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Projekt Druckansicht

Bayessche Inferenz von Erdbebenquellparametern: kinematische und dynamische Störungszonenmodelle

Antragstellerin Dr. Alice-Agnes Gabriel
Fachliche Zuordnung Physik des Erdkörpers
Förderung Förderung von 2018 bis 2022
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 391058966
 
Erstellungsjahr 2024

Zusammenfassung der Projektergebnisse

Key outcomes of our collaborative efforts include the development of innovative Bayesian frameworks for earthquake source inversion, integration of advanced high-performance computing (HPC) techniques, and large-scale 3D dynamic rupture simulations. The project enhanced the earthquake simulation software SeisSol to incorporate dynamic modeling constraints and support reproducible, data-driven seismic hazard assessment. Novel applications included physics-based simulations of large earthquakes such as the 2016 Mw 7.8 Kaikōura and 2019 Ridgecrest events, yielding insights into fault dynamics and ground motion characteristics critical for seismic risk mitigation. The project led to a total of 30 peer-reviewed publications, including publications in Nature, Geophysical Research Letters and Nature Communications. Despite challenges from the COVID-19 pandemic, the project successfully fostered the training of young scientists, with outcomes such as PhD graduations and technical contributions to open-source software. Through this work, BAIES has set a foundation for future explorations of earthquake dynamics and advanced HPC applications in seismology, with broader implications for both scientific understanding and societal resilience to seismic hazards.

Projektbezogene Publikationen (Auswahl)

 
 

Zusatzinformationen

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