Published on 23 May 2022
Experiments on a single large particle segregating in bedload transport
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This depository contains all the data presented in "Experiments on a single large particle segregating in bedload transport" from H. Rousseau, J. Chauchat and P. Frey in Physical Review Fluids, as well as the code to read these data.There are 10 folders that each correspond to a configuration (i.e. size ratio and Shields number). These folders contain subfolders that correspond to the different repetitions we made for each configuration. In a subfolder, one can find:- The first image of the experiment (t=0s).- An hdf5 file called "bedAndWaterLines.h5" which contains the data for the waterline positions and the bedline positions with time.- An hdf5 file called "frame_0_to_3000_with_step_1_and_shift_1.hdf5" which contains the granular bed velocity fields Ux and Uy interpolated over the time. These velocities have been obtained using the OpyFlow toolbox (https://github.com/groussea/opyflow.git).- An hdf5 file called "DataTracked.h5" which contains the results from the detection of the intruder. Inside "DataTracked.h5", one can find one folder by timestep that includes the coordinates of the intruder. The total number of frame, the acquisition rate and the scale are also saved as datasets in "DataTracked.h5".The code "plotData.py" has been coded in python3 and allows one to read the data from the hdf5 files (make sure you installed the h5py package for python before). "plotData.py" is annotated and thus, it contains all the instructions to plot the data of a given repetition. It is based on the following classes:- "LoadResult" that reads "DataTracked.h5"- "loadWaterAndBed" that reads "bedAndWaterLines.h5"- "readOpyf" that reads "frame_0_to_3000_with_step_1_and_shift_1.hdf5" The file "listRepetitions.ods" is also provided. It allows one to match a given experiment in the paper to its name in this depository.Do not hesitate to contact us if you need more info.
Citations (4)
- https://doi.org/10.5281/zenodo.11504983DataCite OpenAlex
Cited on 06 June 2024
Weight: 1.36
- https://doi.org/10.5281/zenodo.11058212DataCite OpenAlex
Cited on 24 April 2024
Weight: 1.36
Cited on 24 April 2024
Weight: 1.36
- https://doi.org/10.1103/physrevfluids.7.064305DataCite OpenAlex
Cited on 28 June 2022
Weight: 1.00
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Publication Details
Subfield
Computational Mechanics
Field
Engineering
Domain
Physical Sciences
Confidence Score
91%
Source
Open Alex