Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “Accretionary Wedges”
Data for paper: Control of fault weakening on the structural styles of underthrusting-dominated non-cohesive accretionary wedges
<p>This repository contains data related to the paper:<br> A. Bauville, M. Furuchi and M. Gerbault, Control of fault weakening on the structural styles of underthrusting-dominated non-cohesive accretionary wedges, Journal of Geophysical Research, 2020.</p> <p>It contains data for all simulations shown in Fig. 7 (last timestep)</p> <p>List of file for each simulations:<br> modelState.json: json file containing various information about the state of the model<br> particles_strain.bin: binary file containing strain data for all particles<br> particles_x.bin: current x position for all particles<br> particles_y.bin: current y position for all particles<br> particles_xIni.bin: initial x position for all particles<br> particles_yIni.bin: initial y position for all particles</p> <p># File format<br> n, u, data</p> <p>n = number of particles bytesize=[1 * int32]<br> u = characteristic unit bytesize=[1 * double]<br> data = data for n particles bytesize=[n * single]</p> <p># example to extract data from bin files in python<br> import numpy as np<br> import os</p> <p>with open(FileName, 'rb') as f:<br> f.seek(12, os.SEEK_SET)<br> data = np.fromfile(f, dtype=np.single, count=-1, sep='')</p>
Simulations scripts for: Strain localization patterns and thrust propagation in 3-D discrete element method (DEM) models of accretionary wedges
<p>High-resolution three-dimensional discrete element method (DEM) simulations of sandbox-scale models of accretionary wedges performed in this study suggest thrusts follow a variety of propagation processes and orientations in the wedges depending on a number of factors including the stage of development of the wedge (precritical vs. critical), basal friction, and type of thrust (forward vs. backward-vergent). In terms of propagation processes, two clear mechanisms are identified. The first involves propagation from the decollement to the wedge top, similar to the standard model of thrust propagation seen in many kinematic models, and in the second, thrusts grow downward from an initial nucleation point just below the top surface of the wedge as well as upward from the decollement joining in the middle. In terms of orientation, forward-vergent thrusts initially form at Roscoe or Arthur orientations, and over shortening, form at Coulomb orientations. To arrive at these results, a wide array of continuum parameters and fields were extracted from the granular assembly of the DEM simulations, including stress, strain, strain rate, kinetic energy, Mohr-Coulomb parameters, and proximity to yielding using the Drucker-Prager criterion to visualize thrust nucleation and propagation. Lastly, the advantages and disadvantages of these continuum proxies for discerning failure in the granular assembly are considered, and the spatial and temporal relationship between proximity to yielding and strain localization (both pre-peak and persistent shear banding) in the granular model of an accretionary wedge is explored.</p>
Simulations scripts for: Strain localization patterns and thrust propagation in 3-D discrete element method (DEM) models of accretionary wedges
Open the record for dataset details and reuse information.
Effects of multi-seamount subduction on accretionary wedge deformation: Insights from analogue modelling
<p>Law data for the manuscript titled "Effects of multi-seamount subduction on accretionary wedge deformation: Insights from laboratory experiments" to the Journal Tectonophysics.</p>
Data set for "Accretion cycles, structural evolution, and thrust activity in accretionary wedges with various décollement configurations: Insights from sandbox analog modeling"
<p>This data set is associated with the paper, ``Accretion cycles, structural evolution, and thrust activity in accretionary wedges with various décollement configurations: Insights from sandbox analog modeling'' by Atsushi Noda, Fabien Graveleau, Cesar Witt, Frank Chanier, and Bruno Vendeville. It is currently available on doi:PREPRINT and to be submitted to the Journal of Geophysical Research, Solid Earth. When citing this data release, please cite as well the paper.</p> <p>Contact: Atsushi Noda, a.noda@aist.go.jp</p> <p>The provided zip file contains the data below.</p> <p>DIC ---- image: Photo images used for DIC analysis<br> |<br> |-- ROI: Image files of "Region of interest" for DIC analysis<br> |<br> |-- matdata: MATLAB data files produced by Ncorr DIC analysis<br> |<br> |-- plot: Plots produced from the MATLAB data files<br> |<br> |-- movie: Images of plots of DIC analysis<br> |<br> |-- data: Output data generated by python scripts</p> <p>figure ---- Output pdf files produced by python scripts</p> <p>Geometry ---- plot: plots for geometrical parameters<br> |<br> |-- qgis: geometrical data files (shapefile format)</p> <p>RAW ---- image: RAW photo images for all models<br> |<br> |-- movies: Images of photos for all models</p> <p>script ---- ncorr_plot_eng.py: To plot the kinematic parameters from MATLAB data file<br> |<br> |-- ncorr_plot_all.py: To plot summary diagrams for the kinematic parameters<br> |<br> |-- envelope.py: To plot theoretical taper angles<br> |<br> |-- comp_wux.py: To calculate and plot strain ratios<br> |<br> |-- plot_param.py: To plot geometrical parameters<br> |<br> |-- calc_strength.py: To calculate and plot the wedge/detachment strengths <br> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.