This dataset includes volumetric data sets from a Digital Volume Correlation (DVC) analysis for recreating images of a re-analyzed analogue models previously presented in (Zwaan et al., 2018). Using a brittle-viscous two-layer setup, this experiment focused on the evolution of a rift-pass structure. On top of the viscous layer, two viscous seeds are placed with a right-stepping stair-case offset to simulate two propagating rift segments, confining a central rift-pass block (Fig. 1). The selected model was analyzed by means of Digital Volume Correlation (DVC) applied on X-Ray computed tomography (XRCT) volumes. The data set includes DVC data in the form of .mat files for incremental (i.e., 20 min intervals) and cumulative displacement components. In addition, this dataset provides a MATLAB script for 1) recreating volumetric displacement sets of subsequent time steps 2) calculating finite stretches and 3) rigid-body rotations. The used experiment was performed at the Tectonic Modelling Laboratory of the University of Bern (UB). DVC analysis was performed at the Royal Holloway University London (RHUL). The model consists of a two-layer brittle-viscous set up with a total thickness of 8 cm and the set up lies on top of a 5 cm thick foam-plexiglass base with a length and width of 800 mm by 305 mm, respectively. Before model construction, the foam-plexiglass assemblage is placed between longitudinal side walls and expands during the course of the experiment as the mobile sidewalls move apart. The applied divergence velocity is 7.5 mm/h and with has an orthogonal direction with respect to the viscous seeds. This results in a maximum displacement of 30 mm after a total run time of 4h. Detailed descriptions of the experiment, mechanical properties as well as monitoring techniques can be found in Schmid et al. (2024).
This dataset provides friction data from ring-shear tests on glass beads with a diameter of 200-300 µm used in analogue modelling of tectonic processes as a rock analogue for “weak” layers in the earth’s upper crust (e.g. Klinkmüller et al., 2016; Ritter et al., 2016; Lohrmann et al., 2003) or as “seismogenic” crust (Rudolf et al., 2022). The glass beads are characterized by means of internal friction coefficients µ and cohesion C. According to our analysis the materials show a Mohr-Coulomb behaviour characterized by a linear failure envelope. Peak, dynamic and reactivation friction coefficients of the glass beads are µP = 0.51 , µD = 0.40, and µR = 0.44, respectively (Table 5). Cohesion of the material ranges between 40 Pa and 70 Pa. The material shows a minor rate-weakening of ~1% per ten-fold change in shear velocity v and a stick-slip behaviour at low shear velocities and at high loads.
This dataset provides friction data from ring-shear tests on glass beads with a diameter of less than 50 µm used in analogue modelling of tectonic processes as a rock analogue for “weak” layers in the earth’s upper crust (e.g. Klinkmüller et al., 2016; Ritter et al., 2016; Lohrmann et al., 2003) or as “seismogenic” crust (Rudolf et al., 2022). The glass beads are characterized by means of internal friction coefficients µ and cohesion C. According to our analysis the materials show a Mohr-Coulomb behaviour characterized by a linear failure envelope. Peak, dynamic and reactivation friction coefficients of the glass beads are µP = 0.47 , µD = 0.44, and µR = 0.47, respectively (Table 5). Cohesion of the material ranges between 50 Pa and 70 Pa. The material shows a neglectable rate-weakening of <1% per ten-fold change in shear velocity v.
This dataset provides friction data from ring-shear tests (RST) for wheat flour used as a fine-grained, cohesive analogue material for simulating brittle upper crustal rocks in the analogue labor-atory of the Institute of Geophysics of the Czech Academy of Science (IGCAS). It is characterized by means of internal friction coefficients µ and cohesion C. According to our analysis the materials show a Mohr-Coulomb behaviour characterized by a linear failure envelope. Peak friction coefficients µP of the tested material is ~0.72, dynamic friction coeffi-cients µD is ~0.67 and reactivation friction coefficients µR is ~0.70. Cohesions of the material range between 27 and 50 Pa. The material shows a minor rate-weakening of ~1.5% per ten-fold change in shear velocity v and a stick-slip behaviour at low shear velocities.
This dataset provides the surface velocity fields derived with MatPIV (open-source Matlab toolbox for Particle Image Velocimetry; Sveen 2004) of three seismotectonic analog models (e.g., Rosenau et al., 2017) performed to investigate the role of geometry and friction of a single subducting seamount on the seismogenic behavior of the megathrust. Model 1 has a seamount covered by sandpaper (i.e., high friction) that is placed at 1/2 of the trench-parallel length of the seismogenic zone. Model 3 has the same geometry of model 1, but the seamount is in direct contact with the gelatin (i.e., not covered by sandpaper, hence low friction). Model 5 has a low friction patch (i.e., no geometry) that is placed again at 1/2 of the trench-parallel length of the seismogenic zone. Together with the surface velocity fields, we also provide Matlab scripts for visualization. A more detailed description of the experimental setup, configuration of the models and materials can be found in Menichelli et al. (submitted), to which this dataset is supplementary. Our seismotectonic models represent a downscaled subduction zone (1 cm in the model corresponds to 6.4 km in nature; Rosenau et al., 2017). The experimental setup consists of a 60 x 34 cm2 Plexiglass box with a 10°-dipping aluminum basal plate that moves downward with a constant velocity of 0.01 cm/s, analog of the subducting plate. The overriding plate is represented by an elastic wedge of 2.5 wt% pigskin gelatin at T = 10 °C (Di Giuseppe et al., 2009). The seismogenic zone of the megathrust is simulated using a rectangular sandpaper patch (Corbi et al., 2013), with a downdip width of 16 cm and located 31 and 47 cm from the backstop. This corresponds to a 100-km-wide seismogenic zone extending over a depth interval between 15 and 34 km. The updip and down dip aseismic regions of the megathrust are simulated by plastic sheets that are fixed on the setup frame and not subject to subduction (Corbi et al., 2013). A 3D-printed PLA seamount is placed on the seismogenic zone (e.g., Van Rijsingen et al., 2019). The seamount has a height of 6.28 mm and a diagonal length of 94 mm, corresponding to 4 km and 60 km in nature, respectively. These dimensions scale well-known seamounts, such as the Joban Seamount chain in the Japan Trench or the Louisville seamount chain in the Tonga-Kermadec Trench. Experiments were monitored with a CCD camera that acquired a sequence of high-resolution top-view images (1600 x 1200 pixels2, 8 bit, 256 gray levels) at 7.5 fps for the entire duration of the experiment (i.e., ca. 24 minutes). Images are processed with Particle Image Velocimetry (PIV; Adam et al., 2005) using the open-source Matlab toolbox MatPIV (Sveen, 2004). MatPIV provides the velocity field between two consecutive frames, measured at the surface of the model. The velocity field was then used as input to identify analog seismic events using the open-source Matlab function findpeak. The threshold used was 0.1 cm/s. Once earthquakes were identified, we derived their source parameters such as seismic slip, magnitude, and recurrence time following Corbi et al. (2017) and van Rijsingen et al. (2019).
The software is provided as an executable python module. The software automatically analyzes the files present in the data publication. The results are saved in the form of the images presented in the main publication. Each figure is implemented as a dedicated function that first loads the necessary data, then does some processing steps, such as curve fitting, and then plots the outputs in the desired layout. A 'main' function calls all figure functions sequentially. However, the packages is modular so that each individual plot has a standalone function which could be used with other, similarly structured data. Several submodules provide additional data for plotting, e.g. the 'groups' submodule that contains naming schemes and the densities for all samples.
This dataset presents the raw data of an experimental series of analogue models performed to investigate the influence of inherited brittle fabrics on narrow continental rifting. This model series was performed to test the influence of brittle pre-existing fabrics on the rifting deformation by cutting the brittle layer at different orientations with respect to the extension direction. An overview of the experimental series is shown in Table 1. In this dataset we provide four different types of data, that can serve as supporting material and for further analysis: 1) The top-view photos, taken at different steps and showing the deformation process of each model; they can be used to interpret the geometrical characteristics of rift-related faults; 2) Digital Elevation Models (DEMs) used to reconstruct the 3D deformation of the performed analogue models, allowing for quantitative analysis of the fault pattern. 3) Short movies built from top-view photos which help to visualize the evolution of model deformation; 4) line-drawing of fault and fracture patters to be used for fault statistical quantification. Further details on the modelling strategy and setup can be found in Corti (2012), Maestrelli et al. (2020), Molnar et al. (2020), Philippon et al. (2015), Zwaan et al. (2021) and in the publication associated with this dataset. Materials used for these analogue models were described in Montanari et al. (2017) Del Ventisette et al. (2019) and Zwaan et al. (2020).
This dataset contains measurements of viscous and viscoelastic materials that are used for analogue modelling. Proper density and viscosity scaling of ductile layers in the crust and lithosphere, requires materials like Polydimethylsiloxane (PDMS), to be mixed with fillers and low viscoity silicone oils. Changing the filler content and filler material, the density, viscosity and power-law coefficient can be tuned according to the requirements. All materials contain a large amount of PDMS and all but one a small amount of an additional silicone oil. Adding plasticine or barium sulfate lead to shear thinning rheologies with power-law exponents of p<0.95. Adding corundum powder only has a minor effect on the power-law exponent. Some mixtures also have an apparent yield point but all are in the liquid state in the tested range. In general, the rheologies of the materials are very complex and in some cases strongly temperature dependent. However, in the narrow range of relevant strain rates, the behaviour is well defined by a power-law relation and thus found suitable for simulating ductile layers in crust and lithosphere.
This dataset includes raw data used in the paper by Reitano et al. (2022), focused on the effect of boundary conditions on the evolution of analogue accretionary wedges affected by both tectonics and surface processes; the paper also focuses on the balance between tectonics and surface processes as a function of the boundary conditions applied. These boundary conditions are convergence velocity and basal slope (i.e., the tilting toward the foreland imposed prior the experimental run). The experiments have been carried out at Laboratory of Experimental Tectonics (LET), University “Roma Tre” (Rome). Detailed descriptions of the experimental apparatus and experimental procedures implemented can be found in the paper to which this dataset refers. Here we present: • Pictures recording the evolution of the models. • GIFs showing time-lapses of models. • Raw DEMs of the models and Incision DEMs, used for extracting data later discusses in the paper.
The data set includes the digital image correlation of 16 dextral strike-slip experiments performed at the University of Massachusetts at Amherst (USA). The DIC data sets were used for a machine learning project to build a CNN that can predict off-fault deformation from active fault trace maps. The experimental set up and methods are described with the main text and supplement to Chaipornkaew et al (in prep). To map active fault geometry and calculate the off-fault deformation we use the Digital Image Correlation (DIC) technique of Particle Image Velocimetry (PIV) to produce incremental horizontal displacement maps. Strain maps of the entire region of interest can be calculated from the displacements maps to determine the fault maps and estimate off-fault strain throughout the Region of Interest (ROI). We subdivide each ROI into five subdomains, windows, for training the CNN. This allows a larger dataset from the experimental results. The data posted here include the incremental displacement time series and animations of strain for the entire ROI.
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