (2011). Ground-motion
simulations for the 1980 M 6.9 Irpinia earthquake (southern Italy)and scenario events, Bull. Seismol. Soc. Am. 101, 1136–1151, doi:
10.1785/0120100231.
Ameri, G., F. Gallovic, F. Pacor, and A. Emolo (2009). Uncertainties in strong
ground-motion prediction with finite-fault synthetic seismograms: An
application to the 1984 M 5.7 Gubbio, Central Italy, earthquake, Bull.
Seismol. Soc. Am. 99, 647–663, doi: 10.1785/0120080240.
Ameri, G., F. Pacor, G. Cultrera, and G. Franceschina (2008). Deterministic
ground-motion scenarios for engineering applications: The case of
Thessaloniki, Greece, Bull. Seismol. Soc. Am. 98, 1289–1303, doi:
10.1785/0120070114.
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Loads for Buildings and Other Structures, (ASCE/SEI 7-05), ASCE,
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Loads for Buildings and Other Structures, (ASCE/SEI 7-10), ASCE,
Reston, Virginia.
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without the ergodic assumption, Seismol. Res. Lett. 70, 19–28, doi:
10.1785/gssrl.70.1.19.
Anderson, J. G., and S. E. Hough (1984). A model for the shape of the Fourier
amplitude spectrum of acceleration at high frequencies, Bull. Seismol.
Soc. Am. 74, 1969–1993.
Atkinson, G. M. (2015). Ground-motion prediction equation for smallto-
moderate events at short hypocentral distances, with application to
induced-seismicity hazards, Bull. Seismol. Soc. Am. 105, 981–992,
doi: 10.1785/0120140142.
Atkinson, G. M., and D. M. Boore (2006). Earthquake ground-motion prediction
equations for eastern North America, Bull. Seismol. Soc. Am.
96, 2181–2205.
Barberi, G., M. T. Cosentino, A. Gervasi, I. Guerra, G. Neri, and B. Orecchio
(2004). Crustal seismic tomography in the Calabrian Arc region, south
Italy, Phys. Earth Planet. In. 147, 297–314, doi: 10.1016/j.
pepi.2004.04.005.
Basili, R., G. Valensise, P. Vannoli, P. Burrato, U. Fracassi, S. Mariano, M.
M. Tiberti, and E. Boschi (2008). The Database of Individual Seismogenic
Sources (DISS), version 3: Summarizing 20 years of research on
Italy’s earthquake geology, Tectonophysics 453, 20–43, doi: 10.1016/j.
tecto.2007.04.014.
Bazzurro, P., and C. A. Cornell (1999). Disaggregation of seismic hazard,
Bull. Seismol. Soc. Am. 89, 501–520.
Bernard, P., and R. Madariaga (1984). A new asymptotic method for the modeling
of near-field accelerograms, Bull. Seismol. Soc. Am. 74, 539–557.
Bindi, D., M. Massa, L. Luzi, G. Ameri, F. Pacor, R. Puglia, and P. Augliera
(2014). Pan-European ground-motion prediction equations for the
average horizontal component of PGA, PGV, and 5%-damped PSA
at spectral periods up to 3.0 s using the RESORCE dataset, Bull.
Earthq. Eng. 12, 391–430, doi: 10.1007/s10518-013-9525-5.
Bommer, J. J. (2002). Deterministic vs. probabilistic seismic hazard assessment:
An exaggerated and obstructive dichotomy, J. Earthq. Eng. 6,
43–73, doi: 10.1080/13632460209350432.
Bommer, J. J., and N. A. Abrahamson (2006). Why do modern probabilistic
seismic-hazard analyses often lead to increased hazard estimates? Bull.
Seismol. Soc. Am. 96, 1967–1977, doi: 10.1785/0120060043.
Bommer, J. J., P. J. Stafford, J. E. Alarcon, and S. Akkar (2007). The influence
of magnitude range on empirical ground-motion prediction,
Bull. Seismol. Soc. Am. 97, 2152–2170, doi: 10.1785/0120070081.
Boore, D. M. (1983). Stochastic simulation of high-frequency ground
motions based on seismological models of the radiated spectra, Bull.
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