Find research datasets worth reusing

opencc-by-4.0Dec 2020View details →

Hyperspectral X-ray CT datasets of an aluminium phantom containing three metal-based powders

General Data description: This is a set of two hyperspectral (energy-resolved) X-ray CT projection datasets of a multi-phase phantom. It was acquired in a custom-built, laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester. The following data contains all the files necessary for reconstruction, following two hyperspectral scans of a metal, multi-phase phantom. The phantom consists of an external aluminium cylinder, with three holes, each filled with a different metal-based powder (CeO2, ZnO, Fe). Each powder provides a unique attenuation signal, with CeO2 in particular producing a distinct spectral marker which can be measured by an energy-sensitive detector. Two identical scans were acquired, with only the exposure time per projection changed. Note: Zenodo Version 2 of this dataset contains the incorrect version of the 180s, 180 projection phantom dataset, if wishing to analyse the dataset used in the associated hyperspectral paper. This version (Version 3) contains the correct dataset from the paper. File descriptions: Contained is an image (.jpg) of the sample, along with five MATLAB (.mat) data files, as well as a single text (.txt) file. Where necessary, the files have been named to match the dataset they belong to, based on the different exposure times used for each dataset. Phantom_design_measurements.jpg contains a photograph of the physical phantom, combined with a diagram showing full sample measurements. Powder_phantom_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections for both scans. Powder_phantom_30s_30Proj_sinogram.mat contains the 4D sinogram constructed following flatfield normalisation of the raw projection data, where an exposure time of 30 s was used for each projection. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired during scanning. The total number of channels in the file is 200. Powder_phantom_180s_180Proj_sinogram.mat is the 4D sinogram for the dataset, when exposure times of 180 s were used for each projection, following flatfield normalisation. A discontinuity occurs at projection 137 due to an interruption in the scan procedure. The total number of channels in the file is 200. Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning. This is the same for both datasets. FF_30s.mat contains the 4D flatfield data acquired when no sample was present, in the case of 30 s exposure times. This data was used to normalise the projection datasets, as the sinogram was constructed. The first 200 channels are included. FF_180s.mat contains the 4D flatfield data for the dataset where 180 s exposure times were used. The first 200 channels are included.

opencc-by-4.0Mar 2022View details →

Laboratory-measured and X-ray CT-derived volumetric composition of a permafrost core

This dataset contains data on the volumetric composition of a permafrost core which has been drilled in a Yedoma upland in northeast Siberia (72.36613 N, 126.27272 E) in September 2017. This dataset supplements a research article to be submitted to the scientific journal The Cryosphere. It contains the following files: volumetric_contents_sampleRes_lab+CT.csv Contains the volumetric contents of total ice, organic, and mineral measured in the laboratory at AWI Potsdam at a coarse resolution. It further contains the volumetric contents of gas, excess ice, and two sediment phases (A,B) derived from a CT scan at UFZ Halle, downsampled to the resolution of the laboratory samples. volumetric_contents_highRes_CT.csv Contains the volumetric contents of gas, excess ice, and two sediment phases (A,B) derived from a CT scan at UFZ Halle at the original resolution of 50µm. regression analysis_paper.py This pyhton script uses the above listed input files to perform and evaluate a regression analysis of the CT data against the laboratory data. The regression result is the composition of the CT-derived sediment phases (A,B) in terms of pore ice, organic, and mineral. The script furthermore computes evaluation metrics of the lab-CT comparison, and computes volumetric contents of pore ice, total ice, organic, and mineral at the high resolution of the original CT data. volumetric_contents_sampleRes_all.csv This file can be reproduced by the files listed above and contains, in addition to the data contained in volumetric_contents_sampleRes_lab+CT.csv, the volumetric contents of pore ice, total ice, mineral, and organic as predicted by the regression model at the same (coarse) resolution as the laboratory samples. volumetric_contents_highRes_all.csv This file can be reproduced by the files listed above and contains, in addition to the data contained in volumetric_contents_highRes_CT.csv, the volumetric contents of pore ice, total ice, mineral, and organic as predicted by the regression model at the same (high) resolution as the original CT data. More details can be found in the article describing the study.

opencc-by-4.0Jun 2022View details →

Hyperspectral X-ray CT datasets of three chemical phantoms

General Data description: The following are hyperspectral (energy-resolved) X-ray CT datasets for a set of chemical phantom samples, each containing multiple phases of an aqueous contrast agent at different concentrations. All scans were acquired with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester. The following data contains all the files necessary for reconstruction of each dataset. The phantom samples were produced as they each offer a distinct spectral marker which, when measured by an energy-sensitive detector, may be used as a form of calibration for spectral analysis. The phantoms were for the common contrast agents of I2KI, BaSO4 and PTA. File descriptions: Contained are four MATLAB (.mat) data files, as well as three text (.txt) metadata files. Iodine_Phantom_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition for the I2KI phantom. The concentrations for the iodine phases were 25, 50, 76 and 101 mg/ml of aqueous I3- ions respectively. Barium_Phantom_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition for the BaSO4 phantom. The concentrations for the BaSO4 phases were 100, 200 and 400 mg/ml of BaSO4 respectively. Tungsten_Phantom_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition for the PTA phantom. The concentrations for the PTA phases were 50, 100 and 200 mg/ml of PTA respectively. Iodine_phantom_sinogram.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data for the I2KI phantom. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. In addition, a ring artefact reduction filter was applied, as well as a centre-of-rotation correction. Barium_phantom_sinogram.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data for the BaSO4 phantom. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. In addition, a ring artefact reduction filter was applied, as well as a centre-of-rotation correction. Tungsten_phantom_sinogram.mat contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data for the PTA phantom. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. In addition, a ring artefact reduction filter was applied, as well as a centre-of-rotation correction. Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.

opencc-by-4.0Jun 2022View details →

Hyperspectral X-ray CT datasets for a set of multiply-stained mouse limb specimens

General Data description: The following are hyperspectral (energy-resolved) X-ray CT datasets for a set of mouse limb specimens, each stained with multiple contrast agents. All scans were acquired with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester. The following data contains all the files necessary for reconstruction of each dataset. The biological specimens were produced as they each contain multiple contrast agents, with distinct spectral markers. When measured by an energy-sensitive detector, each contrast agent may be identified and segmented individually following spectral analysis. A mouse hindlimb was double-stained with elemental iodine and BaSO4. A mouse forelimb was triple-stained with I2KI, BaSO4 and PTA. File descriptions: Contained are two HDF5 (.h5) data files, as well as two (.txt) metadata files and a MATLAB (.mat) file. Hindlimb_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition for the double-stained hindlimb. Forelimb_scan_parameters.txt provides the full sample and detector geometry of the scan acquisition for the triple-stained forelimb. DS_Mouse_hindlimb_sinogram.h5 contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data for the double-stained hindlimb specimen. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. In addition, a ring artefact reduction filter was applied. TS_Mouse_forelimb_sinogram.h5 contains the full 4D sinogram constructed following flatfield normalisation of the raw projection data for the triple-stained forelimb specimen. The 4D array contains the total number of energy channels acquired during scanning, followed by vertical and horizontal pixel number, and finally total projections angles acquired. In addition, a ring artefact reduction filter was applied. Energy_axis.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning.

opencc-by-4.0May 2020View details →

ds-uct-001: Cast Iron GGG40: X-Ray micro-CT of a nodular cast iron sample class GGG40.

Summary: .X-Ray micro-computed tomography (micro-CT) of a nodular cast iron sample class GGG40, including both raw projection data and the final reconstructions, for three different resolutions (voxel sizes of 1 μm, 3 μm and 11 μm). .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility. .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers. Details: .Tomo1 (1024) - Voxel size: 1 μm; Sample-source: 26 mm; Sample-detector: 150 mm; Optical magnification: 4.0X; Filter: HE#6; Beam energy: 160 kV; Power: 10 W; Exposure time: 60.0 sec; Projections: 1600. .Tomo2 (1024) - Voxel size: 3 μm; Sample-source: 28 mm; Sample-detector: 35 mm; Optical magnification: 4.0X; Filter: HE#4; Beam energy: 160 kV; Power: 10 W; Exposure time: 10.0 sec; Projections: 3200. .Tomo3 (1024) - Voxel size: 11 μm; Sample-source: 30 mm; Sample-detector: 158 mm; Optical magnification: 0.4X; Filter: HE#4; Beam energy: 160 kV; Power: 10 W; Exposure time: 3.0 sec; Projections: 3200. Contents: ._info_ds-uct-001.txt .ds-uct-001_cast_iron_ggg40_01um_8bits.zip .ds-uct-001_cast_iron_ggg40_03um_8bits.zip .ds-uct-001_cast_iron_ggg40_11um_8bits.zip .ds-uct-001_cast_iron_ggg40_01um_1600p.txrm .ds-uct-001_cast_iron_ggg40_01um_1600p_Drift.txrm .ds-uct-001_cast_iron_ggg40_01um_1600p_recon.txm .ds-uct-001_cast_iron_ggg40_03um_3200p.txrm .ds-uct-001_cast_iron_ggg40_03um_3200p_Drift.txrm .ds-uct-001_cast_iron_ggg40_03um_3200p_recon.txm .ds-uct-001_cast_iron_ggg40_11um_3200p.txrm .ds-uct-001_cast_iron_ggg40_11um_3200p_Drift.txrm .ds-uct-001_cast_iron_ggg40_11um_3200p_recon.txm

opencc-by-4.0Jun 2020View details →

ds-uct-002: Root Canal Strain: X-Ray micro-CT of four teeth before and after root canal procedure.

Summary: .X-Ray micro-computed tomography (micro-CT) of four teeth before (TomoB) and after (TomoA) simulation of root canal treatment and retreatment procedures instrumented with strain-gauge, including reconstructions, for two different resolutions (TomoB and TomoA with voxel sizes of 20.0 μm and 10.5 μm, respectively). .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility. .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers. Details: .Tomo1B/Tomo2B/Tomo3B/Tomo4B (1024) - Voxel size: 20.0 μm; Sample-source: 45.0 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#1; Beam energy: 60 kV; Power: 5 W; Exposure time: 2.0 sec; Projections: 1600. .Tomo1A/Tomo2A/Tomo3A/Tomo4A (2048) - Voxel size: 10.5 μm; Sample-source: 48.2 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#2; Beam energy: 60 kV; Power: 5 W; Exposure time: 7.0 sec; Projections: 1600. Contents: ._info_ds-uct-002.txt .ds-uct-002_root_canal_strain_tomo1b_20um_8bits.zip .ds-uct-002_root_canal_strain_tomo2b_20um_8bits.zip .ds-uct-002_root_canal_strain_tomo3b_20um_8bits.zip .ds-uct-002_root_canal_strain_tomo4b_20um_8bits.zip .ds-uct-002_root_canal_strain_tomo1a_10um_8bits.zip .ds-uct-002_root_canal_strain_tomo2a_10um_8bits.zip .ds-uct-002_root_canal_strain_tomo3a_10um_8bits.zip .ds-uct-002_root_canal_strain_tomo4a_10um_8bits.zip .PB_PARECER_CONSUBSTANCIADO_CEP_2650528.pdf

opencc-by-4.0Jul 2020View details →

ds-uct-007: Asphalt Concrete: X-Ray micro-CT of an asphalt concrete sample.

Summary: .X-Ray micro-computed tomography (micro-CT) of an asphalt concrete sample, including both raw projection data and the final reconstructions, for one single resolution (voxel size of 7 μm). .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility. .Image data segmented with four different segmentation techniques: DL (Deep Learning), ML (Machine Learning), TH (Thresholding) and WS (Watershed). .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers. Details: .Tomo - Voxel size: 7 μm; Sample-source: 31 mm; Sample-detector: 274.25 mm; Optical magnification: 0.4X; Filter: LE#6; Beam energy: 100 kV; Power: 9 W; Exposure time: 4.0 sec; Projections: 1600. Contents: ._info_ds-uct-007.txt .ds-uct-007_asphalt_concrete_07um_16bits.zip .ds-uct-007_asphalt_concrete_07um_1600p.txrm .ds-uct-007_asphalt_concrete_07um_1600p_Drift.txrm .ds-uct-007_asphalt_concrete_07um_1600p_recon.txm .ds-uct-007_asphalt_concrete_07um_DL.zip .ds-uct-007_asphalt_concrete_07um_ML.zip .ds-uct-007_asphalt_concrete_07um_TH32.zip .ds-uct-007_asphalt_concrete_07um_WS.zip

opencc-by-4.0Nov 2020View details →

Hyperspectral X-ray CT data set of mineralised ore sample with Au and Pb deposits

General data description: This is a hyperspectral (energy-resolved) X-ray CT projection data set of a mineralised ore sample with small gold and galena deposits. It was acquired in a laboratory micro-CT scanner with an energy-sensitive HEXITEC detector in the Henry Moseley X-ray Imaging Facility at The University of Manchester. The data included contains all the relevant files required for reconstruction, following a hyperspectral scan of a mineralised ore sample. The sample contains a number of mineral phases, of varying concentration, distributed throughout. Some phases (including gold, and lead-based Galena) produce unique absorption edges, which act as spectral identifiers that can be measured by an energy-sensitive detector. File descriptions: The data set consists of one .txt file and three .mat (MATLAB) data files. Au_rock_scan_geometry.txt gives a breakdown of the full sample and detector geometry used when acquiring the raw projections. The number of horizontal detector pixels accounts for the fact that a set of 5 tiled scans of the sample were collected and later stitched together. Au_rock_sinogram_full.mat contains the full 4D sinogram constructed following flat-field normalisation of the raw projection data. The data matrix contains the total number of energy channels acquired during scanning, as well as the conventional elements of vertical/horizontal detector pixel number and total projection angles. commonX.mat provides a direct conversion between the energy channels, and the energies (in keV) that they correspond to, following a calibration procedure prior to scanning. FF.mat contains the 4D flatfield data acquired when no sample was present. This data was used to normalise the projection datasets, as the sinogram was constructed.

opencc-by-4.0May 2015View details →

Raw X-Ray CT data of CFC-Cu ITER monoblock mock-up

Raw X-Ray CT data for CFC-Cu ITER monoblock mock-up. The monoblock was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans). This data was used for the publication Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015. DOI: 10.1016/j.fusengdes.2015.04.048

opencc-by-4.0Oct 2021View details →

Multi-resolution X-Ray micro-CT images of Bentheimer Sandstones

This dataset consists of multi-resolution X-Ray micro-tomography images of two Bentheimer sandstone rock cores. The rock cores were first used experimentally in [1] with further modelling in [2]. This new dataset is used directly in the publication [3] - preprint available at https://arxiv.org/abs/2111.01270.  The original dataset from [1] (of the same rock cores) is hosted on the BGS National Geoscience Data Centre, ID #130625 at dx.doi.org/10.5285/5f899de8-4085-4370-a45e-e613f27e8f1d and there is also a subvolume image dataset, for easier download available on the Digital Rocks Portal, project 229, DOI:10.17612/KT0B-SZ28 at digitalrocksportal.org/projects/229.  The images provided herein are from two distinct Bentheimer rock cores -- core 1 and core 2. The cores have diameter, 12.35mm, lengths 73.2mm and 64.7mm, core-averaged porosities of 0.203 and 0.223 and permeabilities of 1.636D and 0.681D for core 1 and 2, respectively. Core 2 has a clear low permeability lamination occurring at 2/3 of the total core length, whereas core 1 has a general fining towards the outlet of the core creating a reduction in porosity [1]. The images were acquired with a Zeiss Versa 510 X-Ray CT scanner. We acquired images of two sub volumes from each core, at locations 1/3rd (subvolume 1) and 2/3rds (subvolume 2) of the way along the core length, at resolutions of 2, 6 and 18 microns. We refer to the 2 micron images as high-resolution (HR), the 6 micron images as low-resolution (LR) and the 18 micron images as very-low-resolution (VLR). There are also super-resolution (SR) images created at 2 micron resolution from the LR images, using a deep-learning algorithm. There are also cubic interpolation images created from the LR image - these are labels bicubic. These have a resolution of 2 microns, and size equal to the HR and SR images. Details of the SR and LR Bicubic generation are found in [3]. The following scanning protocols were used for the direct imaging: 2 micron images: --We use a 4x microscope objective, an exposure time of 8s, 2x averaged binning, 9001 projections, a scan voltage of 80kV and a power of 7W. Each scan takes approximately 24 hours. 6 micron images: --We use a flat panel detector, an exposure time of 0.7s, 10x repeat frames, 1x averaged binning, 2401 projections, a scan voltage of 80kV and a power of 7W. The cone angle is 14.46 degrees and the fan angle is 22.2 degrees. Each scan takes approximately 1 hour. 18 micron images: --We use a 0.4x microscope objective, an exposure time of 1s, 10x repeat frames, 1x averaged binning, 2401 projections, a scan voltage of 80kV and a power of 7W. The cone angle is 12.65 degrees and the fan angle is 12.65 degrees. Each scan takes approximately 2 hours. We present 4 sets of the images with different levels of processing. All images are mutual registered to each other. Each image filename has a Core#_Subvol#_resolution identifier, either with the actual resolution (e.g. 6) or the short form (e.g. LR). The following name endings are used (1) - '_16bit_LE.raw'. These are the .raw images of little-endian format. Preceding this filename is also the cubic image side length in voxels, e.g. _75cube. 12 images in total. (2) - '_16bit_LE_normalised.raw'. These are the .raw images of little-endian format with normalised greyscale values following the procedure in [1]. Preceding this filename is also the cubic image side length in voxels, e.g. _75cube. 12 images in total. (3) - 'Core1_Subvol1_HR' etc. These are the .tiff images of (2) above, which have been converted to 8 bit. Includes bicubic interpolation images and SR images, but no 16 micron images, since these were not used in the analysis of [3]. 16 images in total.  (4) - 'Core1_Subvol1_HR_filtered' etc. These are the .tiff images from (3) above, which have filtered using non-local means filtering. More details are found in [3]. Note there are no SR images here since they are already essentially filtered, and included in (3) above. 12 images in total. References [1] Jackson, S.J., Lin, Q. and Krevor, S. 2020. Representative Elementary Volumes, Hysteresis, and Heterogeneity in Multiphase Flow from the Pore to Continuum Scale. Water Resources Research, 56(6), e2019WR026396 [2] Zahasky, C., Jackson, S.J., Lin, Q., and Krevor, S. 2020. Pore network model predictions of Darcy‐scale multiphase flow heterogeneity validated by experiments. Water Resources Research, 56(6), e e2019WR026708. [3] Jackson, S.J, Niu, Y., Manoorkar, S., Mostaghimi, P. and Armstrong, R.T. 2021. Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling. Under review, preprint available at https://arxiv.org/abs/2111.01270

opencc-by-4.0Jan 2022View details →

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot <blockquote> X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil - [<a href="https://doi.org/10.1002/ppj2.20036">https://doi.org/10.1002/ppj2.20036</a>] </blockquote> The ZIP file contains: <ul> <li><code>MCT1_Rcode.R</code> - Statistics script for candidate single-timepoint experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.</li> <li><code>MCT1... .csv</code> - 3 CSV data files required by the R script.</li> <li><code>MCT2_Rcode.R</code> - Statistics script for time-series experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.</li> <li><code>MCT2... .csv</code> - 3 CSV data files required by the R script.</li> <li><code>R_RooThProcessing.R</code> - R code for aggregating root traits from RooTh software.</li> <li><code>Modelling folder</code> - OpenSimRoot with model parameters and root data used in manuscript.</li> </ul>

opencc-by-4.0Aug 2023View details →

Hyperspectral 2D fan-beam X-ray CT dataset of 5 materials

Hyperspectral X-ray CT dataset acquired at the DTU 3D imaging center. The phantom consists of 5 materials: Aluminium (10 mm) and PVC (7.8 mm) in solid blocks. Sugar, H2O2, and H2O in circular glass containers. 3D array with dimension: 128 x 370 x 258 < channel, angle, horizontal >   Detector parameters: Number of detector pixels: 258 (concatenated from 2 detector modules with 128 pixels each and 2 pixel interpolated across a gap between detectors) Pixel size: 0.077 cm Sep=0.153  Pixels' gap length (cm) det_space=(ndet)*pixel_size+Sep # physical width of detector in cm (pixels*pixel_size), including the gap   Acquisition Parameters 360 # Angular span of projections in degrees 370 # Number of projections. note: last projection taken is not a duplicate of the first projection. At angle: 360/370 degrees from first projection. 115.0 # Source-Detector distance in cm 0 # Vertical source shift from perfect placement 0 # Vertical detector shift from perfect placement 57.5 # Source-AxisOfRotation distance in cm   rot_axis_x = 0 # x-position offset of AxisOfRotation rot_axis_y = 0 # y-position offset of AxisOfRotation

opencc-by-4.0May 2015View details →

Raw X-Ray CT data of CFC-Cu_GS laser flash coupon

Raw X-Ray CT data for CFC-Cu_GS laser flash coupon. The coupon was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans). This data was used for the publications:  - Evans, Ll.M. et al. "Thermal characterisation of ceramic/metal joining techniques for fusion applications using X-ray tomography", Fusion Engineering and Design, Volume 89, Issue 6, June 2014, Pages 826-836, http://dx.doi.org/10.1016/j.fusengdes.2014.05.002.  - Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015, DOI: 10.1016/j.fusengdes.2015.04.048.

opencc-by-4.0Sep 2016View details →

X-ray CT data: fatigue damage in glass fibre/polyester composite used for wind turbine blades

These data are obtained using a Zeiss Xradia Versa 520 scanner to scan a uni-directional glass fibre reinforced polyester composite made from a non-crimp fabric used for wind turbine blades. The scans were performed to study the fatigue damage progression in this material. The data is published together with the below journal paper, in which more information can be found. The present videos of the data relate directly to the figures in this paper. Jespersen, K. M., Zangenberg Hansen, J., Lowe, T., Withers, P. J., & Mikkelsen, L. P. (2016). Fatigue damage assessment of uni-directional non-crimp fabric reinforced polyester composite using X-ray computed tomography. Composites Science and Technology, 136, 94–103. DOI:10.1016/j.compscitech.2016.10.006 For use of these data, please remember to cite the above mentioned paper. Corresponding author, K. M. Jespersen, e-mail kmun@dtu.dk

Fig. 19 in 3D X-ray microscopy (Micro-CT) and SEM reveal Zospeum troglobalcanicum Absolon, 1916 and allied species from the Western Balkans (Ellobioidea: Carychiidae)

Fig. 19. Zospeum simplex Inäbnit, Jochum & Neubert, 2021, (SMF 349425) Scanning Electron Microscopy images. A. Protoconch and upper teleoconch showing microstructure of superficial pitting. B. Close up view of pitting microstructure. C. Last whorl with axial ribbing extending beyond peristome lip. D. Close up view of second whorl showing rows of interrupted dashes of radial pitting. E. Growth lines and radial banding on teleoconch. F. Close up view of growth lines and shell microstructure.

Fig. 22 in 3D X-ray microscopy (Micro-CT) and SEM reveal Zospeum troglobalcanicum Absolon, 1916 and allied species from the Western Balkans (Ellobioidea: Carychiidae)

Fig. 22. Sites of localities and collections. A. Site of type locality of Zospeum njunjicae Jochum, Schilthuizen & Ruthensteiner sp. nov., Golubova pećina, Gornja Seoca, Montenegro. Credit: I. Njunjić. B. Collection site within St John's cave, type locality of Z. kolbae Jochum, Inäbnit, Kneubühler & Ruthensteiner sp. nov. and Z. njegusiense Jochum & Ruthensteiner sp. nov., Njeguši, Montenegro (42.4307° N, 18.8115° E) with speleologist, P. Kunisch. Credit: Péter Lenkei. C. Entrance to Golubova pećina (42.2093° N, 19.1306° E), Gornja Seoca, Montenegro. Credit: I. Njunjić.

Fig. 16 in 3D X-ray microscopy (Micro-CT) and SEM reveal Zospeum troglobalcanicum Absolon, 1916 and allied species from the Western Balkans (Ellobioidea: Carychiidae)

Fig. 16. Light microscopic images of full-bodied Zospeum Bourguignat, 1856 from Njeguši, St John's cave. A–B. Zospeum kolbae Jochum, Inäbnit, Kneubühler & Ruthensteiner sp. nov. (NMBE 571122– 571123), individuals assessed by DNA sequencing with sigmoid intestine showing through shells (shells were destroyed post imaging for tissue extraction). A. Holotype (NMBE 571122), shell of aliquot, aperture, and aperture facing left view. B. Paratype (NMBE 571123), shell of aliquot, aperture, and aperture facing left view. C. Undescribed Zospeum sp. 1 (NMBE 577052) showing all perspectives. D–E. Undescribed Zospeum sp. 1 (NMBE 577053/2) showing all perspectives.

Fig. 13 in 3D X-ray microscopy (Micro-CT) and SEM reveal Zospeum troglobalcanicum Absolon, 1916 and allied species from the Western Balkans (Ellobioidea: Carychiidae)

Fig. 13. Light microscopic images of Zospeum constrictum Jochum & Ruthensteiner sp. nov. (NHMW Mol.Coll.Edlauer 16.693) and collection labels.A. Holotype, aperture, and dorsal views. B–D. Paratypes, aperture and dorsal views.

Fig. 18. 3D in 3D X-ray microscopy (Micro-CT) and SEM reveal Zospeum troglobalcanicum Absolon, 1916 and allied species from the Western Balkans (Ellobioidea: Carychiidae)

Fig. 18. 3D visualizations of Micro-CT data of Zospeum simplex Inäbnit, Jochum & Neubert, 2021, (NMHW-MO-113642 ex RSC 3760) from Dobravljevac jama, Gornji Brišnik, Bosnia and Herzegovina. A–F. Specimen 1 (spm1). A. Aperture view. B. Aperture facing right view. C. Apical view. D. Dorsal view. E. Aperture facing left view. F. Ventral view. G–L. Specimen 2 (spm2). Same perspectives as Specimen 1.