Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “Fiber Bragg gratings”
Project STORM: monitoring the masonry of Michelangelo's Cloister, at the Baths of Diocletian, with Fiber Bragg Grating (FBG) sensors. RAW Dataset 2018 - 2019
<p>This dataset for monitoring the masonry of Michelangelo's Cloister at the Baths of Diocletian (Rome) was created by the University of Tuscia.<br> The measurements are carried out with a Fiber Bragg Grating (FBG) sensors, have been investigated:</p> <ul> <li>Strain of lesions (sensors S0 and S3);</li> <li>Temperature of masonry (sensors S1, S2 and S8);</li> <li>Humidity of masonry (sensors S4, S5, S6 and S7).</li> </ul> <p>The data produced by the sensors were automatically saved them every 30 seconds. The dataset is composed of the data raw obtained from October 2018 to May 2019 and separated by month in 8 sheets. In total more than 2 million values were registered, used to understand the slow hazard phenomena present on the monitored masonry.</p> <p>STORM (Safeguarding Cultural Heritage through Technical and Organisational Resources Management) is a HORIZON 2020 funded European Union Cultural Heritage project that aims at the protection of Cultural Heritage through a combination of technical and organizational resources (http://www.storm-project.eu).</p>
Project STORM: monitoring the masonry of Hall I, at the Baths of Diocletian, with Fiber Bragg Grating (FBG) sensors. RAW Dataset 2017 - 2019
<p>This dataset for monitoring the masonry of Hall I at the Baths of Diocletian (Rome) was created by the University of Tuscia.<br> The measurements are carried out with a Fiber Bragg Grating (FBG) sensors, have been investigated:</p> <ul> <li>Strain of lesions (sensors S0, S2 and S3);</li> <li>Temperature of masonry (sensors S1, and S8);</li> <li>Humidity of masonry (sensors S4, S5, S6 and S7).</li> </ul> <p>The data produced by the sensors were automatically saved them every 30 seconds. The dataset is composed of the data raw obtained from October 2017 to May 2019 and separated by month in 14 sheets. In total more than 4 million values were registered, used to understand the slow hazard phenomena present on the monitored masonry.</p> <p>STORM (Safeguarding Cultural Heritage through Technical and Organisational Resources Management) is a HORIZON 2020 funded European Union Cultural Heritage project that aims at the protection of Cultural Heritage through a combination of technical and organizational resources (http://www.storm-project.eu).</p>
Designing of Fiber Bragg Gratings for Long-distance Optical Fiber Sensing Networks
<p>Research data of <em>Modelling and Simulation in Engineering </em>journal article “Designing of Fiber Bragg Gratings for Long-distance Optical Fiber Sensing Networks”.</p> <p>Most optical sensors on the market are optical fiber Bragg grating (FBG) sensors with low reflectivity (typically 7-40%) and low side-lobe suppression (SLS) ratio (typically SLS <15dB), which prevents these sensors from being effectively used for long-distance remote monitoring and sensor network solutions. This research is based on designing the optimal grating structure of FBG sensors and estimating their optimal apodization parameters necessary for sensor networks and long-distance monitoring solutions. Gaussian, sine and raised sine apodizations are studied to achieve the main requirements, which are - maximally high reflectivity (at least 90%) and side-lobe suppression (at least 20 dB), as well as maximally narrow bandwidth (FWHM<0.2 nm), FBGs with uniform (without apodization). Results gathered in this research propose high-efficiency FBG grating apodizations, which can be further physically realized for optical sensor networks and long-distance (at least 40 km) monitoring solutions.</p> <p> </p>
Propagation of optical pulses through a periodic dielectric structure (Bragg Grating) designed as a delay line interferometer. Example of a designed fiber Bragg grating.
<p>Propagation of optical pulses through a periodic dielectric structure (Bragg Grating) designed as a delay line interferometer. <br> <br> A 9 cm fiber Bragg grating is designed (and fabricated) for this purpose.</p> <p>The top video shows the simulated propagation of a single optical pulse.</p> <p>The bottom video shows the simulated propagation of a sequence of optical pulses, with relative pi-phase shifts in the last pulse, showing both constructive and destructive interferences effect</p>
Data for publication: Developing self-calibrating system for fiber Bragg grating based guided wave sensing under changing temperature conditions
<p>Data for section 3 and section 4 Figure 7- Figure 12 i n. txt format for easy viewing without need for special licenses</p> <p>The work related to the automated system was supported by the Project ‘Guided waves based reference-free SHM using fiber Bragg grating sensors (REFFREE)’<br>(2020/39/D/ST8/00188) Granted by National Science Center, Poland.</p>
Data publication for "High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings"
<p><strong>Summary</strong></p> <p>This data publication supplements the manuscript "High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings" [1] with tabulated data. Furthermore, the provided Matlab and Python scrips allow to reproduce the data and can serve as a starting point for further investigations. They include a multi-objective optimization scheme, a robustness analysis with further optimizations focused on robustness and an investigation of the electrical properties. The following sections explain the contents of each directory and discuss dependencies on third-party software. For a detailed descriptions of the methods and the optimization and analysis pipeline we refer to the related paper [1].</p> <p><strong>Tabulated data</strong></p> <p>The contained text files refer to figures in the manuscript [1] as indicated by their names. Additional information is given in the headers.</p> <p><strong>Optimization</strong></p> <p>The optimization has been carried out with Matlab scripts (tested with version r2019b) which rely on the commercial FEM solver JCMsuite [2] (for a free trial licenses please refer to the homepage of <a href="http://jcmwave.com">JCMwave</a>). In order to run any of the supplied scripts you must edit the path to the installation directory of JCMsuite (5.2.1).</p> <p>The subdirectories <code>JCMsuite</code> and <code>Matlab</code> contain input files for JCMsuite and function definitions along with a recent version of RPExpand [3], respectively. Rerunning the scripts <code>optimization.m</code>, contained in each of the subdirectories <code>NIR</code>, <code>CBand</code> and <code>OBand</code>, will open the dashboard of the optimizer, which provides visualizations of the optimization progress. The target function is defined in <code>Matlab/coupling.m</code>.</p> <p>Wavelength scans of Purcell enhancement, coupling efficiency to a single mode fiber and collection efficiency into a numerical aperture of NA=0.8 have been carried out using interpolation based on modal expansions with RPExpand.</p> <p><strong>Robustness analysis</strong></p> <p>Along with the Python scripts used to run the robustness analysis and further optimizations, a visualization of all results have been added (e.g. <code>final_results/C_Band/robust_opt/figure_purcell_max.pdf</code>), which add to the results presented in figure 2 of the manuscript [1].</p> <p><strong>Electrical properties</strong></p> <p>The script <code>elCBG_capacitor_cylindrical_10_Rings_Ubias_sweep.py</code> is based on <a href="https://devsim.org/index.html">DEVSIM</a> [4]. Version 1.6.0 has been used to generate the original data, but for this data publication, it has been adapted to run with a current version. You can install the required packages, e.g., with Miniconda (22.11.1) running</p> <pre><code>conda install mkl sqlite zlib pip install numpy pandas devsim</code></pre> <p><strong>Bibliography</strong></p> <p>[1] Lucas Rickert, Fridtjof Betz, Matthias Plock, Sven Burger and Tobias Heindel: High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings (2022), http://arxiv.org/abs/2212.04883</p> <p>[2] https://jcmwave.com</p> <p>[3] Fridtjof Betz, Felix Binkowski, Sven Burger, RPExpand: Software for Riesz projection expansion of resonance phenomena, SoftwareX 15, 100763 (2021), https://doi.org/10.1016/j.softx.2021.100763</p> <p>[4] https://devsim.org/index.html</p>
Controllable Light Scattering on Fiber Bragg Gratings in Multimode Fibers: Tailoring Angular Emission for Advanced Fiber-Based Light
<p>The dataset consists of angular scattering patterns and transmission spectra for two fiber Bragg gratings. The scattering data is represented as 2-D arrays (images). The arrays are rectangular, where the longer side corresponds to the phi angle (azimuth) ranging from 0 to 2pi, and the shorter side represents the theta angle (polar angle) ranging from 0 to pi. To get the angle in rad per pixel just divide the corresponding arc length (p, 2pi) by the number of pixels on the axis.</p>
ScienceDex guides
Understand access before you commit
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.