The Transition from Bedload to Complex Granular Dynamics on Steep Slopes: A Force Balance Perspective

Title:Flume Experiment Dataset – Granular Flow Tests (2023)

Authors:I. Koa, A. Recking, F. Gimbert, H. Bellot, G. Chambon, T. Faug

Contact:[e-mail]

Description:This dataset contains NetCDF (.nc) files from controlled flume experiments conducted in 2023 to study the transition from bedload to complex granular flow dynamics on steep slopes. Each file name encodes the experiment date and test number (e.g., CanalMU-20-04-2023-test5.nc = Test 5 on April 20, 2023).

Each test corresponds to a specific discharge (Q) value, detailed in the table below.

Example filename:CanalMU-20-04-2023-test5.nc → Test 5 conducted on April 20, 2023.

Discharge Table:

Discharge (l/s) | Date        | Test Number----------------|-------------|-------------0.14            | 06-04-2023  | Test 30.14            | 04-05-2023  | Test 50.15            | 13-04-2023  | Test 30.15            | 14-04-2023  | Test 10.15            | 14-04-2023  | Test 20.16            | 17-04-2023  | Test 20.16            | 18-04-2023  | Test 30.16            | 04-05-2023  | Test 30.16            | 04-05-2023  | Test 40.17            | 18-04-2023  | Test 40.17            | 18-04-2023  | Test 50.17            | 20-04-2023  | Test 20.17            | 20-04-2023  | Test 40.17            | 20-04-2023  | Test 50.18            | 20-04-2023  | Test 80.18            | 20-04-2023  | Test 90.19            | 20-04-2023  | Test 100.19            | 20-04-2023  | Test 110.20            | 20-04-2023  | Test 120.20            | 04-05-2023  | Test 10.20            | 04-05-2023  | Test 20.21            | 20-04-2023  | Test 130.21            | 21-04-2023  | Test 10.21            | 21-04-2023  | Test 20.22            | 21-04-2023  | Test 30.22            | 21-04-2023  | Test 40.23            | 21-04-2023  | Test 50.23            | 27-04-2023  | Test 20.23            | 27-04-2023  | Test 30.23            | 28-04-2023  | Test 70.24            | 28-04-2023  | Test 10.24            | 28-04-2023  | Test 20.24            | 28-04-2023  | Test 30.25            | 28-04-2023  | Test 40.25            | 21-06-2023  | Test 10.26            | 28-04-2023  | Test 60.26            | 21-06-2023  | Test 30.26            | 21-06-2023  | Test 40.27            | 22-06-2023  | Test 20.27            | 22-06-2023  | Test 30.27            | 22-06-2023  | Test 1

Data Acquisition and Processing:The original data were acquired using LabVIEW and saved in TDMS (.tdms) format. These files were processed using custom Python scripts to extract synchronized time-series data, assign physical units, and store the results in structured NetCDF-4 files.

NetCDF File Structure:Each file includes the following structured groups and variables:

1. Group: Data_Hydro (Hydraulic Measurements)  - Time_Hydro: Time [s]  - Date_et_heure_mesure: Measurement timestamps [string]  - Etat_de_l'interrupteur: Switch state [V]  - Debit_liquide_instant: Instantaneous water discharge [L/s]  - Debit_liquide_consigne: Target water discharge [L/s]  - Vitesse_tapis_instant: Instantaneous conveyor speed [m/s]  - Vitesse_tapis_consigne: Set conveyor speed [V]  - Debit_solide_instant: Instantaneous solid discharge [g/s]  - Hauteur1–4: Water heights from four sensors [cm]

2. Group: Data_Force (Impact Force Measurements)  - Time_Force: Time [s]  - Force_Normale: Vertical impact force [N]  - Force_Tangentielle: Tangential force [N]

3. Group: Data_Annexe (Experimental Metadata)  - channel_width, Channel_slope: Flume geometry  - Position_capteur_hauteur1–4: Water sensor locations [m]  - Position_capteur_force: Force sensor position [m]  - Plaque dimensions and mass: Plate size and weight [m, kg]  - Sensor frequencies and sensitivities [Hz, pC/N]

Format:NetCDF-4 (.nc)

Suggested software for reading:- Python (xarray, netCDF4)- NASA Panoply- MATLAB

Note:The data were processed using custom Python scripts. These are available from the corresponding author upon request.

Example: Accessing NetCDF Data in Python

The dataset can be read using the `netCDF4` or `xarray` libraries in Python. Below is a simple example using netCDF4:

```pythonfrom netCDF4 import Datasetimport numpy as np

# Open netCDF filedata = Dataset('CanalMU-20-04-2023-test5.nc')

# Load hydraulic datathydro = data.groups['Data_Hydro'].variables['Time_Hydro'][:]Qcons = data.groups['Data_Hydro'].variables['Debit_liquide_consigne'][:]Qins = data.groups['Data_Hydro'].variables['Debit_liquide_instant'][:]Tapis = data.groups['Data_Hydro'].variables['Vitesse_tapis_consigne'][:]h1 = data.groups['Data_Hydro'].variables['Hauteur1'][:]h2 = data.groups['Data_Hydro'].variables['Hauteur2'][:]h3 = data.groups['Data_Hydro'].variables['Hauteur3'][:]h4 = data.groups['Data_Hydro'].variables['Hauteur4'][:]

# Load force datatforce = data.groups['Data_Force'].variables['Time_Force'][:]FN = data.groups['Data_Force'].variables['Force_Normale'][:]FT = data.groups['Data_Force'].variables['Force_Tangentielle'][:]

# Apply calibration factorsFN = FN FT = FT

# Fetch metadataslope = data.groups['Data_Annexe'].variables['Channel_slope']alpha = np.arctan(slope[:]/100)L = data.groups['Data_Annexe'].variables['Longueur_plaque_impact'][:]W = data.groups['Data_Annexe'].variables['Largeur_plaque_impact'][:]

```

For more advanced processing, consider using `xarray` which provides easier multi-dimensional data access.