Simulation and properties of a non-homogeneous spring-block earthquake model with asperities

Muñoz-Diosdado, Alejandro; Rudolf-Navarro, Adolfo; Angulo‐Brown, F.

doi:10.2478/s11600-012-0027-7

Cited by 11 publications

(8 citation statements)

References 38 publications

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“…To simulate the homogeneous model α1 and α2 were chosen to be equal; for the non-homogeneous model [6], the lattice was partitioned in regions alternating values of α as shown in figure 2. In order to create a non-homogenous matrix, we decided to use two different α values in our simulations.…”

Section: Simulationsmentioning

confidence: 99%

“…In the homogeneous case, where the elastic constants have the same value, K1 = K2 = KL, meaning that α1 = α2 leading to a value of 0.2 as the best representative of real-life seismicity [5,6,7].…”

Section: Introductionmentioning

confidence: 99%

“…This way, we attempt to represent the idea of asperity from real faults. Asperities are basically regions with different conservation coefficients and elastic parameters [6].…”

Section: Introductionmentioning

confidence: 99%

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A non-homogenous model for the spring-block cellular automaton for earthquakes

Martínez

Oregon²,

Muñoz-Diosdado³

et al. 2022

J. Phys.: Conf. Ser.

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Many complex systems exhibit self-organizing criticality (SOC). In fact, there is a consensus that the Earth’s crust is a SOC system. The Olami, Feder and Christensen (OFC) spring-block model is a non-conservative SOC model that is used successfully to simulate the dynamics of seismic faults. In this model the system of coupled differential equations representing the spring-block model is mapped to a cellular automaton. In this work we include the idea of asperity, which is an important concept in real seismicity, by varying the distribution in the spring-block network. Considering that in real life seismicity faults are composed of different elements, it is necessary to have a model with these characteristics. We were able of reproduce the Gutenberg-Richter behavior (previously obtained in the classic OFC model) in this non-homogenous distribution.

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Section: Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A non-homogenous model for the spring-block cellular automaton for earthquakes

Martínez

Oregon²,

Muñoz-Diosdado³

et al. 2022

J. Phys.: Conf. Ser.

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“…The subsequent BK-type models were solved using cellular automata. These models have been solved in two-and three dimensions, and have been very successful in the qualitative reproduction of the GR law, as well as several other properties of real seismicity [24][25][29][30][31][32]. These results have strengthened the notion that earth's crust is a SOC-system.…”

Section: Analysis Using Synthetic Seismicity -The Ofc Modelmentioning

confidence: 99%

“…Olami et al also showed that the same behaviour was obtained in the isotropic and anisotropic cases. It has been reported that the OFC model has other interesting properties that seem to be related to real seismicity [24][25][29][30][31][32]. As such, it has been proposed that the OFC model can be used as a basic model for describing earthquake occurrence in a seismic fault, because it has many properties that correspond to properties observed in real seismicity.…”

Section: Analysis Using Synthetic Seismicity -The Ofc Modelmentioning

confidence: 99%

Detrended Fluctuation Analysis and Higuchi's Windowing Method Applied to an Analysis of Southern California Seismicity

Muñoz-Diosdado¹

2015

Earthquake Engineering - From Engineering Seismology to Optimal Seismic Design of Engineering Structures

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Recent studies have shown that many complex natural systems are characterized by correlations [7]; however, the identification and quantification of the presence of these long range correlations using spectral analysis is inadequate, because the data are non-stationary. However, the detrended fluctuation method DFA enables the detection of correlations in nonstationary time series, thereby avoiding spurious detections [8, 9]. Telesca et al. [10] described the scale behaviour of seismic sequences in Southern California from 1981 to 1998 (Figure 1), represented as a two-dimensional sequence of jumps and interevent intervals. They used the catalogue of Richards-Dinger and Shearer (RDS) [11], which in the years mentioned above lists 284925 events. The catalogue is complete from a magnitude of M ≥ 1.5, this means that no earthquake greater than 1.5 is missing (Figures 2 and 3). They discussed long-range entire catalogue properties using the DFA method and applying it to the time series of jumps and

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