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      A Statistical Fractal-Diffusive Avalanche Model of a Slowly-Driven Self-Organized Criticality System

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          Abstract

          We develop a statistical analytical model that predicts the occurrence frequency distributions and parameter correlations of avalanches in nonlinear dissipative systems in the state of a slowly-driven self-organized criticality (SOC) system. This model, called the fractal-diffusive SOC model, is based on the following four assumptions: (i) The avalanche size \(L\) grows as a diffusive random walk with time \(T\), following \(L \propto T^{1/2}\); (ii) The instantaneous energy dissipation rate \(f(t)\) occupies a fractal volume with dimension \(D_S\), which predicts the relationships \(F = f(t=T) \propto L^{D_S} \propto T^{D_S/2}\), \(P \propto L^{S} \propto T^{S/2}\) for the peak energy dissipation rate, and \(E \propto F T \propto T^{1+D_S/2}\) for the total dissipated energy; (iii) The mean fractal dimension of avalanches in Euclidean space \(S=1,2,3\) is \(D_S \approx (1+S)/2\); and (iv) The occurrence frequency distributions \(N(x) \propto x^{-\alpha_x}\) based on spatially uniform probabilities in a SOC system are given by \(N(L) \propto L^{-S}\), which predicts powerlaw distributions for all parameters, with the slopes \(\alpha_T=(1+S)/2\), \(\alpha_F=1+(S-1)/D_S\), \(\alpha_P=2-1/S\), and \(\alpha_E=1+(S-1)/(D_S+2)\). We test the predicted fractal dimensions, occurrence frequency distributions, and correlations with numerical simulations of cellular automaton models in three dimensions \(S=1,2,3\) and find satisfactory agreement within \(\approx 10%\). One profound prediction of this universal SOC model is that the energy distribution has a powerlaw slope in the range of \(\alpha_E=1.40-1.67\), and the peak energy distribution has a slope of \(\alpha_P=1.67\) (for any fractal dimension \(D_S=1,...,3\) in Euclidean space S=3), and thus predicts that the bulk energy is always contained in the largest events, which rules out significant nanoflare heating in the case of solar flares.

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          Spatio-Temporal Scaling of Solar Surface Flows

          The Sun provides an excellent natural laboratory for nonlinear phenomena. We use motions of magnetic bright points on the solar surface, at the smallest scales yet observed, to study the small scale dynamics of the photospheric plasma. The paths of the bright points are analyzed within a continuous time random walk framework. Their spatial and temporal scaling suggest that the observed motions are the walks of imperfectly correlated tracers on a turbulent fluid flow in the lanes between granular convection cells.
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            Author and article information

            Journal
            10.1051/0004-6361/201118237
            1112.4859

            Solar & Stellar astrophysics
            Solar & Stellar astrophysics

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