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5 results for “micro fibre”
Text-fig. 8. Lanfrancia subglobosa E.REID et M.CHANDLER. a–c, e–g: Holotype V. 23014. a: reflected light. b, c: Surface renderings from micro-CT data. a, b: Lateral views with dorsal surface of locule facing forward and locule casts protruding in upper part. c: Apical view. d: Fruit showing two locule casts the dorsal surfaces of which face to the left and the right, V. 30417(1). e–g: Successive digital transverse sections showing four u to v to c-shaped locules from micro-CT data. h: Physical transverse section of specimen in (d). i–k: Physical transverse section, V. 30419 from Herne Bay, blue lines in K indicating limits of fibre layer lining the locule. l: Detail from (h), showing sclerenchyma composing the septa and central axis. m: Transverse section, enlargement from (i), showing anatomy of tissues adjacent to the dorsal infold. Blue lines indicate limits of the fibre layer lining the locule. n: Part of (m) recut, tangential section transecting the dorsal infold (central), both limbs of the locule cast, and peripheral parts of the pericarp on either side. o: Detail from (n), showing anatomy of the infold. Scale bars 5 mm in (a–h) (a–g share the same bar), 3 mm in (i), 1 mm in (j–m), 0.5 mm in (n), 0.2 mm in (o). in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 8. Lanfrancia subglobosa E.REID et M.CHANDLER. a–c, e–g: Holotype V. 23014. a: reflected light. b, c: Surface renderings from micro-CT data. a, b: Lateral views with dorsal surface of locule facing forward and locule casts protruding in upper part. c: Apical view. d: Fruit showing two locule casts the dorsal surfaces of which face to the left and the right, V. 30417(1). e–g: Successive digital transverse sections showing four u to v to c-shaped locules from micro-CT data. h: Physical transverse section of specimen in (d). i–k: Physical transverse section, V. 30419 from Herne Bay, blue lines in K indicating limits of fibre layer lining the locule. l: Detail from (h), showing sclerenchyma composing the septa and central axis. m: Transverse section, enlargement from (i), showing anatomy of tissues adjacent to the dorsal infold. Blue lines indicate limits of the fibre layer lining the locule. n: Part of (m) recut, tangential section transecting the dorsal infold (central), both limbs of the locule cast, and peripheral parts of the pericarp on either side. o: Detail from (n), showing anatomy of the infold. Scale bars 5 mm in (a–h) (a–g share the same bar), 3 mm in (i), 1 mm in (j–m), 0.5 mm in (n), 0.2 mm in (o).
Translaminar Fracture in a Mini-Protruded Compact Tension Specimen: A Dataset of Micro-Scale Tomograms of a Thin-Ply Carbon Fibre-Epoxy Composite acquired via Synchrotron Radiation Computed Tomography During In-Situ Loading
<p>In this study, we developed a scaled-down “mini-protruded compact tension specimen” to facilitate in-situ tensile testing coupled with synchrotron radiation computed tomography (SRCT). This innovative design provides valuable insights into in-situ translaminar damage mechanisms, significantly enhancing the accuracy of data used in finite element models.</p> <p>The specimen is made of HS40 carbon fibres and ThinPreg<sup>TM </sup>736LT epoxy resin, with the layup of [90<sub>2</sub>/0/90<sub>2</sub>/0/90<sub>2</sub>/0/90<sub>2</sub>]. The translaminar fracture experiments were conducted under continuous loading and scanning using ultra-fast SRCT at the Swiss Light Source (SLS) TOMCAT beamline (Paul Scherrer Institut in Villigen, Switzerland). A polychromatic beam with an energy of 24 keV was used. The achieved voxel size was 800 <em>nm</em>, and 1000 projections per scan and 2 <em>ms</em> exposure time were acquired per scan. The GigaFRoST camera served as the detector. The scans were reconstructed into 3D volumes using the SLS’s in-house absorption-based algorithm (Gridrec) for critical loading steps during a test—both before and after a load drop (detailed in the accompanying Excel file). The tensile loading was exerted on the specimen at a rate of 0.2 <em>mm/min</em> until failure during scanning with the Deben CT500.</p>
GFRP Glass fibre plain weave laminate - Micro-computed tomography scans
<p>A sample of computed tomography image of a glass fibre plain weave laminate. Detailed description can be found in the attached metadata files as well as in the associated paper: <a href="https://doi.org/10.1016/j.compositesa.2015.03.027">https://doi.org/10.1016/j.compositesa.2015.03.027 </a></p> <p>The sample was used for geometrical analysis and for creating a TexGen model with the subsequent image-based permeability modelling.</p>
Dataset : Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps
<ul> <li><strong>The three files in the dataset are:</strong></li> </ul> <p>1) Healthy Sheep Atria Fibre Orientation Dataset 300µm</p> <p>2) Heart Failure Sheep Atria Fibre Orientation Dataset 300µm</p> <p>3) Human Atria Fibre Orientation Dataset 330µm</p> <ul> <li><strong>Data is stored as numpy binary files. Given below is an example .py script to open the flat datasets:</strong></li> </ul> <p> import numpy as np<br> data = np.load("Human_330um.npy")</p> <ul> <li><strong>Volume and fibre orientation dataset stored in flat format as given below:</strong></li> </ul> <p> i, j, k, v1, v2, v3, ... repeated for each voxel </p> <p>where (i, j, k) are voxel coordinates and (v1, v2, v3) are vector components corresponding to fibre orientation within that voxel.</p>
3D orthogonal woven carbon fibre fabric and composites - Micro-computed tomography scans
<p>Computed tomography images of a 3D orthogonal woven carbon fibre fabric and composites. Detailed description can be found in the attached metadata files as well as in the associated paper: <a href="https://doi.org/10.1016/j.compositesa.2013.10.004">https://doi.org/10.1016/j.compositesa.2013.10.004</a></p> <p>The sample was used for geometrical analysis and for creating a TexGen model with the subsequent permeability and mechanical modelling.</p>
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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.