Experiment p5271 and Data from Shreedharan et al., JGR 2021

This is an experiment with 5x5cm Westerly granite blocks that were dusted with a fine layer (<200 micron thickness and about 0.25 g/layer by mass) of quartz powder (min-u-sil40) to simulate frictional wear material (also see Shreedharan et al., 2020). The granite surfaces were roughened with #60 grit silicon carbide thus producing a root-mean- squared roughness of about 2 micron. The surface roughness and the quartz powder (median particle size of 10.5 micron) are comparable Shreedharan, S., Bolton, D. C., Riviere, J., & Marone, C. (2020). Preseismic fault creep and elastic wave amplitude precursors scale with lab earthquake magnitude for the continuum of tectonic failure modes. Geophysical Research Letters, 46. https://doi.org/10.1029/2020GL086986

RunSheets5268_to_p5272.pdf Run Sheets for Experiments p5268 to p5272


Data are available at the link below

p5268 to p5272 Dataset for Shreedharan et al. - Machine Learning Predicts the Timing and Shear Stress Evolution of Lab Earthquakes Using Active Seismic Monitoring of Fault Zone Processes

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Data from this experiment are report in this paper: Shreedharan, S., Bolton, D. C., Riviere, J., & Marone, C. (2021). Machine learning predicts the timing and shear stress evolution of lab earthquakes using active seismic monitoring of fault zone processes. Journal of Geophysical Research: Solid Earth, 126, e2020JB021588. https://doi. org/10.1029/2020JB021588