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Accelerating Precursory Activity in Statistical Fractal Automata Dion Weatherley and Peter Mora QUAKES, Univ. of Qld., Australia.

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Presentation on theme: "Accelerating Precursory Activity in Statistical Fractal Automata Dion Weatherley and Peter Mora QUAKES, Univ. of Qld., Australia."— Presentation transcript:

1 Accelerating Precursory Activity in Statistical Fractal Automata Dion Weatherley and Peter Mora QUAKES, Univ. of Qld., Australia.

2 Outline Model Description Results from a parameter space study Event size scaling Evolution of mean stress Stress field evolution Accelerating precursory activity Summary of results Effect of varying the fractal dimension Conclusions and questions

3 Model Description Uniform rectangular grid of cells Each cell has two properties Constant, scalar Strength Variable, scale Stress Uniform loading of all cells Cell failure when a cell’s stress exceeds its strength Nearest Neighbour stress redistribution Periodic boundary conditions

4 Event size scaling

5 Mean Stress Evolution models with a char. event distribution (A) relatively low time-averaged mean stress large, saw-tooth fluctuations models with a roll-over distribution (D) high time-averaged mean stress small, irregular fluctuations models with high dissipation (C) near-constant mean stress models with GR-scaling (D) correspond with drop in time-averaged mean stress mark a transition from large to small fluctuations

6 Snapshots of Stress Evolution

7 Accelerating Precursory Activity 1.Select the 100 largest events in each simulation for analysis. 2.Define Tf as the time of the large event. 3.Vary To and m within a range. 4.Compute A,B via least squares fit. 5.Compare power-law with a linear fit. 6.Select best power-law fit for each event. 7.Count number of good power-law fits for each simulation = fit probability.

8 Summary of Results Accelerating Precursory Activity in models with: overabundance of larger events relatively low time-averaged mean stress large, saw-tooth fluctuations in mean stress relatively smooth stress field over broad regions Constant rate of activity in models with: an under-abundance of large events high, near-constant mean stress stress field dominated by small-scale heterogeneity Evidence for a distinct transition between two modes of activity GR-scaling only for simulations along a line through parameter space change in character of mean stress fluctuations across this line change in stress field heterogeneity across this line probability of accelerating precursory activity drops to near-zero at this line

9 Effect of varying the Fractal Dimension of cell Strengths D=1.875 D=2.250 D=2.625

10 Conclusions and some Questions Accelerating Precursory Activity occurs in models in which : there is an overabundance of larger events these large events perturb the system from a state of high stress stress redistribution smoothes the stress field within failed region long-range clustering of cell strengths (smaller fractal dimension) Stress field heterogeneity apparently a factor determining the mode of activity relatively smooth stress field corresponds with accelerating activity a stress field dominated by small-scale heterogeneity corresponds with a constant rate of activity Some questions to motivate discussions Is the transition line a SPINODAL i.e. a line of Critical Points? How might one formulate a mathematical description for these models? Are these models any more or less appropriate as earthquake analogues than pseudo-spinodal or SOC models?


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