Mapping heterogeneities through avalanche statistics

Biswas, Soumyajyoti; Goehring, Lucas

doi:10.1098/rsta.2017.0388

Cited by 4 publications

(3 citation statements)

References 36 publications

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“…Here we use a model of the power grid similar to that studied in refs. [47][48][49][50] where we assume a wide Fig. 2: Day-night variations in outage size distributions can be seen regionally.…”

Section: (A)mentioning

confidence: 99%

Load dependence of power outage statistics

Biswas

Goehring

2019

EPL

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The size distributions of power outages are shown to depend on the stress, or the proximity of the load of an electrical grid to complete breakdown. Using the data for the U.S. between 2002-2017, we show that the outage statistics are dependent on the usage levels during different hours of the day and months of the year. At higher load, not only are more failures likely, but the distribution of failure sizes shifts, to favor larger events. At a finer spatial scale, different regions within the U.S. can be shown to respond differently in terms of the outage statistics to variations in the usage (load). The response, in turn, corresponds to the respective bias towards larger or smaller failures in those regions. We provide a simple model, using realistic grid topologies, which can nonetheless demonstrate biases as a function of the applied load, as in the data. Given sufficient data of small scale events, the method can be used to identify vulnerable regions in power grids prior to major blackouts.

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Section: (A)mentioning

confidence: 99%

Load dependence of power outage statistics

Biswas

Goehring

2019

EPL

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“…In a similar forecasting problem to that described above, our final paper deals with a different method for such forecasting, viz. the change in the b-value of the Gutenberg-Richter-like law with the local stress on the system [39]. The question here is to find the optimal time and length scale over which activity data are necessary to unambiguously determine a weak region in the system.…”

Section: Discussionmentioning

confidence: 99%

Statistical physics of fracture and earthquakes

Biswas

Goehring

Chakrabarti

2018

Phil. Trans. R. Soc. A.

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Manifestations of emergent properties in stressed disordered materials are often the result of an interplay between strong perturbations in the stress field around defects. The collective response of a long-ranged correlated multi-component system is an ideal playing field for statistical physics. Hence, many aspects of such collective responses in widely spread length and energy scales can be addressed by the tools of statistical physics. In this theme issue, some of these aspects are treated from various angles of experiments, simulations and analytical methods, and connected together by their common base of complex-system dynamics. This article is part of the theme issue ‘Statistical physics of fracture and earthquakes’ .

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“…[31] However, foreshocks, aftershocks, and clustering properties indicate the existence of correlation between different events. [32][33][34][35][36] Many seismologists believe that large earthquakes are quasi-periodic, [37][38][39][40] but periodic behavior has appeared in theoretical models only as a special or as a trivial solution, [41][42][43] or as a result of a phase locking due to periodic boundary conditions (BCs), [44][45][46] or synchronized regions [47] in cellular automata.…”

Section: Introductionmentioning

confidence: 99%

Quasi-periodic events on structured earthquake models*

Wang

2019

Chinese Phys. B

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There has been much interest in studying quasi-periodic events on earthquake models. Here we investigate quasi-periodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform. For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system. Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena. Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system, there is evidence that it depends on the time series of the average force of the system.

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Mapping heterogeneities through avalanche statistics

Cited by 4 publications

References 36 publications

Load dependence of power outage statistics

Load dependence of power outage statistics

Statistical physics of fracture and earthquakes

Quasi-periodic events on structured earthquake models*

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