9,426 research outputs found
Development of a system for remote sensing of ionospheric motions and microstructure - The Kinesonde in France, 1970
Kinesonde experiment for development of system for remote sensing of ionospheric motions and microstructur
A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation
Real-time monitoring of multiphase fluid flows with distributed fibre optic sensing has the potential to play a major role in industrial flow measurement applications. One such application is the optimization of hydrocarbon production to maximize short-term income, and prolong the operational lifetime of production wells and the reservoir. While the measurement technology itself is well understood and developed, a key remaining challenge is the establishment of robust data analysis tools that are capable of providing real-time conversion of enormous data quantities into actionable process indicators. This paper provides a comprehensive technical review of the data analysis techniques for distributed fibre optic technologies, with a particular focus on characterizing fluid flow in pipes. The review encompasses classical methods, such as the speed of sound estimation and Joule-Thomson coefficient, as well as their data-driven machine learning counterparts, such as Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Ensemble Kalman Filter (EnKF) algorithms. The study aims to help end-users establish reliable, robust, and accurate solutions that can be deployed in a timely and effective way, and pave the wave for future developments in the field.publishedVersio
The shell elliptical NGC2865: evolutionary population synthesis of a kinematically distinct core
We report on the discovery of a rapidly co-rotating stellar and gas component
in the nucleus of the shell elliptical NGC2865. The stellar component extends ~
0.51/h100 kpc along the major axis, and shows depressed velocity dispersion and
absorption line profiles skewed in the opposite sense to the mean velocity.
Associated with it is a young stellar population with enhanced \hbeta, lowered
Mg and same Fe indices relative to the underlying elliptical. Its recent star
formation history is constrained by considering ``bulge+burst'' models under 4
physically motivated scenarios, using evolutionary population synthesis.
Scenarios in which the nuclear component is formed over a Hubble time or
recently from continuous gas inflow are ruled out.
Our results argue for a gas-rich accretion or merger origin for the shells
and kinematic subcomponent in NGC2865. Arguments based on stellar populations
and gas dynamics suggest that one of the progenitors is likely a Sb or Sc
spiral. We demonstrate that despite the age and metallicity degeneracy of the
underlying elliptical, the age and metallicity of the kinematic subcomponent
can be constrained. This work strengthens the link between KDCs and shells, and
demonstrates that a KDC can be formed from a late merger.Comment: 26 pages, accepted for publication in MNRA
Contextual cropping and scaling of TV productions
This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0804-3. Copyright @ Springer Science+Business Media, LLC 2011.In this paper, an application is presented which automatically adapts SDTV (Standard Definition Television) sports productions to smaller displays through intelligent cropping and scaling. It crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. This approach allows a context-based composition of cropped images. It provides a differentiation between the original SD version of the production and the processed one adapted to the requirements for mobile TV. The system has been comprehensively evaluated by comparing the outcome of the proposed method with manually and statically cropped versions, as well as with non-cropped versions. Envisaged is the integration of the tool in post-production and live workflows
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data
The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400-2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r (2) = 0.61-0.88, RMSEmean = 12%-64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.Peer reviewe
Combined Unbalanced Distribution System State and Line Impedance Matrix Estimation
To address the challenges that the decarbonization of the energy sector is
bringing about, advanced distribution network management and operation
strategies are being developed. Many of these strategies require accurate
network models to work effectively. However, distribution network data are
known to contain errors, and attention has been given to techniques that allow
to derive improved network information. This paper presents a novel method to
derive line impedance values from smart meter measurement time series, with
realistic assumptions in terms of meter accuracy, resolution and penetration.
The method is based on unbalanced state estimation and is cast as a non-convex
quadratically constrained optimization problem. Both line lengths and impedance
matrix models can be estimated based on an exact nonlinear formulation of the
steady-state three-phase network physics. The method is evaluated on the IEEE
European Low Voltage feeder (906 buses) and shows promising results
Fatigue Assessment of Moorings for Floating Offshore Wind Turbines by Advanced Spectral Analysis Methods
The fatigue assessment of mooring lines for floating offshore wind turbines represents a challenging issue not only for the reliable design of the stationkeeping system but also for the economic impact on the installation and maintenance costs over the entire lifetime of the offshore wind farm. After a brief review about the state-of-art, the nonlinear time-domain hydrodynamic model of floating offshore wind turbines moored by chain cables is discussed. Subsequently, the assessment of the fatigue damage in the mooring lines is outlined, focusing on the combined-spectrum approach. The relevant fatigue parameters, due to the low-and wave-frequency components of the stress process, are estimated by two different methods. The former is based on the time-domain analysis of the filtered stress process time history. The latter, instead, is based on the spectral analysis of the stress process by two advanced methods, namely the Welch and Thomson ones. Subsequently, a benchmark study is performed, assuming as reference floating offshore wind turbine the OC4-DeepCWind semisubmersible platform, equipped with the 5 MW NREL wind turbine. The cumulative fatigue damage is determined for eight load conditions, including both power production and parked wind turbine situations. A comparative analysis between time-domain and spectral analysis methods is also performed. Current results clearly show that the endorsement of advanced spectral analysis methods can be helpful to improve the reliability of the fatigue life assessment of mooring lines
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