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Hierarchical model for distributed seismicity.

Alejandro Tejedor1, Javier B Gómez, Amalio F Pacheco

  • 1Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain. atejedor@unizar.es

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Summary
This summary is machine-generated.

This study introduces a fractal cellular automata model for seismic fault interactions. The model simulates earthquakes and their magnitude relationships, offering insights into seismicity patterns and precursory signals.

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Area of Science:

  • Geophysics
  • Complex Systems
  • Computational Seismology

Background:

  • Understanding seismic fault interactions is crucial for earthquake prediction.
  • Existing models often struggle to capture the hierarchical nature of fault systems.

Purpose of the Study:

  • To present a novel cellular automata model for simulating seismic fault interactions.
  • To investigate the hierarchical dynamics of fault systems and earthquake magnitudes.
  • To evaluate the model's ability to reproduce seismicity patterns and test precursory signals.

Main Methods:

  • Developed a cellular automata model using a fractal tree structure to represent faults.
  • Simulated tectonic forces by adding load particles to fault sites.
  • Modeled fault 'toppling' (earthquakes) upon reaching capacity, with particle redistribution.

Main Results:

  • The model successfully reproduces earthquake magnitude distributions consistent with empirical laws.
  • Demonstrated hierarchical particle redistribution between faults of different sizes.
  • Showcased the model's scalability to millions of faults and its utility in testing precursory patterns.

Conclusions:

  • The fractal cellular automata model provides a robust framework for studying seismic fault interactions.
  • The model's geometric parameters offer a new perspective on earthquake dynamics.
  • This approach holds potential for advancing earthquake forecasting and understanding seismicity.