DOI: 10.5281/zenodo.7487189
title: Data used in 'Slumping regime in lock-release turbidity currents'

description: This repository contains the data used in the paper:

Gadal, C., Mercier, M., Rastello, M., & Lacaze, L. (2023). Slumping regime in lock-release turbidity currents. Journal of Fluid Mechanics, 974, A4. doi:10.1017/jfm.2023.762
where the slumping regime of turbidity currents is studied with respect to the initial volume fraction, the bottom slope and the particle settling velocity. The folder 'runs' contains 169 netcdf4 files corresponding to each experimental run used in the paper. For each run, the structure of the NetCDF file is the following:

attributes:

particle_type: particle type used (silica sand, glass beads or saline water)
run_number: NetCDF file name
expe_type: always lock-release here
surface_type: can be 'open surface' or 'rigid lid'
set_up: can be 'set-up 1' or 'set-up 2'
run_oldID: run name corresponding to the experimental notebook
groups:

initial_parameters:

dimensions(sizes):
variables(dimensions):

Bottom slope(): bottom slope
Current density(): initial average (fluid + particle) lock density
Grain density(): particle density (not measured, estimated)
Grain diameter(): particle diameter
Initial Reynolds number(): initial Reynolds number, [rho_0 * u_0 * h_0 / mu]
Initial Rouse number(): initial Rouse number, [v_s / u_0]
Initial volume fraction(): initial lock particle volume fraction
Reduced gravity(): reduced gravity, [g*(rho_0 - rho_f)/rho_f]
Settling velocity(): particle settling velocity
Temperature(): water temperature (not measured)
V0 (lock volume)(): lock suspension volume
Water density(): water density
Water dynamic viscosity(): water dynamic viscosity (not measured)
h0 (lock height)(): suspension height inside lock
u0 (velocity scale)():  velocity scale, [sqrt(g'*h_0)]
w0 (tank width)(): lock crosstream width
x0 (lock length)(): lock streamwise length
scalar_variables:

dimensions(sizes): tuples(2), x(1181)
variables(dimensions):

Av. shape('x',): current average shape
Av. shape head volume(): Volume per unit of width of the head part of current average shape
Av. shape tail volume(): Volume per unit of width of the tail part of current average shape
Av. shape volume(): Volume per unit of width of current average shape
Bulk entrainment coefficient(): Bulk entrainment coefficient during slumping
Current Froude number(): Current Froude number, [u_c/sqrt(g' * h_b)]
Current Reynolds number(): Current Reynolds number, [rho_0 * u_c * h_b / mu]
Current Rouse number(): Current Rouse number, [v_s / u_c]
Current head height (log fit)(): current height h_h coming from log fit
Current height (benjamin fit)(): current height h_b coming from fit of Benjamin's shape
Current nose height (benjamin fit)(): current nose height h_n coming from fit of Benjamin's shape
Current nose height (log fit)(): current nose h_n coming from log fit
Geometrical Froude number(): Current Geometrical Froude number, [u_c/sqrt(g' * h0)]
Geometrical Reynolds number(): Current Geometrical Reynolds number [rho_0 * u_c * h0 / mu]
Times lock opening (tstart, tend)('tuples',): Start and end times of lock opening
Times slumping regime (tstart, tend)('tuples',): Start and end times of constant velocity regime
Velocity (slumping regime)(): Current velocity during slumping
time_series:
dimensions(sizes): time(3071)
variables(dimensions):
Volume('time',): current volume per unit of width
contour time series (x)('time',): x coordinate time series of the current contours
contour time series (y)('time',): y coordinate time series of the current contours
position('time',): front position
time('time',): time vector
velocity('time',): front velocity
Most variables possess the following attributes:

unit: corresponding unit
std: error(s) on the given quantity, calculated by error propagation from measurement uncertainties using the `uncertainties` module (https://pythonhosted.org/uncertainties/) in Python.
comments: comments on the given quantity (definition, formulas, etc ..)
Note that all variables related to the current shape are not available for experimental runs carried out in set-up 2.The script ReadPlotData.py shows how to display the structure of a NetCDF file, and gives examples of how to load some variables and plot them by reproducing some of the paper's figures.The CSV file 'dataset_summary.csv' offers a summary of all runs and corresponding experimental parameters, allowing for easier access for testing purposes. *Note that errors are not given in this file.*
OpenData License: licence-ouverte-v2.0
If you use this open data in your work (research or other), please cite in your bibliography the following reference doi:https://doi.org/10.1017/jfm.2023.762