NG21C-0709
Intermittent criticality in the long-range connective sandpile (LRCS) model
We here propose a long-range connective sandpile model with variable connection probability Pc, which has an
important impact on the slope of the power-law frequency-size distribution of avalanches. The long-range
connection probability Pc is changed according to an explicit function of the size of the latest event, although the
evolution rule of Pc may be different in various physical systems. Such version of the sandpile model
demonstrates large fluctuations in the dynamical variable
NG21C-0710
Long-range connective sandpile models and its implication to seismicity evolution
We propose a new variant of the sandpile model, the long-range connective sandpile model, by means of introducing randomly internal connections between two separated, distant cells. The long-range connective sandpile model demonstrates various self-organized critical states with different scaling exponents in the power- law frequency-size distributions. We found that a sandpile with higher degree of randomly internal long-range connections is characterized by a higher value of the scaling exponent for the distribution, whereas the nearest neighbor sandpile is possessed of a lower scaling exponent. Our numerical experiments on the long-range connective sandpile models imply that higher degree of random long-range connections makes the earthquake fault system more relaxant that releases accumulated energy more easily and produces fewer catastrophic events, whereas lower degree of long-range connections, possibly caused by fracture healing, very likely motivates accelerating seismicity of moderate events.
NG21C-0711
Seismicity patterns and phase transitions in the two-dimensional spring-block model of earthquakes
Earthquakes occur as a result of a fracture process and a frictional slip of a fault, and are categorized into nonlinear complex phenomena in a non-equilibrium open system. However, details of its physical mechanism remain open. On the contrary, many statistical properties of earthquakes have been known as empirical laws, for example, magnitude-frequency distribution called the Gutenberg-Richter (GR) law and the law of temporal decay of aftershocks (the Omori law). Furthermore, the spatio-temporal interval statistics have been studied recently. \par In the 1980s, Bak et al. proposed and emphasized the concept of self-organized criticality (SOC) in earthquake phenomena. Since then, many earthquake models based on the SOC have been proposed. The spring-block model proposed by Burridge and Knopoff is one of the useful model to discuss statistical properties of earthquakes. This model is modified to explain other statistical properties. \par In this presentation, we analyze statistical properties of earthquakes produced by the two-dimensional (2-D) spring-block model involving stick-slip behavior. The magnitude-frequency distribution, the inter-occurrence time statistics, and the hypocenter interval statistics are focused on. Comparing our results with seismicity in nature, we optimize the model parameters. We can show that the 2-D spring-block model can reproduce seismicity in nature in a restricted parameter regime. Additionally, the critical state of the system is presumed from the statistical properties of earthquakes. Then we construct phase diagrams to estimate a transition point. In the optimal case, the model exhibits the critical state. Therefore it is concluded that our results support the hypothesis that fault systems are in the state of self-organized criticality.