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43 results for “compressible flows”
Compressible Hydrodynamics Simulation Data for "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows"
<p><strong>Background</strong></p> <p>This data is a 2D cross-section from a 3D compressible hydrodynamics simulation (Hyburn / AMRex code) of a rapid decompression / shock tube experiment at Special Technologies Laboratory. The simulated shot is a pure argon gas decompression from 1000Psi to atmosphere. </p> <p>This data is used in figures 3 and 5 of the paper "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows".</p> <p>Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and <100 mg of diamond particles and observe sparks occurring below the sharp boundary of a condensation cloud. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. Simulation results agree closely with the experimentally observed Mach disk shock shape and height. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena.</p> <p><strong>Accessing Data</strong></p> <p>The data is saved as python numpy zipped archives numbered by the timestep in the simulation. Files starting with 'tube' contain data from inside the shock tube. Files starting with 'near_vent' contain data from the expansion chamber above the nozzle. All units are in SI.</p> <p>Each .npz file is an array file generated with python numpy.savez(). It can be opened with:</p> <p><em>import numpy as np</em></p> <p><em>data = np.load('<name>.npz')</em></p> <p>The data is an python dictionary. The dictionary keys can be displayed with:</p> <p><em>print(data.files)</em></p> <p>The numpy arrays can be accessed by keyname:</p> <p><em>print(data['keyname'])</em></p> <p>The key names correspond to physical quantities (density, temperature, etc.). All particle quantities are 0 as the simulation did not include particles.</p>
Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows
<div> <div><span># Data repository for the paper</span></div> <br> <div><span># </span><span>_Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows_</span></div> <br> <div><span>Corresponding author:</span></div> <div><span>Berend.van.Wachem@multiflow.org</span></div> <br> <div><span>This repository consists of the data and exemplary python scripts for the paper "Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows" by Christian Gorges, Victor Chéron, Anjali Chopra, Fabian Denner and Berend van Wachem. The data stored in this repository have the following data format:</span></div> <br> <div><span>-</span><span> .csv files consisting the raw data of the simulations used for the coefficient plots in the results' chapter of the paper</span></div> <div><span> </span></div> <div><span>-</span><span> .py files containing python scripts serving as examples on how to use and plot the raw data of the .csv files and the correlations</span></div> <br> <div><span>The main folders of this repository are named as the non-spherical particle shapes (Oblate, Prolate, Rod-like) and a folder with the data on which the correlations are based.</span></div> <br> <div><span>The folders named after the non-spherical particle shapes contain the raw simulation data. For instance, the Oblate folder contains the individual .csv files of all simulations of the oblate spheroid for all Reynolds numbers, Mach numbers, and angles of attack.</span></div> <br> <div><span>The folder Correlations/ consists of the temporally averaged drag, lift and torque coefficients, which are written in .csv files and stored in the folder ResultsCoefficients/, as well as Python scripts for plotting the correlations. </span></div> <br> <div><span>The naming style of the raw data files and the subfolders for each section is explained in the following:</span></div> <br> <div><span>The file names of the .csv files within the particle shape folders consist of the Reynolds number, followed by the Mach number and the angle of attack. For example "log_Re100M2_0_alpha_90.csv" consists of the data for a Reynolds number of 100, a Mach number of 2.0 and an angle of attack of 90 degrees. The content in the .csv files is given as: "%f,%f,%f,%f\n" which corresponds to "Physical time, drag coefficient, lift coefficient, torque coefficient". The first row in each file gives the headers of each column.</span></div> <br> <div><span>The .csv files in the folder Correlations/ResultsCoefficients/ are split per coefficient, shape, and particle Reynolds numbers, which can be identified by the name of the .csv file. For instance, the results obtained for the lift coefficient of</span></div> <div><span>the prolate spheroid particle for at a particle Reynolds numbers 100 for all orientation angles and Mach numbers are given in the file:</span></div> <div><span>"Prolate_100_CL.csv". In these files, the results are ordered per orientation angle (rows) and Mach</span></div> <div><span>number (column). </span></div> <br> <div><span>The python scripts have been tested with Python 3.11.5.</span></div> <br> <div><span>PlotCoefficients.py is an example python script to read the .csv files and plot the aerodynamic force coefficients as it is done in the results section of the paper.</span></div> <br> <div><span>The python scripts in the directory Correlations/ are split in three main functions in two files:</span></div> <div><span>-</span><span> Getter.py (read the .csv files storing the coefficients - separate functions</span></div> <div><span> for the drag, lift and torque coefficients)</span></div> <div><span>-</span><span> ManuscriptCorrelation.py with all the correlations derived in this work for an</span></div> <div><span> effective implementation in any solver, and a plotting function to have visual</span></div> <div><span> representation of the correlations.</span></div> <div><span>-</span><span> generalmain.py (calls Getter and Plotter)</span></div> <br> <div><span>The Getter is called from the generalmain.py file. (run python3 generalmain.py) so that all coefficients can be gathered in a 3D array.</span></div> <div><span>First dimension : Reynolds number</span></div> <div><span>Second dimension : Orientation angle</span></div> <div><span>Third dimension : Mach number</span></div> <div><span>The user just needs to give the absolute path to the folder ResultsCoefficients/.</span></div> <br> <div><span>This project has received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), grant number 447633787.</span></div> </div>
Development and analysis of entropy stable no-slip wall boundary conditions for the Eulerian model for viscous and heat conducting compressible flows
<p>The database used in the submission of "Development and analysis of entropy stable no-slip wall boundary conditions implementation of the Eulerian model for viscous and heat conducting compressible flows."</p> <p>Abstract: Nonlinear entropy stability analysis is used to derive entropy stable no-slip wall boundary conditions for the Eulerian model proposed by Svärd ( <em>Physica A: Statistical Mechanics and its Applications, 2018 </em>). and its spatial discretization based on entropy stable collocated discontinuous Galerkin operators with the summation-by-parts property for unstructured grids. A set of viscous test cases of increasing complexity are simulated using both the Eulerian and the classic compressible Navier–Stokes models. The numerical results obtained with the two models are compared, and differences and similarities are then highlighted.</p>
InSAR data for "Transcrustal compressible fluid flow explains the Altiplano-Puna deformation anomaly"
<p>InSAR data presented in the paper "Transcrustal compressible fluid flow explains the Altiplano-Puna deformation anomaly". See file "README" for detailed descriptions of each item.</p>
Pressure-based algorithm for compressible interfacial flows with acoustically-conservative interface discretisation (Supporting data)
<p>The dataset contains sample numerical results associated with the manuscript under the same title, "Pressure-based algorithm for compressible interfacial flows with acoustically-conservative interface discretisation", published in Journal of Computational Physics (2018), https://doi.org/10.1016/j.jcp.2018.04.028.</p>
Corrigendum of "Assessment of the Elliptic Blending RSM Turbulence Model on a Wind Turbine-Type Rotor Under Mildly Compressible Blade Tip Flow Regime" and updated dataset
<p>This data accompanies the paper "Assessment of the Elliptic Blending RSM Turbulence Model on a Wind Turbine-Type Rotor Under Mildly Compressible Blade Tip Flow Regime", published in the 18th Brazilian Congress of Thermal Sciences and Engineering (2020): <a href="http://www.sistema.abcm.org.br/articleFiles/download/28958">http://www.sistema.abcm.org.br/articleFiles/download/28958</a>. It includes the corrected integral load values described in the PDF document.</p>
Compressible flow over the SHM1 airfoil.
<p>Contours of the instantaneous magnitude of density gradient on the top visualize compressible flow over the SHM1 airfoil. The instantaneous density field and wall pressure coefficient distribution are shown in the bottom left and right frames, respectively. The time-averaged Cp is obtained between t=20 and t=60 with a sampling rate of 0.05 and is compared with experimental data Fujino et al. 2003. The NOHAP closure is used at the processor boundaries to evaluate derivatives in the convective flux terms. Solid black lines in the top and bottom left frames indicate the sub-domain boundary.</p>
Venous Blood Flow Velocity: Electrical Foot Stimulation Compared to Intermittent Pneumatic Compression of the Foot
ClinicalTrials.gov study NCT00114608. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Non-invasive Measurement of Microvascular Blood Flow During Mild External Compression of the Leg
ClinicalTrials.gov study NCT01804478. IPD Sharing: Not stated. Countries: 1. Publications: 23.
Vasculaire Compression System Increases Flow Velocity in the Femoral Vein
ClinicalTrials.gov study NCT01240330. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Neuromuscular Electrical Stimulation Versus Intermittent Pneumatic Compression for Blood Flow
ClinicalTrials.gov study NCT01862471. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of the OsciPulse Rapid Cycling Compression Device Effects on Venous Blood Flow
ClinicalTrials.gov study NCT05087108. IPD Sharing: YES. Countries: 1. Publications: 0.
A Comparison of Neuromuscular Electrical Stimulation and Intermittent Pneumatic Compression in Terms of Lower Limb Blood Flow
ClinicalTrials.gov study NCT01886612. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Rehabilitation Efficacy of Low-Load Blood Flow Restriction Training for Lateral Patellar Compression Syndrome
ClinicalTrials.gov study NCT06988917. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pneumatic Compression vs Blood Flow Restriction for Muscle Recovery
ClinicalTrials.gov study NCT06815367. IPD Sharing: NO. Countries: 1. Publications: 0.
A Comparison of the Effects of Neuromuscular Electrical Stimulation and Intermittent Pneumatic Compression on Blood Flow in the Lower Limb
ClinicalTrials.gov study NCT01894997. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Fetal Blood Flow Response to Partial Occlusion by External Compression
ClinicalTrials.gov study NCT01816737. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Collaborative Testing of Turbulence Models: Compressible Flow Cases from 1980-81 Data Library
This grouping contains the compressible-flow cases from the 1980-81 Data Library.
Collaborative Testing of Turbulence Models: More Recent Compressible Flow Cases
This grouping contains more recent compressible-flow cases.
Collaborative Testing of Turbulence Models: More Recent Compressible Flow Cases
This grouping contains more recent compressible-flow cases.
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