Complexity of Fracturing in Terms of Non-Extensive Statistical Physics: From Earthquake Faults to Arctic Sea Ice Fracturing

Vallianatos, Filippos; Michas, Georgios

doi:10.3390/e22111194

Cited by 15 publications

(5 citation statements)

References 76 publications

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“…Such weak interaction systems do not have a Boltzmann distribution, but rather a power‐law distribution with heavy tails, enhanced by (multi) fractal geometry, long‐range interactions, and intermittence or large fluctuations between various possible states. These systems correspond precisely to seismic phenomena (Sardeli et al, 2023; Sigalotti et al, 2023; Vallianatos et al, 2016). For such systems, Tsallis (1988) established nonextensive statistical mechanics and generalized Boltzmann–Gibbs statistical mechanics.…”

Section: Dynamic Models For Earthquake Triggermentioning

confidence: 62%

Dynamically triggered seismicity on a tectonic scale: A review

Qi,

Wang,

Kocharyan

et al. 2023

Deep Underground Science and Engineering

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Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments. In the past several decades, earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering, earthquake prediction, and the desire to use the mechanism of earthquake triggering to reduce, prevent, or trigger earthquakes. Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes. In the past several decades, some models have been developed, including static, dynamic, quasi‐static, and other models. Some reviews have been published, but explosion‐triggered seismicity was not included. In recent years, some new results on earthquake triggering have emerged. Therefore, this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area. Instead of a complete review of the relevant literature, this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.

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Section: Dynamic Models For Earthquake Triggermentioning

confidence: 62%

Dynamically triggered seismicity on a tectonic scale: A review

Qi,

Wang,

Kocharyan

et al. 2023

Deep Underground Science and Engineering

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“…In addition, the q -values of q T > 1 and q D < 1 are in agreement with the q -values found for aftershock sequences [ 38 , 40 , 83 , 93 , 94 ], for the Hellenic Subduction Zone [ 91 ], for the temporal properties of seismicity [ 60 , 61 ] and for global seismicity [ 41 , 84 ]. In addition, the concept of NESP describes well both the spatial and temporal behavior of the earthquake swarms in diverse tectonic environments [ 7 , 18 , 26 , 95 ] and in volcanic regions [ 23 , 59 ]. Moreover, the value of q T > 1 suggests a sub-additive process, leading to the conclusion of long-range memory in the evolution of earthquake swarms for T < T c .…”

Section: Discussionmentioning

confidence: 99%

Complexity of Recent Earthquake Swarms in Greece in Terms of Non-Extensive Statistical Physics

Sardeli

Michas

Pavlou

et al. 2023

Entropy

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Greece exhibits the highest seismic activity in Europe, manifested in intense seismicity with large magnitude events and frequent earthquake swarms. In the present work, we analyzed the spatiotemporal properties of recent earthquake swarms that occurred in the broader area of Greece using the Non-Extensive Statistical Physics (NESP) framework, which appears suitable for studying complex systems. The behavior of complex systems, where multifractality and strong correlations among the elements of the system exist, as in tectonic and volcanic environments, can adequately be described by Tsallis entropy (Sq), introducing the Q-exponential function and the entropic parameter q that expresses the degree of non-additivity of the system. Herein, we focus the analysis on the 2007 Trichonis Lake, the 2016 Western Crete, the 2021–2022 Nisyros, the 2021–2022 Thiva and the 2022 Pagasetic Gulf earthquake swarms. Using the seismicity catalogs for each swarm, we investigate the inter-event time (T) and distance (D) distributions with the Q-exponential function, providing the qT and qD entropic parameters. The results show that qT varies from 1.44 to 1.58, whereas qD ranges from 0.46 to 0.75 for the inter-event time and distance distributions, respectively. Furthermore, we describe the frequency–magnitude distributions with the Gutenberg–Richter scaling relation and the fragment–asperity model of earthquake interactions derived within the NESP framework. The results of the analysis indicate that the statistical properties of earthquake swarms can be successfully reproduced by means of NESP and confirm the complexity and non-additivity of the spatiotemporal evolution of seismicity. Finally, the superstatistics approach, which is closely connected to NESP and is based on a superposition of ordinary local equilibrium statistical mechanics, is further used to discuss the temporal patterns of the earthquake evolution during the swarms.

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“…We can also identify, as a result of this work, some significant directions on which research can be continued. Among them, here we mention: dual determination of scaledependent deformation functions representing the intermittency characteristics of a given signal; consideration of stochastic deformation (in particular, from covariate effects); sensitivity with respect to the deformation parameter q in generalized entropy measures (Rényi, Tsallis), and its potential usefulness for detecting intermittency levels from the inter/intrascale distribution of energy; extension and interpretation of results in terms of diversity and considering alternative complexity measures; intermittency analysis of spatial or spatiotemporal signals; risk analysis, e.g., using quantile-based risk measures (see, for example, [33]), on loss functions defined in terms of intermittency indicators, with projection, for instance, to identification of recurrence, persistency or clustering patterns; derivations under the perspective of multifractal analysis (see, for example, [34][35][36]).…”

Section: Discussionmentioning

confidence: 99%

Wavelet-Based Multiscale Intermittency Analysis: The Effect of Deformation

Angulo

Madrid

2023

Entropy

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Intermittency represents a certain form of heterogeneous behavior that has interest in diverse fields of application, particularly regarding the characterization of system dynamics and for risk assessment. Given its intrinsic location-scale-dependent nature, wavelets constitute a useful functional tool for technical analysis of intermittency. Deformation of the support may induce complex structural changes in a signal. In this paper, we study the effect of deformation on intermittency. Specifically, we analyze the interscale transfer of energy and its implications on different wavelet-based intermittency indicators, depending on whether the signal corresponds to a ‘level’- or a ‘flow’-type physical magnitude. Further, we evaluate the effect of deformation on the interscale distribution of energy in terms of generalized entropy and complexity measures. For illustration, various contrasting scenarios are considered based on simulation, as well as two segments corresponding to different regimes in a real seismic series before and after a significant earthquake.

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Complexity of Fracturing in Terms of Non-Extensive Statistical Physics: From Earthquake Faults to Arctic Sea Ice Fracturing

Cited by 15 publications

References 76 publications

Dynamically triggered seismicity on a tectonic scale: A review

Dynamically triggered seismicity on a tectonic scale: A review

Complexity of Recent Earthquake Swarms in Greece in Terms of Non-Extensive Statistical Physics

Wavelet-Based Multiscale Intermittency Analysis: The Effect of Deformation

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