Particle image correlation data from Foamquake: a novel seismotectonic analog model mimicking the megathrust seismic cycle

Mastella, Giacomo; Corbi, Fabio; Funiciello, Francesca ; Matthias, Rosenau;

2022-02 || GFZ Data Services

This dataset includes particle image correlation data from 26 experiments performed with Foamquake, a novel analog seismotectonic model reproducing the megathrust seismic cycle. The seismotectonic model has been monitored by the means of a high-resolution top-view monitoring camera. The dataset presented here represents the particle image velocimetry surface velocity field extracted during the experimental model through the cross-correlation between consecutive images. This dataset is supplementary to Mastella et al. (2021) where detailed descriptions of models and experimental results can be found.

Originally assigned keywords

Corresponding MSL vocabulary keywords

MSL enriched keywords

MSL enriched sub domains
  • analogue modelling of geologic processes
Source http://doi.org/10.5880/fidgeo.2021.046
Source publisher GFZ Data Services
DOI 10.5880/fidgeo.2021.046
License CC BY 4.0
Authors
  • Corbi, Fabio
  • 0000-0003-2662-3065
  • Istituto di Geologia Ambientale e Geoingegneria – CNR, Rome, Italy
  • Matthias, Rosenau
  • 0000-0003-1134-5381
  • GFZ German Research Centre for Geosciences, Potsdam, Germany
References
  • Corbi, F., Sandri, L., Bedford, J., Funiciello, F., Brizzi, S., Rosenau, M., & Lallemand, S. (2019). Machine Learning Can Predict the Timing and Size of Analog Earthquakes. Geophysical Research Letters, 46(3), 1303–1311. Portico. https://doi.org/10.1029/2018gl081251
  • 10.1029/2018GL081251
  • Cites
  • Corbi, F., Bedford, J., Sandri, L., Funiciello, F., Gualandi, A., & Rosenau, M. (2020). Predicting Imminence of Analog Megathrust Earthquakes With Machine Learning: Implications for Monitoring Subduction Zones. Geophysical Research Letters, 47(7). Portico. https://doi.org/10.1029/2019gl086615
  • 10.1029/2019GL086615
  • Cites
  • Kosari, E., Rosenau, M., Bedford, J., Rudolf, M., & Oncken, O. (2020). On the Relationship Between Offshore Geodetic Coverage and Slip Model Uncertainty: Analog Megathrust Earthquake Case Studies. Geophysical Research Letters, 47(15). Portico. https://doi.org/10.1029/2020gl088266
  • 10.1029/2020GL088266
  • Cites
  • Rosenau, M., Horenko, I., Corbi, F., Rudolf, M., Kornhuber, R., & Oncken, O. (2019). Synchronization of Great Subduction Megathrust Earthquakes: Insights From Scale Model Analysis. Journal of Geophysical Research: Solid Earth, 124(4), 3646–3661. Portico. https://doi.org/10.1029/2018jb016597
  • 10.1029/2018JB016597
  • Cites
  • Cites
  • Mastella, G., Corbi, F., Funiciello, F., Rosenau, M., Rudolf, M., & Kosari, E. (2021). Properties of rock analogue materials used for Foamquake: a novel seismotectonic analog model mimicking the megathrust seismic cycle at RomaTre University (Italy) [Data set]. GFZ Data Services. https://doi.org/10.5880/FIDGEO.2021.047
  • 10.5880/fidgeo.2021.047
  • HasPart
Contact
  • Mastella Giacomo
  • Universitá degli studi "Roma TRE", Rome, Italy
  • giacomo.mastella@uniroma3.it
Citation Mastella, G., Corbi, F., Funiciello, F., & Matthias, R. (2021). Particle image correlation data from Foamquake: a novel seismotectonic analog model mimicking the megathrust seismic cycle [Data set]. GFZ Data Services. https://doi.org/10.5880/FIDGEO.2021.046