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360 results for “steel”
Data from: Low reversed cyclic loading tests for integrated precast structure of lightweight wall with single-row reinforcement under a lightweight steel frame
Given the development of precast structures for low-rise residential buildings, this study explores a new structure—namely, an integrated precast structure of lightweight recycled-concrete wall with single-row reinforcement—under a lightweight steel frame filled with recycled concrete (integrated precast structure for short). The lightweight steel frame and lightweight wall cooperate to bear the forces. The applied concealed bracing, either a rebar bracing or a steel plate bracing, increases the shear resistance of the wall. The lightweight steel frame is designed to bear the vertical loading, whereas the seismic load in the horizontal direction is jointly borne by the frame and wall. This study presents the results of low reversed cyclic loading tests on nine specimens of integrated precast structures. An analysis is then carried out to investigate the mechanical properties of the specimens; based on these results, a formula for the force-bearing performance of the inclined section is developed. The results show satisfactory performance as an integrated piece; the proposed structure has two seismic lines of defence, with the lightweight wall restraint by the side frame being the first line and the steel frame being the second line. Because the failure of the wall can be categorised as shear failure, the restraint of the lightweight steel frame significantly reduces the potential damage of the wall. As the beams and columns of the steel frame tend to bend against failure, the wall filling helps resist sliding. Therefore, the reinforced joints of the connecting beams and columns show no visible signs of damage, indicating that the connection between the beams and columns is reliable. The narrow spacing of rebars and the setting of concealed bracing contribute to the increase in ductility and energy efficiency and the evident reduction in the failure process. Furthermore, the recycled concrete increases the seismic resistance of the structure.
Data from: Adsorption and corrosion inhibition behavior of new theophylline-triazole based derivatives for steel in acidic medium
The design and synthesis of a series of theophylline derivatives containing 1,2,3-triazole moieties is presented. The corrosion inhibition activities of these new triazole-theophylline compounds were evaluated by studying the corrosion of API 5L X52 steel in 1 M HCl media. The results showed that an increase in the concentration of the theophylline-triazole derivatives also increases the charge transference resistance (Rct) value, enhancing inhibition efficiency and decreasing the corrosion process. The electrochemical impedance spectroscopy under static conditions studies revealed that the best inhibition efficiencies (~90%) at 50 ppm are presented by the all- substituted compounds. According to the Langmuir isotherm, the compounds 4 and 5 analyzed exhibit physisorption-chemisorption process, with exception of the hydrogen 3, bromo 6 and iodo 7 substituted compound, which exhibit chemisorption process. The corrosion when submerging a steel bar in 1 M HCl was studied using SEM-EDS. This experiment showed that the corrosion process decreases considerably in the presence of 50 ppm of the organic inhibitors. Finally, theoretical study showed a correlation between EHOMO, hardness (η), electrophilicity (W), atomic charge and the inhibition efficiency in which the iodo 7 substituted compound presents the best inhibitor behavior.
Data from: Theoretical, thermodynamic and electrochemical analysis of Biotin drug as an impending corrosion inhibitor for mild steel in 15% HCl
The corrosion mitigation efficiency of Biotin drug for mild steel in 15% HCl was thoroughly investigated by weight loss and electrochemical methods. The surface morphology was studied by Contact angle, Scanning electrochemical microscopy (SECM), Atomic force microscope (AFM) and Scanning electron microscopy (SEM) methods. Quantum chemical calculation and Fukui analysis was done to correlate the experimental and theoretical data. The influence of concentration of inhibitor, immersion time, temperature, with activation energy, enthalpy and entropy has been reported. The mitigation efficiency of Biotin obtained by all methods was in good correlation with each other. Polarization studies revealed that Biotin acted as mixed inhibitor. The adsorption of Biotin was found to obey the Langmuir adsorption isotherm. Surface studies showed the hydrophobic nature of the steel with inhibitor and vindicated the formation of a film on the metal surface that reduced the corrosion rate.
Balk looks steel but it's wood
Created with Polycam Source: Objaverse 1.0 / Sketchfab
Data for: "Insights into the various mechanisms by which Shewanella spp. induce and inhibit steel corrosion"
Open the record for dataset details and reuse information.
Influence of elastomeric and steel ligatures on periodontal health during fixed appliance orthodontic treatment: a systematic review and meta-analysis
<p>Dataset for all analyses.</p>
Acoustic Monitoring Dataset for Robotic Laser Directed Energy Deposition (LDED) of Maraging Steel C300
<p>This dataset presents a set of acoustic signals captured during a single-bead wall experiment in robotic Laser Directed Energy Deposition (LDED) using Maraging Steel C300. The acoustic data was recorded using a high-fidelity Prepolarized microphone sensor (Xiris WeldMIC), capturing the intricate sound profiles associated with the LDED process at a sampling rate of 44,100 Hz.</p><p><strong>Laser Directed Energy Deposition:</strong></p><p>This dataset was generated with a robotic LDED process that consists of a six-axis industrial robot (KUKA KR90) coupled with a two-axis positioner, a laser head, and a coaxial powder-feeding nozzle.</p><p> </p><p><strong>Folder Structure:</strong></p><ul><li><strong>/sample-1</strong>: The main folder for the experiment sample.<ul><li><strong>/audio_files</strong>: Contains 4624 <strong>.wav</strong> audio files, each representing a 40 ms chunk of the LDED process sound.</li><li><strong>/annotations_1.csv</strong>: A CSV file providing annotations for the audio files, labeling each as "Defect-free", "Defective", or "Laser-off".</li></ul></li><li>audio_features.h5: extracted acoustic features in time-domain, frequency-domain, and time-frequency representations (MFCC features). Feature extraction was conducted using Python Essentia Library.</li></ul><p> </p><p><strong>File Naming Convention:</strong></p><ul><li>Audio files within the <strong>audio_files</strong> folder are named following the pattern <strong>sample_ExperimentID_SampleID.wav</strong>. Given that there's only one experiment and one sample, the naming will be consistent, for example, <strong>sample_1_1.wav</strong> for the first file.</li></ul><p><strong>Annotation Details:</strong></p><ul><li>The <strong>annotations_1.csv</strong> file contains detailed labels for each audio file, correlating to the conditions observed during the experiment, aiding in quick identification and analysis.</li></ul><p><strong>Experimental Parameters:</strong> The dataset reflects a controlled experiment setup with the following specifications:</p><ul><li>Geometry: Single bead wall structure</li><li>Dimensions: 90 mm * 42.5 mm</li><li>Number of layers: 50</li><li>Laser beam diameter: 2 mm</li><li>Layer thickness: 0.85 mm</li><li>Stand-off distance: 12 mm</li><li>Laser profile: Gaussian</li><li>Laser wavelength: 1064 nm</li></ul><p><strong>Process Parameters:</strong></p><ul><li>Laser power: 2.3 kW</li><li>Speed: 25 mm/s</li><li>Dwell time: 0 s</li><li>Powder flow rate: 12 g/min</li></ul><p>This dataset aims to facilitate the development and testing of acoustic-based defect detection models for real-time quality monitoring in LDED processes. It can also serve as a reference point for further research on sensor fusion, machine learning, and real-time monitoring of manufacturing processes.</p>
Color Steel Buildings Data and Temperature data
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FIGURE 96 in Twenty-one new species of Omaliini from the Papuan Region (Coleoptera: Staphylinidae: Omaliinae), with diagnostic and faunistic notes on some species of the genus Paraphloeostiba Steel, 1960
FIGURE 96. Distribution of Paraphloeostiba papuana in New Guinea.
Sustainability assessment ofsheet pile materials: concrete vs steel inretaining wall construction
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Tailored deformation behavior of 304L stainless steel through control of the crystallographic texture with Laser-Powder Bed Fusion
<p>Laser-powder bed fusion (L-PBF) has gained significant research interest, not only for its profound advantage of producing near-net shape complex geometries of metallic parts, but also for the possibility of producing tailored microstructures. Recent observations have shown that by adjusting the process parameters it is possible to manipulate the crystallographic texture, through the control of the geometrical features of the melt pool. It is also known that the deformation behavior, namely the transformation induced plasticity or twinning induced plasticity effects, of austenitic stainless steels are dependent on the crystallographic texture. Based on the aforementioned observations, the deformation behavior of austenitic stainless steels processed by L-PBF can be tailored. By adjusting the laser power and the laser scanning speed, tailored crystallographic textures were obtained, along the uniaxial loading direction in 304L stainless steel samples produced by L-PBF. The possibility to engineer the crystallographic textures and thus the deformation behavior, in metastable stainless steels, is demonstrated by performing in situ neutron diffraction and uniaxial tension and compression tests. The influence of the initial and the evolving crystallographic texture on the deformation behavior is demonstrated and elaborated accordingly. The observed asymmetry in the deformation behavior between tension and compression is also discussed in detail.</p>
Supplementary material 1 from: Martone M, Murray-Rust P, Molloy J, Arrow T, MacGillivray M, Kittel C, Kasberger S, Steel G, Oppenheim C, Ranganathan A, Tennant J, Udell J (2016) ContentMine/Hypothes.is Proposal. Research Ideas and Outcomes 2: e8424. https://doi.org/10.3897/rio.2.e8424
Video showing ContentMine software applied to EPMC papers mentioning Zika virus.
Figure 1 from: Huntenburg J, Wagstyl K, Steele C, Funck T, Bethlehem R, Foubet O, Larrat B, Borrell V, Bazin P (2017) Laminar Python: tools for cortical depth-resolved analysis of high-resolution brain imaging data in Python. Research Ideas and Outcomes 3: e12346. https://doi.org/10.3897/rio.3.e12346
Figure 1 - Laminar python pipeline, demonstrated using high-resolution MR data of a ferret brain. a) Binary images demarcating inner (grey-white matter interface, top) and outer (pial surface, bottom) boundaries of the cortex. b) Levelset representations of the same surfaces, where positive values are assigned to voxels outside of the volume deliminated by the surface, and negative values to voxels inside, each increasing in value with euclidean distance from the surface. c) Continuous equivolumetric intracortical depth, which models the positions of laminae relative to cortical morphology. d) Discrete representations of equivolumetric depth levels. e) T2 values, sampled at the six equivolumetric intracortical depths. Note that the equivolumetric laminae do not represent architectonic layers, but provide an anatomically meaningful coordinate system of cortical depth.
Data publication: Numerical simulations of pullout test of steel fiber embedded in high performance concrete (HPC)
<p>This data set contains all necessary inputs for the numerical simulations of pullout test of steel fiber embedded in high performance concrete, including discretization data, boundary conditions, material parameters and numerical results. The discretization is realized in terms of the finite element method. </p>
Segregated steel
<p>Segregated steel </p>
Audio Visual in-situ Monitoring Dataset for Laser Directed Energy Deposition (LDED) of Maraging Steel C300
<p>This dataset presents a set of acoustic signals and coaxial CCD images captured during a single-bead wall experiment in robotic Laser Directed Energy Deposition (LDED) using Maraging Steel C300. The acoustic data was recorded using a high-fidelity Prepolarized microphone sensor (Xiris WeldMIC), capturing the intricate sound profiles associated with the LDED process at a sampling rate of 44,100 Hz. The coaxial CCD melt pool images are captured at 30 Hz.</p> <p><strong>Laser Directed Energy Deposition:</strong></p> <p>This dataset was generated with a robotic LDED process that consists of a six-axis industrial robot (KUKA KR90) coupled with a two-axis positioner, a laser head, and a coaxial powder-feeding nozzle.</p> <p> </p> <p><strong>File Naming Convention:</strong></p> <ul> <li>Audio files within the <strong>audio_files</strong> folder are named following the pattern <strong>sample_ExperimentID_SampleID.wav</strong>. Given that there's only one experiment and one sample provided in this demo dataset, the naming will be consistent, for example, <strong>sample_1_1.wav</strong> for the first file.</li> <li>Coaxial melt pool image files within the <strong>images </strong>folder are named following the pattern <strong>sample_ExperimentID_SampleID.jpg</strong>. </li> </ul> <p><strong>Annotation Details:</strong></p> <ul> <li>The <strong>annotations_1.csv</strong> file contains detailed labels for each audio file and image file, correlating to the conditions observed during the experiment, aiding in quick identification and analysis.</li> </ul> <p><strong>Handcrafted features for ML modelling:</strong></p> <ul> <li>The <strong>audio_features.h5</strong> file contains various physics-informed acousitc feature extracted through Python, which can be used for baseline ML modelling purpose.</li> </ul> <p><strong>Experimental Parameters:</strong> The dataset reflects a controlled experiment setup with the following specifications:</p> <ul> <li>Geometry: Single bead wall structure</li> <li>Dimensions: 90 mm * 42.5 mm</li> <li>Number of layers: 50</li> <li>Laser beam diameter: 2 mm</li> <li>Layer thickness: 0.85 mm</li> <li>Stand-off distance: 12 mm</li> <li>Laser profile: Gaussian</li> <li>Laser wavelength: 1064 nm</li> </ul> <p><strong>Process Parameters:</strong></p> <ul> <li>Laser power: 2.3 kW</li> <li>Speed: 25 mm/s</li> <li>Dwell time: 0 s</li> <li>Powder flow rate: 12 g/min</li> </ul> <p>This dataset aims to facilitate the development and testing of acoustic-based, or multi-sensor fusion-based defect detection models for real-time quality monitoring in LDED processes. It can also serve as a reference point for further research on sensor fusion, machine learning, and real-time monitoring of manufacturing processes.</p>
Data from: Inhibition behavior of mild steel by three new benzaldehyde thiosemicarbazone derivatives in 0.5 M H2SO4: Experimental and computational study
Three new benzaldehyde thiosemicarbazone derivatives namely benzaldehyde thiosemicarbazone (BST), 4-carboxyl benzaldehyde thiosemicarbazone (PBST) and 2-carboxyl benzaldehyde thiosemicarbazone (OCT) were synthesized and their inhibition effects on mild steel corrosion in 0.5 M H2SO4 solution were studied systematically using gravimetric and electrochemical measurements. Weight loss results revealed that PBST exhibited the highest inhibition efficiency of 96.6% among the investigated compounds when the concentration was 300 μM. The analysis of polarization curves indicated that the three benzaldehyde thiosemicarbazone derivatives acted as mixed type inhibitors and PBST and OCT predominantly anodic. The adsorption process of all these benzaldehyde thiosemicarbazone derivatives on Q235 steel surface in 0.5 M H2SO4 solution conformed to Langmuir adsorption isotherm. Scanning electron microscopy was conducted to show the presence of benzaldehyde thiosemicarbazone derivatives on Q235 mild steel surface. The results of theoretical calculations were in good agreement with that of experimental measurements.
Figure 3 from: Martone M, Murray-Rust P, Molloy J, Arrow T, MacGillivray M, Kittel C, Kasberger S, Steel G, Oppenheim C, Ranganathan A, Tennant J, Udell J (2016) ContentMine/Hypothes.is Proposal. Research Ideas and Outcomes 2: e8424. https://doi.org/10.3897/rio.2.e8424
Figure 3 - Amanuens.is has automatically highlighted facts which can be viewed alongside manual annotations. Annotators can discuss and reply to each other in the browser.
Figure 2 from: Martone M, Murray-Rust P, Molloy J, Arrow T, MacGillivray M, Kittel C, Kasberger S, Steel G, Oppenheim C, Ranganathan A, Tennant J, Udell J (2016) ContentMine/Hypothes.is Proposal. Research Ideas and Outcomes 2: e8424. https://doi.org/10.3897/rio.2.e8424
Figure 2 - A data table showing facts extracted from the 123 papers, including species, human genes, DNA primers and top word frequencies.
Dynamical simulation of EBSD master pattern of a sigma-phase in steel
<p>Dynamical simulation of an electron backscatter diffraction (EBSD) master pattern of a sigma-phase (FeCr) in steel (<em>P4<sub>2</sub>/mmm</em>, <em>a</em> = 8.7961 Å, <em>c</em> = 4.5605 Å) (see Yakel [1983], doi:<a href="https://doi.org/10.1107/S0108768183001974">10.1107/S0108768183001974)</a>. The master pattern was simulated with EMsoft v5.0. The HDF5 file includes master patterns of the upper and lower hemispheres, in both the stereographic projection and the square Lambert projection, of accelerating voltages from 5 to 20 kV with an increment of 1 kV.</p> <p>The HDF5 file can be opened with any HDF5 reader, e.g. the applications HDFView and HDFCompass or the Python library h5py. The file can also be read and plotted with the Python library kikuchipy (https://kikuchipy.org). Assuming Python and the library is installed, the stereographic projection of the master pattern with all energies can be read and plotted with the following commands:</p> <pre><code class="language-python">import kikuchipy as kp s = kp.load("/path/to/steel_sigma_mc_mp_20kv.h5") s.plot()</code></pre> <p>The PNG file shows the stereographic projection of the upper hemisphere of the master pattern from 20 kV. The remaining files are input and output files to the EMsoft programs EMmkxtal (output: steel_sigma.xtal), EMMCOpenCL (input: steel_sigma.xtal, mcopencl.nml; output: steel_sigma_mc_mp_20kv.h5) and EMEBSDmaster (input: BetheParameters.nml, ebsdmaster.nml, steel_sigma_mc_mp_20kv.h5; output: added to existing steel_sigma_mc_mp_20kv.h5).</p>
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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.