Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
64
datasets available to search
ShareScore release 0.9.0
Dataset results
64 results for “fracture modelling”
A Non-parametric Discrete Fracture Network Model
<p>Database used to build discrete fracture networks through a non-parametric approach from Gómez et al. 2023 (DOI: 10.1007/s00603-022-03194-y). The data is structured in twelve.csv files, each with an array of size n-by-3, containing the orientation of the discontinuity (dip direction and dip of the pole) and its pseudo-trace length in meters, with n being the number of fractures in each file.</p>
Fortran code used in 'A fractal model for effective excess charge density in variably saturated fractured rocks'
<p>This code is uploaded to support the research study 'A fractal model for effective excess charge density in variably saturated fractured rocks' by L. Guarracino and D. Jougnot (submitted to JGR: Solid Earth, 2021).</p> <p>Files:<br> a) Fortran source code (qvfrac.f) for estimating the effective excess charge density in fractured rocks. The calculation is based on model equations described in the research study.<br> b) Input data (network1.dat) to calculate the effective excess charge density for fracture network 1 described in Section 3 (Figure 5a).</p>
The Effect of Bone Graft Substitute in Healing Fractures with Bone Defects Through Examination of Alkaline Phosphatase and Radiology in the Murine Model (Rattus norvegicus) Wistar strain
<p>Raw data for manuscript with the title <strong>The Effect of Bone Graft Substitute in Healing Fractures with Bone Defects Through Examination of Alkaline Phosphatase and Radiology in the Murine Model (<em>Rattus norvegicus</em>) Wistar strain </strong></p>
The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model
<p>This data is the raw data for the manuscript with titled The Effect of Stromal Vascular Fraction (SVF) & Scaffolds Application on Fracture Healing with Bone Defect as Assessed Through Osteocalcin and Bone Morphogenetic Protein-2 (BMP-2) Biomarker Examination: Experimental Study on Murine Model.</p>
Dataset files for 'Tan et al., Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'
<p>These files are the data and result files for the manuscript entitled<strong> 'Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'</strong> by Tan et al., including</p> <p>catalog.dat : the seismic phase catalog used in seismic tomography</p> <p>station.dat : the station coordinates of the local seismic network</p> <p>relocation.dat : the earthquake relocations obtained by double-difference seismic tomography</p> <p>1-D Vs.xlsx : the 1-D Vs model in the shale gas field</p> <p>3-D Vp.dat: the 3-D Vp model obtained by DD seismic tomography</p> <p>3-D Vs.dat: the 3-D Vs model obtained by DD seismic tomography</p> <p>3-D VpVs.sgy: the 3-D Vp/Vs model obtained by DD seismic tomography (3-5 km)</p> <p>3-D pressure.sgy: the 3-D pore pressure field model obtained by focal mechanism tomography (3-5 km)</p>
Dataset files for 'Tan et al., Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'
<p>These files are the data and result files for the manuscript entitled<strong> 'Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'</strong> by Tan et al., including</p> <p><strong>station.dat</strong> : the station coordinates of the local seismic network (including the station ID, longitude, latitude, elevation(negative)/depth(positive), X, Y)</p> <p><strong>catalog.dat</strong> : the seismic phase catalog used in double-difference (DD) seismic tomography</p> <p><strong>relocation.dat </strong>: the earthquake relocations obtained by DD tomography</p> <p><strong>1-D Vs.xlsx</strong> : the 1-D Vs model in the shale gas field</p> <p><strong>3-D Vp.dat</strong>: the 3-D Vp model obtained by DD tomography</p> <p><strong>3-D Vs.dat</strong>: the 3-D Vs model obtained by DD tomography</p> <p><strong>3-D VpVs.sgy</strong>: the 3-D Vp/Vs model (interpolated, within 3-5 km)</p> <p><strong>3-D pressure.sgy</strong>: the 3-D pore pressure field model (interpolated, within 3-5 km)</p>
Data of "Ductile fracture of high entropy alloys: from the design of an experimental campaign to the development of a micromechanics-based modeling framework"
<p>Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data):</p> <p>title = "Ductile fracture of high entropy alloys: from the design of an experimental campaign to the development of a micromechanics-based modeling framework",<br> journal = "Engineering Fracture Mechanics",<br> year = "2022",<br> volume = "275",<br> pages = "108844 ",<br> doi = "https://doi.org/10.1016/j.engfracmech.2022.108844",<br> author = "Antoine Hilhorst, Julien Leclerc, Thomas Pardoen, Pascal J. Jacques, Ludovic Noels, Van-Dung Nguyen"</p> <p>New version following review.</p> <p> </p> <p> </p>
Codes, Catalogues and Data for "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"
<p><strong>Codes, Catalogues and Data available for:</strong> <br>"Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"</p> <p><strong>Catalog</strong> folder: Contains the CMM (beam-forming based) event catalogue as well as event and station information for the PNR-1z site.</p> <p><strong>Classification Test</strong> folder: Jupyter notebooks that run the classification tests and mseed input data of isolated phases (P, S, Noise).</p> <p><strong>DL_model_catalogues</strong> folder: Contains full catalogues for each DL phase picker (GPD, U-GPD, EQT and PhaseNet) and the LinMEF-filtered catalogues.</p> <p><strong>Model_run_docs</strong> folder: Util/core files for PhaseNet and EQTransformer to read data with different sampling frequencies (i.e., not 100 Hz)</p> <p><strong>Data</strong> folder: Contains one hour of continuous downhole data (11th December 2018, 9am-10am) from the PNR-1z dataset.</p>
Dataset - Permeability and viscoelastic fracture of a model tumor under interstitial flow
<p>This includes all the experimental data which are presented in the paper titled "Permeability and viscoelastic fracture of a model tumor under interstitial flow", Soft Matter, 2018 by Quang D. Tran, Marcos and David Gonzalez-Rodriguez.</p> <p>In each data folder, we have attached a Readme file to instruct readers how to analyze or compute our data.</p>
A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture
<p><strong>Abstract:</strong></p> <p>(from [1])</p> <blockquote> <p>For the smeared approximation of a discrete crack, phase-field fracture simulations of brittle materials require suitable finite element meshes in regions where crack propagation is expected to get an accurate resolution of the phase-field function. The intuitive option is to pre-refine the mesh in regions of the expected crack paths. However, this could lead to very computationally intensive simulations due to the high number of elements. Alternatively, adaptive spatial refinement of the finite element mesh is utilized based on appropriate error indicators to obtain the required accuracy in the areas of crack propagation. Different error indicators can be used: the most common one for phase-field fracture simulations is the threshold-based approach, in which elements are refined depending on the value of the phase-field function. Alternatively, the Kelly error indicator can be used as a criterion for spatial adaptivity. It considers the jumps in the gradients of the phase-field function between the elements. We additionally introduce here an error indicator based on configurational forces, that depend on the Eshelby stress tensor. For mode I loading in linear elastic fracture mechanics, the configurational forces have a close connection to the <span class="math-tex">\(\mathscr{J}\)</span>-Integral and the critical fracture energy <span class="math-tex">\(\mathrm{G}_\mathrm{c}\)</span> , respectively. Therefore, a suitable norm of the configurational forces is introduced as an error indicator here. These three error indicators are introduced and compared to each other in terms of accuracy and efficiency by means of numerical examples for crack growth in the single edge notched shear test.</p> </blockquote> <p><strong>Contact:</strong></p> <p>Maurice Rohracker</p> <p>Institute of Applied Mechanics</p> <p>Friedrich-Alexander-Universität Erlangen-Nürnberg</p> <p>Egerlandstr. 5</p> <p>91058 Erlangen</p> <p><strong>Software:</strong></p> <p>All phase-field fracture simulations were performed with <em>deal.II</em> [2], version 9.2.0, on the HPC cluster <em>Meggie</em> of NHR@FAU. The authors gratefully acknowledge the scientific support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). The hardware is funded by the German Research Foundation (DFG).</p> <p><strong>License:</strong></p> <p>Creative Commons Attribution 4.0 International</p> <p><strong>Context:</strong></p> <p>Dataset supplementing preprint:</p> <p>[1] M.Rohracker, P.Kumar, J.Mergheim, "A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture", Forces in Mechanics, 2022, <a href="https://doi.org/10.1016/j.finmec.2022.100157">10.1016/j.finmec.2022.100157</a>.</p> <p>This dataset contains the complete results presented in [1], which include global variables, field variables, and meshes.</p> <p><strong>File structure:</strong></p> <p>The file structure is explained in more detail in the shipped <em>README.md</em> in the dataset folder.</p> <p><strong>References:</strong></p> <p>[1] M.Rohracker, P.Kumar, J.Mergheim, "A comparative assessment of different adaptive spatial refinement strategies in phase-field fracture models for brittle fracture", Forces in Mechanics, 2022, <a href="https://doi.org/10.1016/j.finmec.2022.100157">10.1016/j.finmec.2022.100157</a>.</p> <p>[2] D. Arndt, W. Bangerth, B. Blais, T. C. Clevenger, M. Fehling, A. V. Grayver, T. Heister, L. Heltai, M. Kronbichler, M. Maier, P. Munch, J.-P. Pelteret, R. Rastak, I. Thomas, B. Turcksin, Z. Wang, D. Wells, <strong>The deal.II Library, Version 9.2</strong> Journal of Numerical Mathematics, vol. 28, p. 131-146, 2020.</p>
Validation of Fracture Caging to Contain Hydraulic Fractures: Timeseries, Videos, and Model Script
<p>The data file include an Excel spreadsheet and two videos for each experimental test.</p> <p>You can start with reading the ReadMeFirst.txt file to understand the whole structure of the dataset.</p> <p>The caging_model.txt file includes python codes to calculate critical flow rates and uncaged fracture radius according to the theory that the authors developed and will be published soon.</p>
Dataset: High-fidelity experimental model verification for flow in fractured porous media
<p>The dataset consists of five image series of tracer experiments in fractured porous media. The images have been taken using PET imaging and are available in DICOM format. Overall, three fractured geometries have been considered, called fractip-a, fractip-b, and fractip-e. Different boundary conditions have been used, generating in total four experiments. In addition, images of simple water displacement experiments in an intact core (fractip-j) are provided, useful for extracting macroscopic hydraulic properties of the core material. All experiments are based on water displacement and use 18F-FDG tracer for PET tracking. The available DICOM images are reconstructed using 1 min x 0.4mm space-time voxels. </p> <p>A related data analysis based on the Darcy Scale Image Analysis toolbox DarSIA is available at 10.5281/zenodo.10410227.</p>
Superalloys fracture process inference based on overlap analysis of 3D models
<h2>Datasets and code utilized in the paper "Superalloys fracture process inference based on overlap analysis of 3D models"</h2> <h2>Code and data description</h2> <h3>Data for 3D reconstruction</h3> <ul> <li>Original SEM images of Fracture A - Fracture D obtained through the collection method in the paper.</li> </ul> <h3>Data for scale calibration</h3> <ul> <li>Original SEM images sequences of marked points 'dot1' and 'dot2' of Fracture A - Fracture D.</li> </ul> <h3>Sharpness score calculation</h3> <ul> <li>'shapeness.m' : Calculating image sharpness using normalized variance equations.</li> <li>'focus_A_data' - 'focus_D_data' : Sharpness scores for all images in the image sequences and their corresponding sample stage coordinates.</li> </ul> <h3>3D fracture models</h3> <ul> <li>Scale calibrated 3D models of Fracture A - Fracture D.</li> </ul> <h3>Description of internal cracks</h3> <ul> <li>Original images and EDS results for an illustration of the regions of internal crack generation in Fracture A</li> </ul> <p> </p> <p> </p>
Osteolitic vs Osteoblastic metastatic lesion: Computational modeling of fracture risk in the human vertebra after screws fixation procedure
<p>Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screwfixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing the surgical treatment. This work proposes an image-basedfinite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for the metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response, and suggest better account these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for irregular shape of the overall metastatic tissue has a not significant effect on fracture load of vertebra macroscopically. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining the fracture risk. The proposed computational approach moves towards defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.</p>
Supporting Information: Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography
<p>Supporting Information README</p> <p>2018-Jan-17</p> <p>"Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography"</p> <p>Yanhui Dong, Yunmei Fu, Tian-Chyi Jim Yeh, Yu-Li Wang, Yuanyuan Zha, Liheng Wang, Yonghong Hao</p> <p>This file contains the supplementary data for this manuscript, including the locations and properties of fracture networks, the locations of observation wells and validation wells, the water head used in inverse model and validation tests, as well as the executive file used in the inverse model.</p>
Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years
<p>Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years</p>
Pore-scale modeling and investigation on thermal-hydro-mechanical-chemical coupled rock dissolution and fracturing process
<p>Attached files include the executable file of the pore-scale multi-field coupled LBM-DEM program written by C language, post-processing programs to record the reactive surface area and reactive temperature written by MATLAB, and the simulation results of rock acid fracturing with 20MPa at the injection hole.</p>
Numerical results data of 'Impact of Injection Pressure and Polyaxial Stress on Hydraulic Fracture Propagation and Permeability Evolution in Greywacke: Insights from Discrete Element Models of a Laboratory Test'
<p>Numerical results data of '<strong>Impact of Injection Pressure and Polyaxial Stress on Hydraulic Fracture Propagation and Permeability Evolution in Greywacke: Insights from Discrete Element Models of a Laboratory Test</strong>'</p>
2D Abaqus finite element model of the climbing drum peel test for fracture toughness and mode mixity determination
<p>Abaqus finite element model files published in connection with the below article:</p> <p>Jespersen, K.M and Toftegaard, H. L. (2023), Mode mixity for the fracture toughness obtained by climbing drum peel tests. Risø symposium 2023. <a href="https://doi.org/10.1088/1757-899X/1293/1/012032">doi.org/10.1088/1757-899X/1293/1/012032</a></p> <p>Uploads include the overall .cae file for Abaqus 2022 and the corresponding .odb (result) and .inp files. Videos showing the deformation of the model are included for the "CDP_mat-GFRP_cracklength-a10_BC-gripped" case.</p>
Data for: The biomechanics of tooth strength: testing the utility of simple models for predicting fracture in geometrically complex teeth
<p>Teeth must fracture foods while avoiding being fractured themselves. This study evaluated dome biomechanical models used to describe tooth strength. Finite element analysis (FEA) tested whether the predictions of the dome models applied to the complex geometry of an actual tooth. A finite element model (FEM) was built from microCT scans of a human M3. The FEA included three loading regimes simulating contact between 1) a hard object and a single cusp tip, 2) a hard object and all major cusp tips, and 3) a soft object and the entire occlusal basin. Our results corroborate the dome models with respect to the distribution and orientation of tensile stresses, but document heterogeneity of stress orientation across the lateral enamel. This implies that high stresses might not cause fractures to fully propagate between cusp tip and cervix under certain loading conditions. The crown is most at risk of failing during hard object biting on a single cusp. Geometrically simple biomechanical models are valuable tools for understanding tooth function but do not fully capture aspects of biomechanical performance in actual teeth whose complex geometries may reflect adaptations for strength.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.