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345 results for “cracking”
Dataset for Brittle Creep and Brittle Failure of Rocks: a reformulation of the wing crack model
<p>brittleCreepScript.nb - Commented Mathematica Notebook script containing the steps needed to plot Figure 8</p> <p>Mechanical_data.mat - mechanical data from tertiary creep of Etna basalt (Mansbach 2022), Iceland basalt (Xing et al. 2022), Inada Granite and Thala limestone (Brantut et al. 2013), Darley Dale sandstone and Etna Basalt (Heap 2009) and glass (Mallet et al. 2015) experiments.</p> <p>Data structure: First column - time (min), second column - axial strain (%), third column (where available) - differential stress (MPa).</p> <p>data_plotting.m - Matlab script for plotting all strain - time data found in Mechanical_data.mat.</p> <p>References:<br> Xing, T., H.O. Ghaffari, U. Mok and M. Pec (2022), Creep of CarbFix basalt: influence of rock-fluid interaction, Solid Earth, 13, 137–160, https://doi.org/10.5194/se-13-137-2022</p> <p>Mansbach, Elias. 2022. “Effect of Carbon Sequestration and Reservoir Conditions on Brittle Creep in Etna Basalt.” Thesis Commons. Doi: 10.31237/osf.io/64gxc<br> <br> Brantut, N., M.J. Heap, P.G. Meredith and P. Baud (2013), Time-dependent cracking and brittle creep in crustal rocks: a review, J. Struct. Geol., 52, 17-43.</p> <p>Heap, M.J. (2009), Creep: Time-dependent Brittle Deformation in Rock, PhD Thesis, University College London, pp. 399.</p>
Stress effects on wave velocities of rocks: Contribution of crack closure, squirt flow and acoustoelasticity
<p>These data are the P- and S-wave waveform data obtained by Ba et al. (2019-2022) through ultrasonic experimental measurements on rock samples at different pressures.</p> <p>In the package of data, each folder of Sample A1, Sample A2, Sample A3, Sample A4, Sample A5, Sample A6, Sample B1, Sample B2, Sample B3, Sample B4, Sample B5, and Sample B6 indicates sample number. For each sample with different pore fluids, waveforms measured at different pressures are saved as different TXT files. For the title of each TXT file, it includes the sample number, saturation condition, temperature, differential pressure value and wave type. For instance, “Sample A1_fullwater_20℃_15MPa_Pwave” denotes that P-wave waveform of sample A1 with the full water saturation is measured at 20℃ and the differential pressure of 15MPa, while “Sample B2_dry_130℃_20MPa_Swave” denotes that S-wave waveform of dry sample B2 is measured at 130℃ and the differential pressure of 20 MPa. The package also includes the TXT file of sample lengths.</p> <p>In the TXT files of Samples A1-A6, the columns give wave amplitudes. The time interval is 0.05 μs. The travel times of P-wave and S-wave in the measured system are 8.4 μs and 14.45 μs, respectively. In the TXT files of Samples B1-B6, the first column gives time and the second column gives wave amplitude.</p>
Crack simulations in random heterogeneous media: worm burrows
<p>The folders correspond to the panels of Figure 5 in the referencing paper. The top row of figures are in the kic subfolder, cov_minus, baseline and cov_plus from left to right. The bottom two rows are in the kikic folder cov_minus, baseline and cov_plus from left to right.</p> <p> </p> <p>Data is in the .mat files, each of which contains three variables. x1_path contains the horizontal locations of the crack tip during its propagation and x2 path contains the vertical position.</p> <p> </p> <p>The data can be recreated by executing the .m files in each subfolder, having downloaded and extracted the entire archive. The files are matlab files which must be executed in matlab. </p> <p> </p> <p>The simulation engine is in burrow_prop_03.m</p>
Data for: Condition monitoring system for in situ crack detection based on thermal emissions
<p>The advent of packaged infra-red (IR) bolometer detectors has led to thermography-based techniques becoming popular for non-destructive evaluation of aerospace structures. These packaged bolometers are relatively compact and cost about 10% the price of high-resolution IR photovoltaic effect detectors. In this work, a condition monitoring system for in situ crack detection has been presented which utilises an original equipment manufacturer (OEM) microbolometer detector. The proposed system cost approximately 1% the price of a state-of-the-art photovoltaic effect detector system and has the potential to transform the use of IR imaging for condition monitoring in the aerospace industry and elsewhere. The proposed system performs crack detection based on the principles of thermoelastic stress analysis (TSA), which is a well-established non-destructive thermography technique. Proof-of-concept lab tests were performed on open-hole aluminium specimens to compare the performance of the proposed system against an IR photovoltaic effect detector system and demonstrate its potential application for in situ crack detection in industrial environments. It was demonstrated that crack detection is possible from loading waveform signals with frequencies as low as 0.3 Hz. This represents a significant advance in the viability of TSA-based crack detection in large-scale structural tests where loading frequencies are usually lower than 1 Hz.</p> <p> </p>
Crack density evolution on glass/epoxy laminates under spectrum loadings (MOST - Spoke 11 - Task 6.3)
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Fracture metamaterials with on-demand crack paths enabled by bending
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Expansive Soil Desiccation Crack Segmentation using DeepLabv3+
<p>DeepLabv3+ with different backbones were used to perform expansive soil recognition and segmentation. The zip included the code and sample image datasets used to train, validate, and test the DeepLabv3+ with 4 different backbones (MobileNetV2, ResNet-18, ResNet-50, and Xception). The code was implemented using MATLAB R2023b. See README.txt for more information.</p>
Digital image correlation displacements and strains around a growing fatigue crack in an AA2024-T3 aluminium alloy
<p>This repository contains the data used in the research article:</p> <p>Strohmann, Melching, Paysan, Dietrich, Requena, Breitbarth. Next generation fatigue crack growth experiments of aerospace materials. <em>Scientific Reports</em>, 2024, <a href="https://doi.org/10.1038/s41598-024-63915-x" target="_blank" rel="noopener">https://doi.org/10.1038/s41598-024-63915-x</a>.</p> <p> </p> <p><strong>General Description</strong><br>The dataset contains digital image correlation (DIC) data of a growing fatigue crack in an AA2024-T3 alloy. For the experiment, two independent DIC measurement devices were used – a global full-field DIC and a local microscopic DIC. Thus, the dataset consists of two main directories. One for the 3D DIC data ("global_3d_dic") and a second one for the 2D microscopic DIC data ("local_2d_dic"). Both of these are described and connected by rich metadata.<br>The 3D DIC data directory contains two subdirectories (a "Nodemaps" directory and a "Connections" directory). Both of them contain 797 '.txt'-files. The "Nodemaps" give the DIC results (i.e. coordinates, displacement and strains) for every timestep throughout the experiment. These are usually maximum, minimum, and mean load of a certain load cycle. However, for few crack lengths, we obtained DIC data for a higher number (ca. 100) of images within one load cycle. The nodemaps' format and structure is optimized for data processing in the open-source Python package <a title="CrackPy" href="https://doi.org/10.5281/zenodo.10990494" target="_blank" rel="noopener">CrackPy</a>. The last integer number of each filename can be interpreted as a 'timestep' throughout the experiment. The "Connection" files represent the connections of the DIC facet center coordinates. These are necessary to export the "Nodemap" data to any mesh like dataset, e.g. for VTK. <br>The 2D microscopic DIC directory contains 3 subdirectories ("80", "90", "95") for predefined positions with respect to the specimen coordinate system. For each location, a number of DIC data are stored, again within two subdirectories "Nodemaps" and "Connections" as '.txt'-files. For the 2D DIC data, the last integer of each name cannot be correlated to a timestep. Instead, we provide a descriptive file "local_2d_microscopic_coordinates_by_nodemaps.csv" linking each and every "Nodemap"-file to its respective coordinates and timestep (i.e. the load cycles).</p> <p>To describe the data, we distinguish between<br>1. Higher-level metadata - these data contain information about the experiment and material. The data do not change between timesteps and are given within this description.<br>2. Timestep metadata - these data contain information about one timestep of the experiment and are stored in the header of each "Nodemap"-file.</p> <p> </p> <p><strong>Higher-level Metadata</strong><br>The experiment is described in detail in the reference publication by <a title="Strohmann et al. (2024)" href="https://www.researchsquare.com/article/rs-3128435/v1" target="_blank" rel="noopener">Strohmann et al. (2024)</a> and a summary is given below. Moreover, we provide a dictionary in javascript object notation explaining terms which are used in the higher-level metadata. We use such a dictionary since no standardized ontology is currently available. This dictionary is stored in the main directory as "higher_level_metadata_dictionary.json".</p> <p><em>Material </em><br>A commercially available AA2024-T3 aluminum alloy was tested in L-T orientation, i.e. rolling direction, L, parallel to the load axis. The specimen had a width W = 160 mm cut from a rolled sheet of 2 mm.</p> <p><em>Digital image correlation</em><br>For 3D DIC, we used a GOM Aramis 12M system with a facet size of 20 x 20 pixels and a 16 pixels facet distance. One facet, therefore, covers ~0.614 x 0.614 mm². For the 2D microscopic DIC we captured images using a Zeiss STEMI 206C light optical microscope (LOM), equipped with a Basler a2A5320-23µmPro global shutter CMOS camera. One image has a size of 10.2 x 5.7 mm², 5328 x 3040 Pixels and a facet size of 40x40 pixels (distance of facet center points 30 pixels). The LOM was mounted to a robotic arm, a KUKA lbr Iiwa Cobot.</p> <p><em>Fatigue crack growth</em><br>We used a standard uniaxial servo-hydraulic testing rig. We applied a cyclic load ranging from Fmin = 4.5 kN to Fmax = 15 kN, i.e. R=Fmin/Fmax = 0.3. Throughout the experiment, we measured the crack length using direct current potential drop (DCPD).</p> <p><em>Image acquisition during fatigue crack growth</em><br>We acquired reference images for the DIC calculations before the experiment. For the global DIC, this is simply an image of the unloaded specimen. For the local microscopic DIC, the reference images are acquired in a checker board pattern with an overlap of 70 %. The depth of focus was calibrated for each image individually following (see <a title="Paysan et al. (2023)" href="https://doi.org/10.1007/s11340-023-00964-9" target="_blank" rel="noopener">Paysan et al. (2023)</a>). Images were acquired every 0.5 mm of crack extension at minimum, maximum and 0.5(Fmax- Fmin).</p> <p> </p> <p><strong>Timestep Metadata</strong><br>The timestep-wise metadata is stored in the individual DIC output files, "Nodemaps". We explain the terms used in a second dictionary, "timestep_level_metadata_dictionary.json". For all DIC data, we stored all data coming from the machine controller, i.e. number of cycles, force, displacement of the cylinder and also potential and crack length calculated from the potential as well as current values for back face strain gauges at both back faces of the MT specimen. In addition, for the local microscopic DIC data, we also store the current location of the center point of the image with respect to the global coordinate system provided by the current position of the robot carrying the LOM.</p>
Data of "Ultra-thin Strain Hardening Cementitious Composite (SHCC) layer in reinforced concrete cover zone for crack width control"
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Matlab code for the 'Force–displacement response of in-plane loaded unreinforced brick masonry walls: the Critical Diagonal Crack model'
<p>The repository contains the the Matlab code and the test data (.csv files) used for the analyses and results presented in the research article:</p> <p>Force–displacement response of in-plane loaded unreinforced brick masonry walls: the Critical Diagonal Crack model, <em>Bulletin of Earthquake Engineering</em>,<em> </em>2017, <a href="https://link.springer.com/article/10.1007%2Fs10518-016-0049-7">Link</a></p>
High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys - Supporting data
<p>Data related to High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys:</p> <p>Conor Gillen, Alistair Garner, Pia Tejland, Philipp Frankel,<br> High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys, Journal of Nuclear Materials, Volume 519, 2019, Pages 166-172, ISSN 0022-3115,<br> https://doi.org/10.1016/j.jnucmat.2019.03.027.</p> <p>Datafiles for STEM-EDX analysis - STEM-EDX.zip</p> <p>Datafiles for TKD analysis - TKD.zip</p> <p>Datafiles for NanoSIMS analysis - 1: NanoSIMS raw data file (.im file) with all 160 planes and data for all ion signals acquired. Can be opened with the OpenMIMS plugin for ImageJ or other NanoSIMS software. 2: NanoSIMS processed data file (.nrrd file) which is drift corrected and can be opened with the OpenMIMS plugin for ImageJ</p>
Assessing instantaneous stiffness of cracked reinforced concrete beams based on crack depths
<p>The crack presence changes the shape or size of sections in reinforced concrete beams, and greatly affects the section inertias and the beam stiffness. To assess the instantaneous stiffness of the cracked beams, a method is proposed based on the exact crack depth. The region affected by cracks is determined firstly, and different nonlinear strain distributions are modeled in the effect region to describe the change of concrete strains caused by cracks. The internal force equilibria are adopted to find a solution to the top strain and neutral axis, and according to the solution, the inertias of key sections are calculated to assess the beam stiffness. The proposed method has been validated using experimental results obtained from two-stage tests on five reinforced concrete beams. The dataset stores valuable results calculated by the proposed method.</p>
Fatigue crack initiation data for glass/epoxy notched composites (MOST-Spoke 11-WP6)
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Dataset for Crack Detection in Images of Masonry Using CNNs
<p>We trained a convolutional neural network (CNN) on images of brick walls built in a laboratory environment and test its ability to detect cracks in images of brick-and-mortar structures both in the laboratory and on real-world images taken from the internet. We also compared the performance of the CNN to a variety of simple classifiers operating on handcrafted features. This is the dataset used in that work.</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>
Figure data for ``Fatigue crack growth under large scale yielding condition: a tool based on explicit crack growth''
<p>Figure data used for the paper "Fatigue crack growth under large scale yielding condition: a tool based on explicit crack growth" (doi 10.46298/jtcam.9296). The numerical values are provided as raw text in the tikz/pgfplots format. They can be compiled using latex/pdflatex engines. The name of each data file corresponds to the figure numbering in the paper.</p>
Data for: Tensile cracks can shatter classical speed limits
<p class="MsoNormal"><span>Brittle materials fail by means of rapid cracks. At</span> <span>their tips, tensile cracks dissipate elastic energy </span><span>stored in the surrounding material to create newly</span> <span>fractured surfaces, precisely maintaining `energy </span><span>balance' by exactly equating the energy flux with</span> <span>dissipation. Using energy balance, fracture</span> <span>mechanics perfectly describes crack motions;</span> <span>accelerating from nucleation to their maximal speed </span><span>of c</span><span><sub>R</sub>,</span><span> </span><span>the Rayleigh wave speed. Beyond c</span><sub><span>R</span></sub><span>, tensile</span> <span>fracture is generally considered to be impossible</span><span>. B</span><span>y the use of brittle hydrogels,</span> <span>we experimentally demonstrate that a wholly </span><span>new and different class of tensile cracks</span><span> that move faster than the shear wave speed, c<sub>s</sub>, </span><span>exists. The principle of energy</span> <span>balance no longer dictates their dynamics; this new </span><span>branch of cracks smoothly surpasses </span><span>c<sub>s</sub> </span><span>to reach</span> <span>unprecedented speeds that approach the speed of </span><span>dilatation waves. The transition from `classical'</span> <span>cracks to these `supershear' cracks takes place at </span><span>critical values of applied strains. We, furthermore,</span> <span>show that the values of these, rather moderate (12–14%), critical strains are intimately related to the</span> <span>microscopic material structure.</span> <span>This new mode of tensile</span> <span>fracture represents a fundamental paradigm shift in</span> <span>our understanding of 'how things break'.</span></p>
Crack in Sicilia - risposte al questionario online
<p>Risposte al questionario online "Crack in Sicilia" rimasto disponibile per la compilazione agli operatori dei SerT e delle Comunità terapeutiche della regione Siciliana dal 30 marzo al 19 aprile 2023.</p>
Inputs, output and animation files related to the article titled "A computational framework for crack propagation along contact interfaces and surfaces under load" submitted to CMAME.
<p>Here you can find input mesh files, parameter files, output files and animations for numerical examples considered in the paper entitled "A computational framework for crack propagation along contact interfaces and surfaces under load" submitted to Computer Methods in Applied Mechanics and Engineering.</p>
Clinical Implication of the Tunable Crack Sensor
ClinicalTrials.gov study NCT03805815. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
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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)
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DANDI Archive for NWB datasets
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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.