API src

Found 5 results.

Other language confidence: 0.6848629088447109

Particle image velocimetry data from an analog seismo-tectonic model addressing the interaction between neighbor asperities

This dataset includes the results of Particle Image Velocimetry (PIV) of one experiment on subduction megathrust earthquakes (with interacting asperities) performed at the Laboratory of Experimental Tectonics (LET) Univ. Roma Tre in the framework of AspSync, the Marie Curie project (grant agreement 658034; https://aspsync.wordpress.com). Detailed descriptions of the experiments and monitoring techniques can be found in Corbi et al. (2017). This data set is from one experiment characterized by the presence of a 7 cm wide barrier separating two asperities with equal size, geometry and friction. Here we provide PIV data relative to a 16.3 min long interval during which the experiment produces 138 analog earthquakes with an average recurrence time of 7 s. The PIV analysis yields quantitative information about the velocity field characterizing two consecutive frames, measured in this case at the model surface. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Corbi et al. (2017) paragraph 2. This data set has been used for: a) studying velocity variations (Fig. 2 in Corbi et al., 2021) and rupture patterns (Fig. 3a, b in Corbi et al., 2021) occurring during the velocity peak of one of the two asperities (aka trigger).

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

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.

Supplementary material to "Rough subducting seafloor reduces interseismic coupling and mega-earthquake occurrence: insights from analogue models"

This dataset contains digital image correlation (DIC) data of eight seismotectonic analogue experiments that were performed at the Laboratory of Experimental Tectonics (LET), Univ. Rome Tre, to investigate the effect of subduction interface roughness on the seismogenic behaviour of the megathrust. The study has been done in the framework of the Marie Sklodowska-Curie grant agreement 642029 – ITN CREEP. Together with DIC data we also provide analogue earthquake characteristics and Matlab scripts for visualization. Here we provide Digital Image Correlation data for eight experiments that last about 20 minutes (i.e., including tens of seismic cycles), of which four experiments include a smooth subduction interface and four a rough subduction interface. The DIC analysis provides a velocity field between two consecutive frames, measured at the surface of the model. Details about the nature and geometry of this interface, as well as the experimental procedure, model set-up and materials can be found in van Rijsingen et al. (2019), paragraph 2 and supporting information. A more detailed description of the data that we provide, the methods and the matlab scripts used for visualisation can be found in the data description file. An overview of the dataset can be found in the list of files.

Supplementary material to "Machine Learning can predict the timing and size of analog earthquakes"

This data set includes the results of digital image correlation of one experiment on subduction megathrust earthquakes with interacting asperities performed at the Laboratory of Experimental Tectonics (LET) Univ. Roma Tre in the framework of AspSync, the Marie Curie project (grant agreement 658034) lead by F. Corbi in 2016-2017. Detailed descriptions of the experiments and monitoring techniques can be found in Corbi et al. (2017 and 2019) to which this data set is supplementary material. We here provide Digital Image Correlation (DIC) data relative to a 7 min long interval during which the experiment 
produces 40 seismic cycles with average duration of about 10.5 s (see Figure S1 in Corbi et al., 2019). The DIC analysis yields quantitative about the velocity field characterizing two consecutive frames, measured in this case at the model surface. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Corbi et al. (2017) paragraph 2. This data set has been used for: a) studying the correlation between apparent slip-deficit maps and earthquake slip pattern (see Corbi et al., 2019; paragraph 4); and b) as input for the Machine Learning investigation (see Corbi et al., 2019; paragraph 5). Further technical information about the methods, data products and matlab scripts is proviced in the data description file. The list of files explains the file and folder structure of the data set.

Supplement to: Sandbox Rheometry: Co-Evolution of Stress and Strain in Riedel- and Critical Wedge-Experiments

This dataset is supplementary to the article of Ritter et al. (2017). In this article, a new experimental device is presented that facilitates precise measurements of boundary forces and surface deformation at high temporal and spatial resolution. This supplementary dataset contains the measurement data from two experiments carried out in this new experimental device: one experiment of an accretionary critical wedge and one of Riedel-type strike-slip deformation. For a detailed description of the set-up and an analysis of the data, please see Ritter et al. (2017). The data available for either experiment are: • A video showing deformation in top view together with the evolution of boundary force. This file is in AVI-format. • A time-series of 2D vector fields describing the surface deformation. These vector fields were obtained from top-view video images of the respective experiment by means of digital image correlation (DIC). Each vector field is contained in a separate file; the files are consecutively numbered. The vector fields are stored in *.mat-files that can be opened using e.g. the software Matlab or the freely available GNU Octave. They take the form of Matlab structure arrays and are compatible to the PIVmat-toolbox by Moisy (2016) that is freely available. The most important fields of the structure are: x and y, that are vectors spanning a coordinate system, and vx and vy, which are arrays containing the actual vector components in x- and y-direction, respectively. • A file containing the measurements of the boundary force applied to drive deformation. This file is also a *.mat-file, containing a structure F with fields force, velocity and position. These fields are vectors describing the force applied by the indenter, the indenter velocity and the indenter position

1