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Dataset

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

Cite as:

Mastella, Giacomo; Corbi, Fabio; Funiciello, Francesca; Matthias, Rosenau (2021): Particle image correlation data from Foamquake: a novel seismotectonic analog model mimicking the megathrust seismic cycle. GFZ Data Services. https://doi.org/10.5880/fidgeo.2021.046

Status

I   N       R   E   V   I   E   W : Mastella, Giacomo; Corbi, Fabio; Funiciello, Francesca; Matthias, Rosenau (2021): Particle image correlation data from Foamquake: a novel seismotectonic analog model mimicking the megathrust seismic cycle. GFZ Data Services. https://doi.org/10.5880/fidgeo.2021.046

Abstract

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.

Methods

Foamquake is a scaled seismotectonic model that reproduces the key features of a generic natural megathrust. The experimental setup is composed of a Plexiglass box where a flat-topped elastic foam rubber wedge with a dimension of 145x90x20 cm^3 (the overriding plate analog) overlaying a planar, 10° dipping rigid plate (the subducting plate analog). The model is free to move laterally for 5 cm within the Plexiglass box. Thus, it is not affected by friction acting at the two sides of the foam wedge. Instead, the rear (i.e., the thickest side) of the vertical wedge is confined by a rigid vertical backstop. The interface between the foam and the lower plate mimics the megathrust interface. Along the rigid subducting plate, a plastic conveyor belt moves downward at the constant velocity of 0.01 cm/s reproducing a steady trench-orthogonal subduction. Along the plate interface a 1 cm layer of granular material (i.e., rice) mimics a seismic asperity surrounded by sand reproducing the heterogeneous frictional configuration of the analog fault zone. Due to the physical properties of granular materials placed along the analog megathrust, Foamquake experiences stick-slip behavior. This behavior, can be described in the rate and state framework, results in the quasi-periodic spontaneous nucleation of frictional instabilities within the rice layer, named foamquakes. The rice is characterized by a velocity weakening frictional behavior while the sand is characterized by velocity neutral behavior. As a consequence, analog earthquakes nucleate within the granular seismic asperity, while the sand tends to inhibit the rupture propagation. Given the 3D nature of the setup, models with more than one asperity can be performed with Foamquake.
This dataset includes data from 22 models with a single-asperity configuration. Those models differ from each other by a variation of the normal load applied above the asperity and of the along trench asperity length. This repository also includes data derived from 4 models characterized by the presence of two asperities divided by a barrier.

Authors

Contact

Contributors

Laboratory of Experimental Tectonics (University of Roma TRE, Italy); Mastella Giacomo

Keywords

subduction megathrust earthquakes, asperities, multi-scale laboratories, EPOS, Analog modelling results, deformation, geologic process, tectonic process, subduction, Particle Image Velocimetry (PIV), analogue models of geological processes, MatPIV, Earthquake simulator, earthquake, seismic activity, geological process, thrust fault, subduction zones, plate margin setting, Wedge simulator, geological process > seismic activity > earthquake, lithosphere > earth's crust > fault

GCMD Science Keywords

Files

License: CC BY 4.0

Dataset Description

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