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Dataset results
17 results for “Mechanical deformation”
Using coupled micropillar compression and micro-Laue diffraction to investigate deformation mechanisms in a complex metallic alloy Al13Co4
<p>In this investigation, we have used <em>in-situ</em> micro-Laue diffraction combined with micropillar compression of focused ion beam milled Al<sub>13</sub>Co<sub>4</sub> complex metallic alloy to study the evolution of deformation in Al<sub>13</sub>Co<sub>4</sub>. Streaking of the Laue spots showed that the onset of plastic flow occured at stresses as low as 0.8 GPa, although macroscopic yield only becomes apparent at 2 GPa. The measured misorientations, obtained from peak splitting, enabled the geometrically necessary dislocation density to be estimated as 1.1 x 10<sup>13</sup> m<sup>-2</sup>.</p>
Data for "High-temperature low-cycle fatigue and fatigue-creep behaviour of Inconel 718 superalloy: Damage and deformation mechanisms"
<p>Title of dataset: Data for "High-temperature low-cycle fatigue and fatigue-creep behaviour of Inconel 718 superalloy: Damage and deformation mechanisms"<br>Name/institution/contact information: Dr. Michal Bartošák, Czech Technical University in Prague - Faculty of Mechanical Engineering, email: michal.bartosak@fs.cvut.cz<br>Date of data collection: The data were collected from the start of 2021 to the end of 2023.<br>File name structure: The data within the folder "SEM" are images of microstructural observations of selected specimens. The data within the folder "FATIGUE_LIFE" include the fatigue lifetimes, as well as the stress and strain amplitudes at mid-life, of all investigated specimens.</p> <p>See https://doi.org/10.1016/j.ijfatigue.2024.108369 for the associated article and a detailed description of the methods.</p>
Mechanical and hydraulic transport properties of transverse-isotropic Gneiss deformed under deep reservoir stress and pressure conditions.
<p>"This is the ReadMe file corresponding to the study entitled: "Mechanical and hydraulic transport properties of transverse-isotropic<br> Gneiss deformed under deep reservoir stress and pressure conditions" <br> <br> "By M. Acosta, & M. Violay." <br> <br> This study has been published in the International Journal of Rock Mechanics and Mining Sciences in June 2020. <br> https://doi.org/10.1016/j.ijrmms.2020.104235<br> <br> This Read-Me file has been last edited on 2020-06-31 <br> <br> This readme file describes the data repository and supplementary files accompanying the above publication. <br> For any further queries please contact mateo.acosta@epfl.ch <br> <br> The following files are included: <br> <br> --- Regarding Figure 3. <br> <br> "1) ""Acosta_et_al_2020_Figure3Data.xlsx"" " <br> This is the processed data from the experiments described in Figure1 of the article. <br> "In this .xlsx File, each sheet corresponds to one figure panel as follows: " <br> <br> Fig.3: One experiment example<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>--- Regarding Figure 4. <br> <br> "1) ""Acosta_et_al_2020_Figure4Data.xlsx"" " <br> This is the processed data from the experiments described in Figure1 of the article. <br> "In this .xlsx File, each sheet corresponds to one figure panel as follows: " <br> <br> Fig.4a&g: Beta=0deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4b&h: Beta=30deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4c&i: Beta=45deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4d&j: Beta=60deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4e&k: Beta=90deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4f&l: LPG<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>--- Regarding all other Figures, the tables provided in the article allow reproduction of these.</p> <p> </p>
Casting voids in nickel superalloy and the mechanical behaviour under room temperature tensile deformation
<p>This repository contains the original X-ray tomography data presented in the publication 'Casting voids in nickel superalloy and the mechanical behaviour under room temperature tensile deformation'.</p> <p>The XCT data were collected using Zeiss Xradia Versa 520 instrument from Henry Moseley X-ray Imaging facility at the University of Manchester. Access to the instrument was granted by Henry Royce Institute through PhD access funding scheme for Zhuocheng Xu. Data to produce Figure8 and Figure9 are also uploaded.</p>
Data presented in Crustal structure and anisotropy measured by CHINArray and implications for complicated deformation mechanisms beneath the eastern Tibetan margin
<p>The dataset includes the raw waveforms and receiver functions presented in the paper Crustal structure and anisotropy measured by CHINArray and implications for complicated deformation mechanisms beneath the eastern Tibetan margin, submitted to JGR Solid Earth.</p><p>Contact: Zengsijia@cug.edu.cn</p><p> </p>
Mechanical Metamaterial: Square Array of Circular Holes Under Deformation
<p>This repository contains data for a research project involving graph neural networks (GNNs) applied to mechanical metamaterials and their deformations. </p> <p>The mechanical metamaterials of interest consist of a flexible rubber-like material with a square grid of almost-circular holes in it, of various diameters. The holes are not quite circular, because they were made slightly elliptic to avoid the bifurcation point.</p> <p>This data was used to obtain the results in the paper 'Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials'.</p> <p>The data includes PyTorch Geometric Graph objects, raw data from MATLAB simulations, and files describing the finite element mesh. The Jupyter notebook 'data_create_graphs.ipynb' in the GitHub repository can be used to turn the raw data and mesh information into the graph objects.</p> <p>GitHub repository with the code: <a title="https://github.com/FHendriks11/SimEGNN" href="https://github.com/FHendriks11/SimEGNN">https://github.com/FHendriks11/SimEGNN</a></p> <p>Link to the corresponding paper <em>Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials</em>: <a href="https://www.sciencedirect.com/science/article/pii/S0045782525001392">https://www.sciencedirect.com/science/article/pii/S0045782525001392</a> (also on ArXiv: <a title="https://arxiv.org/abs/2404.17365" href="https://arxiv.org/abs/2404.17365">https://arxiv.org/abs/2404.17365</a>)</p> <p>The .pkl files are pickle files and can be opened in Python using the standard pickle library. The mesh files, which have the extension .mat, are MatLab files and can be opened either in MatLab or in Python using scipy.io.loadmat from the scipy library.</p>
Studying gastrulation by invagination: the bending of a cell sheet by mechanical cell properties using 3D deformable cell based simulations
<p>This dataset contains the scripts and end results of invagination simulation experiments.<br>The data are the results of a 3D cell based model that was used to investigate invagination: the bending of a cell sheet, and uses cell-cell adhesion, apical constriction, cell volume conservation, collision detection and handeling.</p>
Internal defect database of mechanically deformed ferritic steel via X-ray computed tomography
Open the record for dataset details and reuse information.
Experimental data used in the article entitled "Exploring microstructure refinement and deformation mechanisms in severely deformed LPBF AlSi10Mg alloy"
Open the record for dataset details and reuse information.
Dynamic Evaluation of Ankle Joint and Muscle Mechanics in Children With Spastic Equinus Deformity Due to Cerebral Palsy
ClinicalTrials.gov study NCT02814786. IPD Sharing: NO. Countries: 1. Publications: 1.
Data used in the figures of "Aseismic deformation during the 2014 Mw 5.2 Karonga earthquake, Malawi from InSAR and earthquake source mechanisms"
<p>Data used in Figures 2, 4, and SI3 of the paper "Aseismic deformation during the 2014 Mw 5.2 Karonga earthquake, Malawi from InSAR and earthquake source mechanisms."</p>
Dataset for "Reconstruction of Excitation Waves from Mechanical Deformation using Physics-Informed Neural Networks"
<p>Archive consisting of the synthetic datasets used in "Reconstruction of Excitation Waves from Mechanical Deformation using Physics-Informed Neural Networks" (<a title="https://doi.org/10.1038/s41598-024-67597-3" href="https://doi.org/10.1038/s41598-024-67597-3" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1038/s41598-024-67597-3</span></a>) as well as the results after PINN optimization. Datasets include the electrical simulation data, generated active tension and resulting deformation. The PINN_results.zip file covers all results discussed in the paper. Short txt files give more information on the data format. The code used to create the synthetic dataset, construct and optimize the PINNs, and generate the figures from the paper can be found on <a href="https://gitlab.com/heartkor/scripts-2d-deformation-pinn">https://gitlab.com/heartkor/scripts-2d-deformation-pinn</a>.</p>
Investigating multi-physical process and deformation mechanism of reservoir landslide using integrated multi-source monitoring
<p>Data to support this study are available.</p>
Data for Stress fields around magma chambers influenced by elastic thermo-mechanical deformation: implications for forecasting chamber failure
<p>COMSOL model outputs as .txt files. as supplement to the paper: Stress fields around magma chambers influenced by elastic thermo-mechanical deformation: implications for forecasting chamber failure which has been submitted for publication in Scientific Reports. </p> <p> </p> <p> </p>
Multimodal Bio-mechanical Analysis of Adult Spinal Deformity With Sagittal Plane Misalignment
ClinicalTrials.gov study NCT04812730. IPD Sharing: NO. Countries: 1. Publications: 0.
Contributions of microbiome and mechanical deformation to intestinal bacterial overgrowth and inflammation in a human gut-on-a-chip
GEO Series GSE65790. Homo sapiens. 6 samples. Type: Expression profiling by array.
DRM2 mediates CHH DNA methylation via a substrate deformation mechanism
GEO Series GSE146700. Arabidopsis thaliana. 6 samples. Type: Methylation profiling by high throughput sequencing.
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.