Computational Seismology and Physics-Informed AI : Foundations of Rupture Mechanics and Tectonic State Evolution - Computational Seismology and Physics-Informed AI, #1

Computational Seismology and Physics-Informed AI

Volume I: Foundations of Rupture Mechanics and Tectonic State Evolution

Earthquakes do not begin when the ground shakes.

They begin years, decades, and sometimes centuries earlier through a hidden evolution of stress, friction, damage accumulation, and fault interaction deep within the Earth's crust. The devastating rupture observed in seconds is merely the final act of a much longer and largely invisible process.

Volume I: Foundations of Rupture Mechanics and Tectonic State Evolution takes readers inside that process.

Combining modern seismology, rock mechanics, fracture physics, elastodynamics, geophysical sensing, and computational modeling, this volume builds the physical foundation required to understand how tectonic systems store energy, evolve toward instability, and ultimately fail.

Through intuitive explanations, rigorous derivations, real-world case studies, and computational perspectives, readers will explore:

✓ Stress, strain, and fault mechanics

✓ Mohr-Coulomb failure and rock fracture physics

✓ Fractal asperities and fault surface roughness

✓ Slow Slip Events (SSEs) and Episodic Tremor and Slip (ETS)

✓ Rupture kinematics and dimensionless scaling laws

✓ Seismic wave propagation and elastodynamics

✓ Distributed Acoustic Sensing (DAS)

✓ Acoustic emission signatures of micro-cracking

✓ Full-Waveform Inversion (FWI)

✓ Attenuation physics and Q-factor analysis

More than a traditional seismology textbook, this volume introduces a systems-level perspective in which faults are viewed as evolving physical systems possessing memory, feedback, and measurable precursors. Readers are guided from first-principles mechanics to the emerging concept of Phase Kinetic Coherence (PKC), a framework that seeks to unify physical state evolution, sensing, and computational intelligence.

Designed for graduate students, researchers, engineers, geoscientists, data scientists, and professionals working at the intersection of Earth science and computation, this book provides the essential foundation for the advanced fault dynamics, Physics-Informed Neural Networks (PINNs), and forecasting architectures developed in Volumes II and III.

The future of earthquake science begins with understanding how failure evolves.

This volume is the first step.