DOI: 10.5061/dryad.m37pvmd88
title: LES-DPM simulation dataset for oscillatory flow over a mobile, rippled bed

description: This repository contains the output data files from the LES-DPM numerical
 model utilized for the analyses presented in DeVoe et al. (2025)*. Please
 note that the model is a coupled two-phase model and that this repository
 contains both the fluid and particle data, as well as the necessary files
 to convert data from their native binary format to ASCII format.
   The LES-DPM was developed by Hagan (2018) and validated by
 Hagan et al. (2023). Note: This dataset was generated using the
 model's governing equations and framework as presented by Hagan
 (2018) and Hagan et al. (2023), but is not the same dataset used for the
 analyses in those two manuscripts. This dataset has a higher sampling
 frequency (100 Hz) and a shorter duration than the datasets used in Hagan
 (2018) and Hagan et al. (2023). Please refer to the README and DeVoe et
 al. (2025)* for additional information about the model parameters. *
 DeVoe, S. R., Wengrove, M. E., Foster, D. L., & Hagan, D. S.
 (2025). Characterization of the spatiotemporal distribution of shear
 stress and bedload flux within a mobile, rippled bed. Journal of
 Geophysical Research: Oceans. DOI: doi.org/10.29/2025JC022369
description: # LES-DPM RippledBed Dataset This repository contains the output data
 files from the LES-DPM numerical model utilized for the analyses presented
 in DeVoe et al. (2025)*.* Please note that the model is a coupled
 two-phase model and that this repository contains both the fluid and
 particle data, as well as the necessary files to convert data from their
 native binary format to ASCII format. The LES-DPM was developed by Hagan
 (2018) and validated by Hagan et al. (2023). Note: This dataset was
 generated using the model's governing equations and framework as
 presented by Hagan (2018) and Hagan et al. (2023), but is not the same
 dataset used for the analyses in those two manuscripts. This dataset has a
 higher sampling frequency (100 Hz) and a shorter duration than the
 datasets used in Hagan (2018) and Hagan et al. (2023). Please refer to the
 README and DeVoe et al. (2025) for additional information about the model
 parameters. **Corresponding Author for Dataset & LES-DPM Inquiries:**
 Yves Dubief, University of Vermont. **Corresponding Author Email:**
 ydubief [at] uvm [dot] edu. *DeVoe, S. R., Wengrove, M. E., Foster, D. L.,
 & Hagan, D. S. (2025). Characterization of the spatiotemporal
 distribution of shear stress and bedload flux within a mobile, rippled
 bed. Journal of Geophysical Research: Oceans. DOI:
 doi.org/10.29/2025JC022369 ## Written by Savannah DeVoe, Aug. 2024 Edited
 by Savannah DeVoe, February 2026: * Updated the URL at the end of the
 README in the Hagan et al. (2018) citation, which originally included a
 UNH Proquest login prompt. URL is now a generic/public access link. Edited
 by Savannah DeVoe, July 2025: * Grouped individual data files into .zip
 folders in groups of 100 (e.g., fluid000001-fluid000100.zip) to meet new
 Dryad limit of 100 files per repository * Merged particle and fluid
 repositories together (originally, they were separate due to file size and
 number limitations) * Incorporated article title and reference edits
 following paper acceptance/JGR reviewer feedback * Additional edits to
 .f90, .txt, and README files for further clarity. # File Descriptions *
 README: This file. Contains general information about the dataset
 properties, including, but not limited to, a description of the
 model's boundary conditions and initial conditions, the particle and
 fluid variables output by the model, the sampling rate, the length of the
 time series, the oscillation period, wave zero-crossing time steps, etc. *
 fluid000XXX-fluid000XXX.zip: Zip files containing individual binary fluid
 data files for time step XXX (e.g., fluid000001-fluid000100.zip contains
 fluid files fluid.000001, fluid.000002, ... etc., where fluid.000001 is
 the fluid data for time step 1). For this dataset, XXX = 1-903. After zip
 files have been extracted, fluid.000XXX binary files can be opened in any
 text editor application but they are not human-readable until after they
 have been converted. The following zip files are included: *  
 fluid000001-fluid000100.zip *   fluid000101-fluid000200.zip *  
 fluid000201-fluid000300.zip *   fluid000301-fluid000400.zip *  
 fluid000401-fluid000500.zip *   fluid000501-fluid000600.zip *  
 fluid000601-fluid000700.zip *   fluid000701-fluid000800.zip *  
 fluid000801-fluid000900.zip *   fluid000901-fluid000903.zip *
 particle000XXX-particle000XXX.zip: Same as fluid000XXX-fluid000XXX.zip
 files, but for the binary particle data files. The following zip files are
 included: *   particle000001-particle000100.zip *  
 particle000101-particle000200.zip *   particle000201-particle000300.zip *
   particle000301-particle000400.zip *   particle000401-particle000500.zip
 *   particle000501-particle000600.zip *  
 particle000601-particle000700.zip *   particle000701-particle000800.zip *
   particle000801-particle000900.zip *   particle000901-particle000903.zip
 * extract_fluid.f90: Fortran script for converting binary fluid data files
 into ASCII format .DATA files for further processing. Can be opened in any
 text editor application. Contains instructions for installing specific
 open-source packages required for binary file conversion, and instructions
 for either single file conversion (in Terminal/WSL prompt) or batch
 conversion using the binary_textfileconv_fluid_stats routine (see below).
 * extract_particles.f90: Same as extract_fluid.f90, but for the binary
 particle data files. Batch conversion performed using the
 binary_textfileconv_particle_stats routine (see below). *
 binary_textfileconv_fluid_stats.txt: Simple example script for batch
 processing to extract multiple binary fluid files at once with the
 extract_fluid.f90 routine. Written in MATLAB language but can be adapted
 to other programming languages. To open in MATLAB, simply change the file
 extension from .txt to .m, or copy/paste the contents of the file into a
 new MATLAB script. * binary_textfileconv_particle_stats.txt: Same as
 binary_textfileconv_fluid_stats.txt, but for the binary particle data
 files. * matfileconv_fluid_stats.txt: Example script for importing
 converted fluid000XXX.DATA files into MATLAB, parsing columns into
 particle variables, and saving the variables in a fluid000XXX.mat file
 format. Written in MATLAB language but can be adapted to other programming
 languages. * matfileconv_particle_stats.txt: Same as
 matfileconv_fluid_stats.txt, but for the converted particle000XXX.DATA
 files. Users should begin by reading this file (README), then follow the
 instructions provided in extract_fluid.f90 and extract_particles.f90 to
 install required packages for conversion. Batch processing can then be
 done following the example in binary_textfileconv_fluid_stats.txt and
 binary_textfileconv_particle_stats.txt, and finally, data can be prepped
 for post-processing following the MATLAB example in
 matfileconv_fluid_stats.txt and matfileconv_particle_stats.txt. \***Please
 note that binary conversion and preparation for post-processing may take
 several minutes if you choose to process all 903 fluid or all 903 particle
 files at once. You can check the progress of conversion in your output
 folder as new .DATA or .mat files are created.*** # LES-DPM Model
 Description The LES-DPM data is derived from a coupled Large Eddy
 Simulation (LES) and Discrete Particle Model (DPM). The model's
 governing equations were developed by Hagan (2018) and validated against
 laboratory data by Hagan et al. (2023). The model simulates oscillatory
 flow over a movable, rippled bed comprised of individual sediment grains.
 The LES solves large scales of the fluid flow and models the small scales,
 while the DPM resolves the position and velocity of individual particles.
 See Hagan et al. (2023) for more information about the governing equations
 and numerical methodology. # Model Domain The domain measures 0.60 m x
 0.15 m x 0.30 m (LxWxH). The top and bottom boundaries have a no-slip
 condition, while the streamwise and spanwise boundaries are periodic. The
 bottom wall is covered by a rippled bed comprised of individual sediment
 grains. There are 6 sinusoidal ripples in the domain with a wavelength of
 0.10 m and a height of 0.02 m. A total of 1,540,800 individual particles
 exist in the model. The fluid in the domain is water. The coordinate
 system for the DATA defines x in the streamwise, z in the spanwise, and y
 in the vertical directions, respectively. (Note this differs from the
 coordinate system adopted in DeVoe et al., 2025.) The fluid grid system is
 comprised of 256 x 128 x 64 nodes (streamwise, vertical, spanwise,
 respectively) with a uniform dx = dz = 0.0023 m and a varying dy (smallest
 near the top and bottom boundaries and larger towards the center of the
 domain). Particles are simulated on a Lagrangian reference frame and can
 exist at any (x,y,z) position within the domain. See Hagan et al. (2023)
 or DeVoe et al. (2025) for more information about the model domain. #
 Model Initial Conditions and Forcing Particles in the model are first
 allowed to settle under gravity in a face-centered cubic configuration
 (solid volume fraction = 0.74) in the still fluid. After settling, the
 domain is subjected to fluid oscillations driven by an oscillating
 pressure gradient with period, T = 2.4 s. The maximum fluid velocity in
 the free stream reaches 0.23 m/s. Quasi-equilibrium is reached after
 approximately 3 wave periods (Hagan et al., 2023). The bed is then
 subjected to 11 additional oscillations. The LES-DPM datasets used by
 Hagan (2018) and Hagan et al. (2023) contained these 11 oscillation
 periods with a model output of approximately 10 Hz. The dataset used in
 DeVoe et al. (2025) contains only 3 full oscillations in the set of 11
 oscillations, and is output at a higher frequency (100 Hz). See Hagan et
 al. (2023) or DeVoe et al. (2025) for more information about the initial
 conditions and forcing. # Time Series The dataset contains 903 fluid files
 and 903 particle files, with each file pertaining to a single instant in
 time (i.e., fluid.000001 and particle.000001 are the fluid data and
 particle data for time step 1, respectively). The data is output at 100
 Hz, meaning each oscillation is comprised of 240 samples. The wave zero
 crossings (where the free-stream fluid velocity is approximately zero)
 occur at time instances 1, 241, 481, and 721. The remaining files
 (722-903) are for a partial fourth oscillation period. NOTE: Time step 586
 contains anomalous fluid velocity data. As such, it should be replaced by
 interpolation of the fluid variables between time steps 585 and 587. #
 Binary Data Files Data is divided into binary fluid and particle files for
 each time instant. E.g., particle data for time step 1 is contained in the
 binary file particle.000001, and fluid data for time step 1 is contained
 in fluid.000001. Binary files are compressed into zip files that must be
 downloaded and extracted (because Dryad limits repositories to 100 files
 or less). After extraction, the individual binary files must be converted
 from to ASCII format using the extract_fluid.f90 and extract_particles.f90
 scripts via Terminal/WSL prompt. Refer to those documents for instructions
 on how to convert from binary to ASCII (.DATA file). Example code is
 provided to execute the binary file conversion in a loop (for batch
 processing multiple binary files at once) and to then import the converted
 ASCII file into MATLAB for further processing. These example codes are
 provided as .txt files so they can be opened, viewed, and subsequently
 converted to other programming languages if the user does not have access
 to MATLAB or wishes to use another program. Once the binary files are
 converted, the data in the resulting .DATA file is divided into the
 following columns with units shown in square brackets: # Fluid Variables *
 x - fluid grid x position (streamwise) [m] * y - fluid grid y position
 (VERTICAL) [m] * z - fluid grid z position (SPANWISE) [m] * p - pressure
 [N/m2] * visc - dynamic viscosity [kg/m-s] * epsf - fluid volume fraction
 [unitless] * rho - density [kg/m3] * pcrit - P criterion, first invariant
 of the velocity gradient tensor (sum of rank one determinants on diagonal)
 * qcrit - Q criterion, second invariant of the velocity gradient tensor
 (sum of rank two determinants on diagonal) * rcrit - R criterion, third
 invariant of the velocity gradient tensor (sum of rank three determinants
 on diagonal) * u - x-component of fluid velocity (streamwise) [m/s] * v -
 y-component of fluid velocity (VERTICAL) [m/s] * w - z-component of fluid
 velocity (SPANWISE) [m/s] # Particle Variables * n - row number [unitless]
 (not physically relevant to the model, reflects binary conversion order
 only) * id - unique particle identification number [unitless] * diam -
 particle diameter [m] * x - particle x position (streamwise) [m] * y -
 particle y position (VERTICAL) [m] * z - particle z position (SPANWISE)
 [m] * u - x-component of particle velocity (streamwise) [m/s] * v -
 y-component of particle velocity (VERTICAL) [m/s] * w - z-component of
 particle velocity (SPANWISE) [m/s] * wx - x-component of particle angular
 velocity (streamwise) [m/s] * wy - y-component of particle angular
 velocity (VERTICAL) [m/s] * wz - z-component of particle angular velocity
 (SPANWISE) [m/s] # REFERENCES DeVoe, S. R., Wengrove, M. E., Foster, D.
 L., & Hagan, D. S. (2025). Characterization of the spatiotemporal
 distribution of shear stress and bedload flux within a mobile, rippled
 bed. Journal of Geophysical Research: Oceans. DOI:
 [https://doi.org/10.29/2025JC022369](https://doi.org/10.29/2025JC022369).
 Hagan, D., Wengrove, M., Dubief, Y., Desjardins, O., Frank-Gilchrist, D.,
 & Calantoni, J. (2023). Particle based Large Eddy Simulation of vortex
 ripple dynamics using an Euler–Lagrange approach. European Journal of
 Mechanics-B/Fluids, 97, 53-69.
 [https://doi.org/10.1016/j.euromechflu.2022.09.003](https://doi.org/10.1016/j.euromechflu.2022.09.003). Hagan, D. S. (2018). Large eddy simulation of oscillatory flow over a mobile rippled bed using an euler-lagrange approach (Order No. 10747462). Available from ProQuest Dissertations & Theses Global. (2025980859). Retrieved from [https://www.proquest.com/docview/2025980859.](https://www.proquest.com/docview/2025980859)