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207 results for “friction”
On the Moreau–Jean scheme with the Frémond impact law: energy conservation and dissipation properties for elastodynamics with contact, impact and friction — data
<p>This deposit contains the data output of the systems described in <a href="https://hal.science/hal-04230941">On the Moreau–Jean scheme with the Frémond impact law. Energy conservation and dissipation properties for elastodynamics with contact impact and friction.</a> The codes that generated this data are available in another <a href="../records/10953181">deposit</a> archived on Zenodo, as well as in a GitHub repository archived on <a href="https://archive.softwareheritage.org/swh:1:dir:33ff6d960b70505c7939c0ce21c039cabbe1351c;origin=https://github.com/nickcollins-craft/On-the-Moreau-Jean-scheme-with-the-Fremond-impact-law;visit=swh:1:snp:72aede3d3a464732a36ef79c20ef07eebd1f9918;anchor=swh:1:rev:b63b68c25e72d23d7d9ee30225165fa0ebffb3c2">Software Heritage</a>, which is the preferred method of obtaining the codes. Two of the files in this deposit ("deformed_sliding_block_mesh.png" and "sliding_block_mesh.png") are required for one of the codes in the code deposit to run successfully ("block_mesh_plot.py", with the files assumed to be located in the folder specified in the data_folder variable of the file "path_file.py"), but the deposits are otherwise independent.</p>
Supporting data "Scaling theory for the statistics of slip at frictional interfaces"
<p>Principle data supporting "Scaling theory for the statistics of slip at frictional interfaces"</p> <p>T. W. J. de Geus and M. Wyart (2022), <em>Phys. Rev. E</em>, 106(6):065001.</p> <ul> <li>See code at <a href="../doi/10.5281/zenodo.10723197">doi: 10.5281/zenodo.10723197</a> (and its documentation) for workflow, detailed information of the data, and further dependencies. </li> <li>The files <code>N=*_Run*.zip</code> contain fully restorable events for event-driven athermal quasi-static shear. Sequentually numbered files contain different parts of a single dataset.</li> <li>The file <code>summary.zip</code> contains an extract of the key variables of these runs, and of triggers at different stresses. Finally, it contains "flow" data acquired by driving at finite rate. </li> <li>The files <code>N=3^6x4_Trigger_EnsemblePack.zip</code> contain fully restorable triggers at different stresses in the largest system. The sequentially numbered files correspond to one dataset split in different<em> </em><code>.h5</code> files.</li> <li>Highly specific (and poorly documentated) plotting functions are available upon request.</li> </ul>
Colebrook-White friction factor data
<p>The Colebrook-White equation is a fundamental formula in fluid mechanics, widely used to determine the friction factor in turbulent flow through pipes. It is crucial for calculating head losses in pipelines and for the design and optimization of hydraulic systems. In this dataset, the friction factor (f) is obtained via numerical solution using the Newton-Raphson method, with a truncation accuracy of 1e-6.</p> <p>The first and second columns of the provided dataset pertain to the Reynolds number (Re) and relative roughness (ε/D) variables, respectively. The data were generated across specified ranges [4500-2250000] with constant step of 4500 for Re and [0.00005, 0.0005, 0.005, 0.05, and 0.5] for ε/D. The third column presents of the f values calculated using the Colebrook-White equation, which is given as:</p> <div> </div> <div>1/(\sqrt(f)) = -2*log((\epsilon/D)/3.7 + 2.51/(Re*\sqrt(f)))</div> <div> </div> <div> </div> <div>This dataset has multiple applications: it facilitates evaluating empirical formulas approximating the Colebrook-White equation and provides a valuable foundation for developing machine learning models to accurately predict the friction factor. Beyond aiding hydraulic system design, this dataset is a useful resource for researchers and engineers aiming to optimize pipeline flow, model turbulent pipe flow behavior, and advance computational methods in fluid dynamics.</div>
Single molecule nanotribology: understanding friction and adhesion at a single molecule level
<p>Data presented in the annual conference SAOG2019 (Surface Science and Thin Films Community of Switzerland 2019). </p> <p>Here we discuss the effect of molecular vibrations on its friction properties. This is intended to provide an overview of the results published in the following peer-reviewed freely available papers:<br> Nature Communications 10, 685 (2019). [DOI:10.1038/s41467-019-08531-4 ]<br> Nano Lett. 20, 652 (2020). [DOI: 10.1021/acs.nanolett.9b04418]<br> (Please cite them, if you found this information useful.)</p> <p> </p>
Machine learning predicts earthquakes in the continuum model of a rate-and-state fault with frictional heterogeneities
<p>Numerical data used to make Figures in the manuscript entitled "Machine learning predicts earthquakes in the continuum model of a rate-and-state fault with frictional heterogeneities". We provide the data to create Figures 1 to 4 from the main text and Figures S1 to S9 from the supplementary information. We also provide Python scripts to plot them.</p>
Fracture Data Supporting: 'The 2024 Mw4.8 New Jersey Intraplate Earthquake: Preferential Rupture of an Immature Fault in Frictionally Unstable Basement Rocks'
<p>The spreadsheets contain fracture and paleoslip surface datasets measured across the epicentral region of the April 5, 2024 Mw4.8 New Jersey earthquake. Datasets contain coordinates of outcrops, strike, dip, and trend/plunge or rake (where slickenlines are observed).</p>
Effects of Periodic Normal Stress Oscillations on Frictional Properties of Simulated Natural Fault Gouges under In Situ P-T Conditions
<p>Files named by in a format of "Uxxx_xx_xxMPa_xxC" refer to the original mechanical data recorded during experiment.</p> <p>The compressed package includes the files to perform numerical modeling, modeling results and the experimental data for comparison. To replicate the numerical modeling, readers can open the COMSOL project file (".mph" file) using COMSOL software (version >5.4) then input the parameters for the boundary conditions, such as the temperature, load-point velocity, oscillation amplitude and frequency. </p>
Data for: Changes in Processing Characteristics and Microstructural Evolution during Friction Extrusion of Aluminum
<p>This dataset contains measurement data, micrographs and machine logs for the publication "Changes in Processing Characteristics and Microstructural Evolution during Friction Extrusion of Aluminum".</p>
Data from: Combined experimental-numerical analysis of the temperature evolution and distribution during friction surfacing
<p>This dataset contains the data for the publication "Combined experimental-numerical analysis of the temperature evolution and distribution during friction surfacing".</p>
Data for: Comparison of Friction Extrusion Processing from Bulk and Chips of Aluminum-Copper Alloys
<p>This dataset contains measurement data, machine logs as well as microstructure and overview images for the publication "Comparison of Friction Extrusion Processing from Bulk and Chips of Aluminum-Copper Alloys".</p>
Data Set for "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs" I: Lesser Antilles Volcanic Arc
<p>Data set for the 48 friction experiments performed for gouge samples (altered andesitic rocks) from the Lesser Antilles used in the manuscript, "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs". This data set can be used in combination with the data set for the Cascades used in the same manuscript (doi:10.5281/zenodo.10964936). This large combined data set (of 108 frictional experiments) represents a unique opportunity to systematically study frictional behaviour in the framework of rate and state. All samples are tested in wet and dry conditions at 10, 30, and 50 MPa with velocity steps and slide-hold-slides. These two data sets have the further advantage of being performed with exactly the same protocol (same run in, same initial gouge thickness, same velocity steps, same hold periods), in the same machine, by the same operator (or by an operator who was trained and supervised by the original operator). </p>
Evaluation of DEM simulations measuring internal friction and particle movement
<p>The data contains evaluated data from particle motion simulations during the internal friction test using a rotary shear cell. These are several models with different input parameters. The data includes a version of a scientific article on the subject.</p>
Process Simulation of Friction Extrusion of Aluminum alloys
<p>The friction extrusion process (FEP) is a solid-state material processing technique in which a translating extrusion die is pressed against a billet/feedstock material in a rotating extrusion container to produce an extruded rod or wire. A key aspect of FEP is the non-equilibrium thermo-mechanical condition created at the contact region between the die and billet, leading to a possibly improved microstructure. Numerical simulations of FEP are highly complex due to contact between the tool and the workpiece, and interplay between thermo-mechanical conditions and the present severe plastic deformation. In the present work, a three-dimensional finite element model is developed to study the material flow behavior for different extrusion ratios for a 60° die angle during friction extrusion. The developed model is numerically validated against experimental data. The spatial temperature, strain and velocity distributions illustrate the effect of extrusion ratio on the deformation characteristics of the extruded aluminum alloys, thereby assisting in experimental microstructure interpretation.</p>
Frictional fluid instabilities shaped by viscous forces
<p>Original images constituting the data set used for the phase diagrams in the paper </p> <p>Frictional fluid instabilities shaped by viscous forces</p> <p>Zhang D, Campbell JM, Eriksen J, Flekkoy EG, Maloy KJ, MacMinn CW and Sandnes B.</p> <p>Accepted for publication in Nature Communications</p> <p> </p> <p>The experiments involved injection of a viscous mixture (water/glycerol) into dry hydrophobic grains in a Hele-Shaw cell. The cell gap was 0.9 mm, and the outer radius shown in the images is 13.4 cm. The experimental variables were: granular material filling fraction (phi), injection rate (volumetric) and viscosity of the injected fluid. The images correspond to Fig. 2, Fig. 8 and Fig. 9 in the paper, with simulation output corresponding to the experiments included in Fig. 2 and 8.</p> <p> </p> <p>The File names include the experimental/simulation variables. For example:</p> <p>Fig2_exp_phi042_rate1_visc1.jpg</p> <p>- Belongs to Fig 2 in the paper</p> <p>- Is an experimental image</p> <p>- The filling fraction was phi = 0.42</p> <p>- The injection rate was 1 mL/min</p> <p>The viscosity of the injected fluid was 1 mPs s (i.e. water)</p> <p> </p> <p>The experiments and simulations are described in detail in the Zhang et al. paper.</p> <p> </p>
Friction extrusion processing of aluminum powders: microstructure homogeneity and mechanical properties
<p>This dataset contains the data from the publication</p> <p><strong>"Friction extrusion processing of aluminum powders: microstructure homogeneity and mechanical properties"</strong></p> <p> </p> <p> </p>
Data for: Grain structure evolution ahead of the die during friction extrusion of AA2024
<p>Friction extrusion (FE) is a thermo-mechanical process using a rotating die to produce fully consolidated extrudates in different shapes, e.g. wires, rods and tubes. FE utilizes a non-consumable die to plastically deform material and to generate heat by friction due to the relative rotation between the die and feedstock. In this study, the FE process is applied to extrude the Al-Cu alloy AA2024 using a 90 degree scroll-featured die. The grain structure evolution induced by thermo-mechanical processing is analyzed, in particular using the electron backscatter diffraction technique. Introduction of severe plastic deformation and high temperature exposure induced by the die movement in radial and longitudinal directions relative to the materials enable grain refinement induced by dynamic recrystallization. The grain structure formation prior to deformation through the die orifice plays an essential role to obtain fully-recrystallized homogeneous wire.</p>
Data for: Microstructure evolution and texture development during production of homogeneous fine-grained aluminum wire by friction extrusion
<p>This dataset contains the data for paper “Microstructure evolution and texture development during production of homogeneous fine-grained aluminum wire by friction extrusion” published in Materials Characterization.</p> <p>Abstract: This study aims to understand the microstructure evolution and texture development during friction extrusion of aluminium alloys, focusing on AA7075 as exemplary alloy system. Electron backscatter diffraction technique has been employed to obtain crystallographic data from various regions in front of the die and in the wire. It can be deduced that the combination of continuous dynamic recrystallization and geometric dynamic recrystallization mainly govern the formation of a fine-grained structure, however discontinuous dynamic recrystallization may also play a role at high temperature. The global shear deformation during the process was characterized as a simple shear deformation with dominant <span class="math-tex">\(B/\overline{B}\)</span> simple shear texture components. The material flow is mainly driven by the in-plane shear strain and the extrusion-induced shear strain that are determined by die rotational speed and extrusion force, respectively. The in-plane shear strain strongly affects the formation of a homogeneous fine-grained microstructure in the aluminum wire. In this regard, a novel material flow model for friction extrusion has been proposed.</p>
Data for: Processability of Mg-Gd powder via friction extrusion
<p>This dataset contains measurement data, machine logs as well as microstructure and overview images for the publication "Processability of Mg-Gd powder via friction extrusion".</p>
Dataset - Learning to Measure Static Friction Coefficient in Cloth Contact
<p>Dataset for: Learning to Measure the Static Friction Coefficient in Cloth Contact</p>
Cyclic friction tests of ballast stones interfaces under varying vertical load
<p>This data set contains results from cyclic ballast-ballast friction tests under varying load.<br> Two types of railway ballast were tested: “Calcite” (stems from Croatia) and “Kieselkalk”, also known as Helvetic Siliceous Limestone, (stems from Switzerland).<br> In each friction test, a stone with a distictive tip was sheared over a flat (stone) surface under a given normal load.<br> The applied normal load was increased from 10 N to 100 N in several load steps in each test.<br> For each applied load, a given number of cycles were conducted.<br> In total, 7 tests were conducted for Calcite and 8 for Kieselkalk.<br> The test results are provided in .csv files and contain (among other values) the measured coefficient of friction (CoF) values.<br> The test were organised in three test series. In all conducted test, the angular tip stones were 3D scanned before and after the tests.<br> Test series 1 and 2, involved a 3D scanning before each load increase.<br> The data of these tip scans are also provided (in .ply file format). From the 3D scans the contact areas were calculated (using an alogorithm described in the paper below).<br> A detailed description of the tests and discussion of measurements can be found in:</p> <p>B. Suhr, T.A. Butcher, R. Lewis, K. Six<br> "Friction and wear in railway ballast stone interfaces"<br> Tribology International 2020<br> <a href="https://doi.org/10.1016/j.triboint.2020.106498">https://doi.org/10.1016/j.triboint.2020.106498</a></p> <p><br> This data set is organised as follows:</p> <p>Folder FrictionTests: contains measured data from friction tests in .csv file format.<br> Folder TipScans: contains data from scans of ballast tip stones before/in between/after cyclic friction tests. Meshes are provided in .ply file format.<br> Folder TipScans: contains two files with detail information on the contact area calculation (for the two types of ballast tested)</p> <p>Each folder contains three subfolder: Series1, Series2, Series3, which contains the data of the corresponding test series,<br> see paper above for a more detailed description.</p> <p>Check the README.txt file for more information on the technical aspects</p> <p> </p> <p>The investigated ballast types are the same, as previously investigated</p> <p>1) in uniaxial compression tests and direct shear tests:<br> Suhr, Bettina, & Six, Klaus. (2018).<br> "Compression tests and direct shear test of two types of railway ballast [Data set]"<br> Zenodo. http://doi.org/10.5281/zenodo.1423742</p> <p>2) in shape analysis including 3D scans:<br> Suhr, Bettina, Six, Klaus, Skipper, William A., & Lewis, Roger. (2020).<br> "3D scans of two types of railway ballast including shape analysis information [Data set]".<br> Zenodo. http://doi.org/10.5281/zenodo.3689592</p> <p> </p>
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