title: Finite-size effects on return interval distributions for weakest-link-scaling systems.
abstract: The Weibull distribution is a commonly used model for the strength of brittle materials and earthquake return intervals. Deviations from Weibull scaling, however, have been observed in earthquake return intervals and the fracture strength of quasibrittle materials. We investigate weakest-link scaling in finite-size systems and deviations of empirical return interval distributions from the Weibull distribution function. Our analysis employs the ansatz that the survival probability function of a system with complex interactions among its units can be expressed as the product of the survival probability functions for an ensemble of representative volume elements (RVEs). We show that if the system comprises a finite number of RVEs, it obeys the κ-Weibull distribution. The upper tail of the κ-Weibull distribution declines as a power law in contrast with Weibull scaling. The hazard rate function of the κ-Weibull distribution decreases linearly after a waiting time τ(c) ∝ n(1/m), where m is the Weibull modulus and n is the system size in terms of representative volume elements. We conduct statistical analysis of experimental data and simulations which show that the κ Weibull provides competitive fits to the return interval distributions of seismic data and of avalanches in a fiber bundle model. In conclusion, using theoretical and statistical analysis of real and simulated data, we demonstrate that the κ-Weibull distribution is a useful model for extreme-event return intervals in finite-size systems.
authors.affiliation: Department of Mineral Resources Engineering, Technical University of Crete, Chania 73100, Greece.
authors.forename: Dionissios T
authors.initials: DT
authors.lastname: Hristopulos
authors.affiliation: Department of Mineral Resources Engineering, Technical University of Crete, Chania 73100, Greece.
authors.forename: Manolis P
authors.initials: MP
authors.lastname: Petrakis
authors.affiliation: Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.
authors.forename: Giorgio
authors.initials: G
authors.lastname: Kaniadakis
mesh_terms: D003198:Computer Simulation; D008954:Models, Biological; D015233:Models, Statistical; D018401:Sample Size; D016008:Statistical Distributions; D013997:Time Factors