FINSIM--a FORTRAN Program for Simulating Stochastic Acceleration Time Histories from Finite Faults

Beresnev, Igor A.; Atkinson, Gail M.

doi:10.1785/gssrl.69.1.27

Cited by 241 publications

(120 citation statements)

References 30 publications

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“…They agree well with empirical regression equations (e.g., Abrahamson and Silva, 1997;Sadigh et al, 1997) in the magnitude-distance ranges that are well represented by the strong-motion database. The stochastic ground motion relations are underpinned by a source model that has been validated for earthquakes from magnitudes 4 through 8 (e.g., Silva et al, 1990;Schneider et al, 1993;Silva and Darragh, 1995;Beresnev and Atkinson, 1997, 1998a, 1998b. The attenuation model is derived from regional seismographic data over distances of hundreds of km (Raoof et al, 1999).…”

Section: Discussionmentioning

confidence: 99%

“…The methodology has been described by Schneider et al (1993) and Atkinson (1997, 1998a). The computations are made with the FINSIM computer code (Beresnev and Atkinson, 1998a), and results are checked against those made with the finite-fault code of Silva (Silva et al, 1990;Silva and Stark, 1992;Schneider et al, 1993).…”

Section: Source Modelmentioning

confidence: 99%

“…The time history at an observation point is obtained by summing the contributions from all subfaults, appropriately lagged in time according to the rupture and propagation time for each of the subfaults. Heterogeneity of the source process is modeled by randomizing the subevent rise times and slip distribution, as described by Beresnev and Atkinson (1998a).…”

Section: Source Modelmentioning

confidence: 99%

“…The main "free" parameter of the modeling is the radiation strength factor s. The parameter s was introduced by Beresnev and Atkinson (1998a) to measure the strength of high-frequency radiation from faults. It may be related to the maximum slip velocity on the fault, and controls the level of the acceleration spectra above the corner frequency of the subfaults.…”

Section: Source Modelmentioning

confidence: 99%

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Stochastic Modeling of California Ground Motions

Atkinson¹

2000

Bulletin of the Seismological Society of America

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Ground-motion relations are developed for California using a stochastic simulation method that exploits the equivalence between finite-fault models and a two-corner point-source model of the earthquake spectrum. First, stochastic simulations are generated for finite-fault ruptures, in order to define the average shape and amplitude level of the radiated spectrum at near-source distances as a function of earthquake size. The length and width of the fault plane are defined based on the moment magnitude of the earthquake and modeled with an array of subfaults. The radiation from each subfault is modeled as a Brune point source using the stochastic model approach; the subfault spectrum has a single-corner frequency. An earthquake rupture initiates at a randomly chosen subfault (hypocenter), and propagates in all directions along the fault plane. A subfault is triggered when rupture propagation reaches its center. Simulations are generated for an observation point by summing the subfault time series, appropriately lagged in time. Fourier spectra are computed for records simulated at many azimuths, placed at equidistant observation points around the fault. The mean Fourier spectrum for each magnitude, at a reference nearsource distance, is used to define the shape and amplitude levels of an equivalent point-source spectrum that mimics the salient finite-fault effects. The functional form for the equivalent point-source spectrum contains two corner frequencies.Stochastic point-source simulations, using the derived two-corner source spectrum, are then performed to predict peak-ground-motion parameters and response spectra for a wide range of magnitudes and distances, for generic California sites. The stochastic ground-motion relations, given in the Appendix for rock and soil sites, are in good agreement with the empirical strong-motion database for California; the average ratio of observed to simulated amplitudes is near unity over all frequencies from 0.2 to 12 Hz. The stochastic relations agree well with empirical regression equations (e.g., Abrahamson and Silva, 1997;Sadigh et al., 1997) in the magnitude-distance ranges well represented by the data, but are better constrained at large distances, due to the use of attenuation parameters based on regional seismographic data. The stochastic ground-motion relations provide a sound basis for estimation of ground motions for earthquakes of magnitude 4 through 8, at distances from 1 to 200 km.

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Section: Discussionmentioning

confidence: 99%

Section: Source Modelmentioning

confidence: 99%

Section: Source Modelmentioning

confidence: 99%

Section: Source Modelmentioning

confidence: 99%

See 2 more Smart Citations

Stochastic Modeling of California Ground Motions

Atkinson¹

2000

Bulletin of the Seismological Society of America

Self Cite

379

288

View full text Add to dashboard Cite

show abstract

“…Strong ground motions were simulated using the FINSIM code of Beresnev and Atkinson (1998). This code implements the stochastic strong ground motion simulation technique for finite earthquake sources Atkinson, 1997, 1998), which is based on the pioneering work of Boore (1983).…”

Section: Methodsmentioning

confidence: 99%