Record-breaking earthquake intervals in a global catalogue and an aftershock sequence

Yoder, Mark R.; Turcotte, Donald L.; Rundle, John B.

doi:10.5194/npg-17-169-2010

Cited by 18 publications

(19 citation statements)

References 19 publications

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“…This idea was extended to earthquakes by Ref. [16] where the sequence of interval times between successive earthquakes were analyzed. It was shown that for global earthquakes the statistics of both record-breaking longer and record-breaking shorter intervals is consistent with IID processes.…”

Section: Discussionmentioning

confidence: 99%

“…At the same time the ratio r of the number of record-breaking longer and shorter intervals proved to be predominantly greater than one, which was suggested as a measure to distinguish between background seismicity and aftershock sequences [16]. Extending the calculation of the ratio r to a broader spatiotemporal interval, before and after the main shock, r < 1 and r > 1 were found, respectively, which addressed a possibility of using record-breaking statistics for forecasting [16]. For interevent times of aftershocks the Omori-type relaxation was proved to be responsible for the power-law increase of the number of records, while in our case the monotonically increasing average event size towards failure plays a similar role.…”

Section: Discussionmentioning

confidence: 99%

“…Records are noise that have a size greater than any previous events of the series. Recently, the record statistics of stochastic time series has attracted great attention due to its relevance for climate and earthquake research [13][14][15][16]. Interesting analytic results have been obtained for the RB statistics of the sequences of independent identically distributed (IID) random variables for a randomly sampled stationary process [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…The record statistics of crackling noise have also been studied recently in models exhibiting self organized criticality (SOC) [18] and in a mean-field model of fracture [25]. For earthquakes record statistics were recently applied to reveal spatiotemporal clustering of seismicity either by focusing on the interevent times [16] or using both the spatial and temporal distance of events [14,15]. In our realistic discrete element model of compressive failure we analyze both the aggregated statistics of records and the evolution of record breaking as the sample approaches macroscopic failure.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the record statistics of stochastic time series has attracted great attention due to its relevance for climate and earthquake research [13][14][15][16]. Interesting analytic results have been obtained for the RB statistics of the sequences of independent identically distributed (IID) random variables for a randomly sampled stationary process [16][17][18]. In physics the statistics of records has been applied to understand correlated processes emerging in various types of random walks [19][20][21], superconductors [22], domain wall dynamics in spin glasses [23], and in chaotic processes [24].…”

Section: Introductionmentioning

confidence: 99%

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Record-breaking events during the compressive failure of porous materials

et al. 2016

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An accurate understanding of the interplay between random and deterministic processes in generating extreme events is of critical importance in many fields, from forecasting extreme meteorological events to the catastrophic failure of materials and in the Earth. Here we investigate the statistics of record-breaking events in the time series of crackling noise generated by local rupture events during the compressive failure of porous materials. The events are generated by computer simulations of the uniaxial compression of cylindrical samples in a discrete element model of sedimentary rocks that closely resemble those of real experiments. The number of records grows initially as a decelerating power law of the number of events, followed by an acceleration immediately prior to failure. The distribution of the size and lifetime of records are power laws with relatively low exponents. We demonstrate the existence of a characteristic record rank k * , which separates the two regimes of the time evolution. Up to this rank deceleration occurs due to the effect of random disorder. Record breaking then accelerates towards macroscopic failure, when physical interactions leading to spatial and temporal correlations dominate the location and timing of local ruptures. The size distribution of records of different ranks has a universal form independent of the record rank. Subsequences of events that occur between consecutive records are characterized by a power-law size distribution, with an exponent which decreases as failure is approached. High-rank records are preceded by smaller events of increasing size and waiting time between consecutive events and they are followed by a relaxation process. As a reference, surrogate time series are generated by reshuffling the event times. The record statistics of the uncorrelated surrogates agrees very well with the corresponding predictions of independent identically distributed random variables, which confirms that temporal and spatial correlation in the crackling noise is responsible for the observed unique behavior. In principle the results could be used to improve forecasting of catastrophic failure events, if they can be observed reliably in real time.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%