Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Predicting failure in solids has broad applications including earthquake prediction which remains an unattainable goal. However, recent machine learning work shows that laboratory earthquakes can be predicted using micro-failure events and temporal evolution of fault zone elastic properties. Remarka...

Descripción completa

Detalles Bibliográficos
Autores principales: Borate, Prabhav, Rivière, Jacques, Marone, Chris, Mali, Ankur, Kifer, Daniel, Shokouhi, Parisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284922/
https://www.ncbi.nlm.nih.gov/pubmed/37344479
http://dx.doi.org/10.1038/s41467-023-39377-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284922/
https://www.ncbi.nlm.nih.gov/pubmed/37344479
http://dx.doi.org/10.1038/s41467-023-39377-6

Ejemplares similares