3 papers
physics.geo-ph2026
PINN-based short-term forecasting of fault slip evolution during the 2010 slow slip event in the Bungo Channel, Japan
Masayuki Kano, Rikuto Fukushima
Monitoring and forecasting fault slip evolution are fundamental for understanding earthquake cycles and assessing future seismic hazards. This study proposes a physics-based data a…
physics.geo-ph2026
Physics-informed deep learning links geodetic data and fault friction
Rikuto Fukushima, Masayuki Kano, Kazuro Hirahara +1
Fault slip modeling, based on laboratory-derived friction laws, has significantly enhanced our understanding of fault mechanics. Agreement between model predictions and observation…
physics.geo-ph2025
Three-dimensional crustal deformation analysis using physics-informed deep learning
Tomohisa Okazaki, Takeo Ito, Kazuro Hirahara +3
Earthquake-related phenomena such as seismic waves and crustal deformation impact broad regions, requiring large-scale modeling with careful treatment of artificial outer boundarie…