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EN
We apply a stochastic model to study Benioff strain release after the Mw6.9 October 18, 1989 Loma Prieta strong earthquake in north California, USA. The model is developed, following a compound Poisson process and contours the evolution of strain release during the aftershock sequence following the main shock occurrence. First, the temporal evolution of the aftershock decay rate was modeled by the Restricted Epidemic Type Aftershock Sequence (RETAS) model and after that the recognized best fit model is integrated into the strain release stochastic analysis. The applied stochastic model of Benioff strain release empowers a more detailed study by detecting possible deviations between observed data and model. Real values of the cumulative Benioff strain release surpass the expected modeled ones, indicating, that large aftershocks cluster at the beginning of the Loma Prieta sequence immediately after the occurrence of the main shock. Strain release spatial analysis reveals release patterns, which change during the aftershock sequence.
2
Content available remote Testing fractal coefficients sensitivity on real and simulated earthquake data
EN
We examined the behavior of different fractal dimensions when applied to study features of earthquake spatial distribution on different types of data. We first examined simulated spatial fields of points of different clustering level, following the so called Soneira-Peebles model. The model was chosen because it displays some similarity to the real clustering structure of earthquakes occurring on hierarchically ordered faults. The analysis of the capacity, clustering and correlation dimensions revealed that their behavior did not completely correlate with the clustering level of the simulated data sets. We also studied temporal variations of the fractal coefficients, characterizing the spatial distribution of the 1999 Izmit-Düzce aftershock sequence. The calculated coefficient values demonstrated analogous behavior like for the simulated data. They exposed different variability in time, but for all of them a systematic fluctuation was observed before the occurrence of the Düzce earthquake. Our analysis revealed that although fractal coefficients could be applied to measure earthquake clustering, they should be used with caution, trying to figure out the best coefficient for a certain data set.
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