1056 research outputs found
Sort by
Dataset for "Breaking Wave Imaging using Lidar and Sonar"
No full textThis dataset comprises the primary data used in the paper "Breaking Wave Imaging using Lidar and Sonar".
The data consists of water surface elevation data throughout the surf and swash zone of a prototype-scale laboratory beach collected at the GWK Large Wave Flume, Hanover using a Lidar array and concurrent acoustic intensity data obtained using a bed-mounted multibeam. The goal of the work was to image the bubble plumes from breaking waves from above and below.
The dataset is composed of one .mat file, which was generated with the MATLAB software. The content of each file is described in the readme file and is included in the structure data as well.The experiment was completed in the GWK Large Wave Flume in Hanover. The flume measures 309 m long, 5 m wide and 7 m deep and is equipped with a combined piston-flap-type wave paddle. A sandy beach with an initially planar slope of 1:15 was constructed at the opposite end of the flume to the wave paddle.
Lidar data were collected using an array of 3 roof-mounted SICK LMS511 2D scanning Lidar. The locations of each instrument are provided in the paper. The array of instruments enabled the free surface elevation to be detected along a 60m transect throughout the surf and swash zone. Data was collected at 25Hz and the instrument had an angular resolution of 0.1666degrees.
Multibeam data were collected using a bed-mounted Reson SeaBat 7125 multibeam instrument. The device was positioned seaward of the breaking wave location approximately 2 m below the still water level looking up and back toward the shallow section of the wave flume. Data was collected at 10 Hz.
For further details of the methodology used, see the "Methodology" section of the corresponding paper.Lidar data were converted from polar to cartesian coordinates to give the x and z positions of the free surface.Lidar data was collected using SICK LMS511 instruments. The instruments were sampled using in-house data-acquisition software. Polar to Cartesian coordinate conversion was done using Matlab.
Multibeam data was collected using a Reson SeaBat 7125 instrument.
Matlab is required to use the stored dataset
Dataset for "3D Printed Contactor for Enhanced Oil Droplets Coalescence"
No full textThis dataset includes all the original data for this project including the design of the 3D contractors, detailed methodology of preparation and characterisation results, raw data of filtration tests.Preparation and characterization of emulsions
The oil-in-water emulsions were prepared by adding specific amounts of oil (0.3, 0.4, and 0.5 vol %) in 1 L of water. A homogenizer (ULTRA-TURRAX, T 25 basic, IKA) was used to mix the oil with water at 19,000 rpm for 5 min. Volume-weighted oil droplets size distributions were obtained for oil-in-water emulsions using a Malvern Mastersizer X (300 mm lens, 1.2 − 600 μm detection range, dispersion unit controller, 3000 rpm). Triplicate measurements were conducted on discrete samples and the volume median diameter D (v, 0.5) was used to compare between the oil droplet sizes in the feed and the permeate. To visualize the oil layer that had formed during the visual observation tests, a stock solution prepared by mixing sunflower oil with Sudan Blue II with ratio 99.9:0.1 (wt. %) was used. 1 L each of oil-in-water emulsion was prepared by mixing different amounts of (0.3, 0.4 and 0.5 vol%) stock solution with pure water.
Contactor permeance and rejection performance
The demulsification of the oil-in-water emulsions was carried out by using a vacuum filtration setup: 300 ml of oil-in-water emulsions were used in each experimental run: The first 250 ml were passed through the 3D printed contactors using vacuum filtration and collected in a separating funnel. After 1 h, 20 ml samples were taken from the bottom layer of the permeate in the separating funnel for analysis following an established procedure. Three types of 3D printed contactors, Cylindrical, Schwarz–P and Gyroid, were used.
Visual observation
The remaining 50 ml of the starting 300 ml emulsion were poured into a burette and a picture (using a Canon EOS 600D) of the top layer was taken every 30 min for 180 min to observe the increase in the thickness of the oil layer with time and quantify the separation rate of the oil phase using the 3D printed contactors and natural separation (Fig.s S9-11). Image J was used to measure the oil layer thickness in the recorded images.
Fabrication and characterization of 3D printed contactors
The process of translating a digitally designed 3-dimensional object into a printed membrane introduces a novel set of challenges compared to traditional membrane fabrication processes: First, the more complex the object, the higher the resolution required to accurately render the object in 3D. This, in turn, leads to very large digital file sizes. For example, increasing the number of grid points needed to create the implicit surface from 150 to 800 (cfr. Fig. 2a–d), increased the file size of the Gyroid contactor from 50 Mbyte to 1.8 Gbyte. The number of grid points is a measure of the resolution of the printed object. The larger file size not only requires a longer time to transfer the file to the printer (up to 72 h), but ultimately might exceed the handling capacity of the printer software itself. After trial and error, a compromise resolution of 600 grid points was found to provide an adequately high resolution for the 3D printed samples and a manageable digital file.1. A 3D printer model (ProJet 3500 HD Max printer (3D Systems)) have been used to print the 3D contractors.
2. A contact angle goniometer (OCA machine, Data Physics, Germany) have been used to measure the contact angles.
3. Electron microscopy (JEOL FESEM6301F) have been use to generate micrographs.
4. Atomic force microscopy (AFM; Nanosurf EasyScan 2 Flex, Switzerland) have been used to measure the surface roughness.
5. MATLAB R2017b have been used to design Schwarz-P and Gyroid 3D contractors.
6. Openscad software have been used to design cylindrical-based 3D contractor.
7. A homogenizer (ULTRA-TURRAX, T 25 basic, IKA) was used to mix the oil with water.
8. A Malvern Mastersizer X was used to measure oil droplets size distributions.
9. A turbidity meter (EUTECH TN-100, Thermo-Scientific) was used to determine the oil concentration in the feed and permeate.
10. The demulsification of the oil-in-water emulsions was carried out by using a vacuum filtration setup.Excel file sheet have been used to arrange the raw data. PowerPoint file have been used to mange the micro graph
Dataset for "Quantitative analysis of anti-resonance in single-ring, hollow-core fibres"
No full textThis dataset contains the data used to create Figures 2 to 5 in the paper, "Quantitative analysis of anti-resonance in single-ring, hollow-core fibres". The data represents the confinement loss of jacketed and unjacketed single-ring, hollow-core fibres and of a reference model consisting of concentric glass and air layers. The different Figures, and the related datasets, show the dependence of the confinement loss on the structural parameters of the fibres. Data for jacketed and unjacketed fibres is calculated using the commercial finite-element solver, COMSOL Multiphysics. Data for the reference model is calculated with an in-house code.Full details of the methodology may be found in the associated paper.The spreadsheets are in MS Excel (.xslx) format and are named after the Figure and type of fibre to which each relates. Each spreadsheet contains an "Information" sheet that provides full details of the data. Raw data from the COMSOL Multiphysics (https://uk.comsol.com/) calculations is provided, together with the processing used to produce the final data used in the paper.
The text files are in fixed field format, and are named after the Figure to which each relates. The first line of each file describes the data contained in the file; the quantities have the same meaning as described in the respective spreadsheet
Dataset for "Winter thermal comfort and health in the elderly"
Get PDFThe data within this dataset was collected from 43 homes, all in Bath, UK, with at least one occupant aged 65 or over. Sensors were placed in the living rooms and bedrooms of the participating homes to measure temperature at 90-minute intervals throughout the phases of the project. There were four phases in total: November 2016 – March 2017; June 2017 – September 2017; November 2017 – March 2018; June 2018 – September 2018. Corresponding questionnaires were completed on a monthly basis throughout the phases of the project, gathering data about thermal comfort and health. Within this dataset the measured internal temperatures, participant self-reported thermal comfort and health problems are contained in either Excel or CSV files.Longitudinal Temperature Monitoring - Between November 2016 until March 2017 and November 2017 until March 2018, sensors were deployed in the 43 participating homes measuring internal temperatures (in the living room and bedroom) at 90 minute intervals.iButton DS1922L sensors were used
Dataset for 'Exercise snacking to improve muscle function in healthy older adults: A pilot study'
No full textThis dataset contains baseline participant characteristics (age, sex, height, weight, Short Physical Performance Battery score, 60 second sit-to-stand score, habitual physical activity level (provided as daily energy expenditure/basal metabolic rate and time spent in age determined physical activity thresholds), and dietary intake of carbohydrate, protein, and fat, ant total energy intake). Pre- and post-intervention (28-days of exercise snacking or control) data is provided for the following variables: physical function characteristic (60 second sit-to-stand score and associated rating of perceived exertion for the test, and velocity, force, and power variables of leg pressing performance), anthropometric characteristics (calf and thigh muscle cross-sectional areas, and total lean mass, leg lean mass, and percentage body fat), and physical activity level and daily energy intake with total carbohydrate, fat, and protein intake relative to body mass. This dataset is to accompany the manuscript 'Exercise snacking to improve muscle function in healthy older adults: A pilot study' submitted for publication to the Journal of Aging Research.Full details of the methodology used may be found in sections 2 and 3 of the associated paper
Dataset for "Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers"
No full textReduced X-ray reflectometry dataset associated with Diamond Light Source experiment SI10526-1, and neutron reflectometry dataset associated with Institut Laue-Langevin experiment 9-13-612, used in the publication "Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers". The datasets are associated with the X-ray reflectometry of DLPC, DMPC, DPPC, and DMPG at the interface between a 1:2 mixture of choline chloride:glycerol and air, and the neutron reflectometry of DMPC and DPPC at the same interface (two isotopic contrasts).Within this dataset are both X-ray reflectometry (XRR) and neutron reflectometry (NR) datasets. These were collected at the Diamond Light Source beamline I07 and Institut Laue Langevin instrument FIGARO respectively.
The README.md file includes details of the specific lipid and surface pressure for each datafile.These data are presented as received following the experiment and the on-site data reduction process.XRR measurements were taken on I07 at Diamond Light Source, at 12.5 keV photon energy using the double-crystal-deflector. 4 The reflected intensity was measured in a momentum transfer range from 0.018 Å=1 to 0.7 Å=1. The data were normalised with respect to the incident beam and the background was measured from off-specular reflection and subsequently subtracted. Samples were equilibrated for at least one hour and preserved under an argon atmosphere to minimise the adsorption of water by the subphase.
XRR data were collected for each of the lipids, DLPC, DMPC, DPPC and DMPG at four surface pressures (DLPC: 20, 25, 30, and 35 mNm=1, DMPC: 20, 25, 30, and 40 mNm=1 , DPPC: 15, 20, 25, and 30 mNm=1, DMPG: 15, 20, 25, and 30 mNm=1), as measured with an aluminium Wilhelmy plate; all measurements were conducted at 22 ◦C. The aluminium Wilhelmy plate was used over a traditional paper plate due to the low wetability of paper by the DES.
The NR experiments were performed on FIGARO at the Institut Laue-Langevin using the time-of-flight method. 5 Data at two incident angles of 0.62◦ and 3.8◦ were measured to provide a momentum transfer range from 0.005 Å=1 to 0.18 Å=1 . Two surface pressures for each system and contrast was measured (DMPC: 20 and 25 mNm=1 , DPPC: 15 and 20 mNm=1 ). Similar to the X-ray procedure, samples were given enough time to equilibrate (at least two hours), kept under an inert atmosphere, and all measurements were conducted at 22 ◦C
'On Fast Matrix Inversion' Cancellations Demonstration Worksheet
No full textA Maple (2018) worksheet created to demonstrate cancellations found in the accompanying paper 'On Fast Matrix Inversion by Fast Matrix Multiplication', written by Zak Tonks and published on ArXiV. This worksheet also describes and demonstrates additional effects mentioned in the paper, such as the use of padding on the new object "Delta" in the fraction free case.Worksheet written, run, and saved by Zak Tonks, November 2018 using Maple 2018.0.Written and run using Maple 2018.0, running on a PC running Windows 10 Pro, i5-2500 processor 3.3GHz, 16GB RAM. Worksheet presented for viewing at least, but one should be able to run successfully in a few minutes on any processor at least as good. Licensed copy of Maple required to view, tested and verified working in earliest version Maple 2017, but may run in earlier versions as no particular packages used
Dataset for "Surface-Controlled Water Flow in Nanotube Membranes"
No full textThis dataset includes raw data for the results presented in the article "Surface-Controlled Water Flow in Nanotube Membranes" and specifically for permeance data (Figure 5 in the article), Raman and X-ray photoelectron spectroscopy (XPS) (Figure 2 in the article), surface zeta potential calculation and additional micrography as applied to carbon nanotube (CNT) and carbon nitride nanotube (CNNT) membranes.Full details of the methodology may be found in the associated manuscript. See the "Characterization of CNNTs Membranes" for details of the field emission scanning electron microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy. See the "Computational Methodology" section for details concerning the normalised permeance data. See the manuscript's supporting information for details concerning the surface zeta potential raw data.Within the X-ray photoelectron spectroscopy data, "B.E." stands for "Binding Energy"
Dataset for "AlN overgrowth of nano-pillar-patterned sapphire with different offcut angle by metalorganic vapor phase epitaxy"
No full textThis dataset contains scanning electron microscopy (SEM) images of nano-pillar-patterned sapphire created via Displacement Talbot Lithography and Inductively coupled plasma dry etching.Secondary electron images were captured using a Hitachi S-4300 scanning electron microscope (SEM). An accelerating voltage of 5 kV was used to collect the imagesDTL patternings have been performed on 2-inch sapphire wafers. A stack of two layers was spin-coated at 3000 rpm to obtain a ~ 270 nm bottom antireflective coating (BARC) (Wide 30W – Brewer Science) layer thickness, followed by either a layer of high-contrast positive resist (Dow® Ultra-i 123 diluted with Dow® EC11 solvent). A bake at 150°C of the BARC enables a wet-developable process and thus to create an undercut profile. DTL (PhableR 100, Eulitha) was then used to expose the resist with a coherent 375 nm light source with an energy density of 1 mW.cm-2 (Fig. 1a). A 1 μm pitch with 550 nm opening mask was employed which result in a Talbot length of 3.80 μm. A Gaussian velocity integration was applied and 8 Talbot lengths travel distance has been chosen to assure a homogeneous integration on several Talbot motifs. After a certain exposure time (which defines the exposure dose), the sample was baked for 1 min 30 sec at 120°C on a hot plate. The wafer was developed in MF-CD-26 for 180 to 240 sec (depending on the dose employed). The undercut profile created in the BARC after exposure and development was employed as a lift-off layer. 200 nm Ni layers were deposited via e-beam evaporation to produce metal masks in the circular opening at the surface of the wafer. Subsequent lift-off was achieved by soaking the wafer in MF-CD-26 developer. The wafers were cleaned in a 2 min reactive-ion etching (RIE) oxygen plasma to remove any BARC residue. Then, an ICP dry etch system was used to create nano-pillars in sapphire substrates. The experiments were performed with a Cl2/BCl3/Ar chemistry of 5/50/5 sccm, a temperature of 5°C, a pressure of 8 mTorr, 100 W RF power and 600 W ICP source power. Finally, the masks were etched away in aqua-regia solution (HCl:HNO3, 3:1)
Processed Lake Tahoe and Lake Geneva Water Levels
No full textThis processed data set contains the water level elevation in Lake Tahoe (2013-2015) and Lake Geneva (1974-2013). The higher frequency oscillations in the data show the periods and damping of the surface seiches in both lakes. In Geneva, there are three points where this data was measured and how the water level at the different points at the same time varies indicates further properties of the seiche.The time series data used in the Random Decrement Technique (RDT) analysis of Lake Geneva took the form of water elevation data collected at three locations; location 2026, 2027 and 2028. This data had a sampling rate of 10 minutes and was continuously collected between 00:00 on 1 January 1974 and 23:50 on 7 January 2013.
The RDT analysis for Lake Tahoe was carried out using water pressure head data collected at a buoy located at Homewood. Three time-series data sets were utilized in the analysis; 30 July 2013 00:00:00 to 6 December 2013 23:59:30, 1 January 2014 00:00:00 to 10 May 2014 23:59:30, 6 January 2015 00:00:00 to 15 May 2015 23:59:30. All data had a sampling rate of 30 seconds.The raw Lake Geneva data was collected by the Swiss Federal Office for the Environment and was provided by Damien Bouffard of the Swiss Federal Institute of Aquatic Science and Technology. The files were received as ascii files, cleaned, and converted to the Matlab files provided here.
The raw Lake Tahoe data was provided as csv files by Geoff Schladow of the University of California at Davis and converted to the Matlab files here for the RDT analysis.The processed data is in Matlab format and must be viewed using Matlab. For access to the original data files, please contact Damien Bouffard or Geoff Schladow
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇