Adaptive quasi-unsupervised detection of smoke plume by lidar

The early detection of fire is one of the possible applications of LiDAR techniques. The smoke generated by a fire is mainly compounded of CO2, H2O, particulate, and other combustion products, which involve the local variation of the scattering of the electromagnetic wave at specific wavelengths. The increases of the backscattering coefficient are transduced in peaks on the signal of the backscattering power recorded by the LiDAR system, located exactly where the smoke plume is, allowing not only the detection of a fire but also its localization. The signal processing of the LiDAR signals is critical in the determination of the performances of the fire detection. It is important that the sensitivity of the apparatus is high enough but also that the number of false alarms is small, in order to avoid the trigger of useless and expensive countermeasures. In this work, a new analysis method, based on an adaptive quasi-unsupervised approach was used to ensure that the algorithm is continuously updated to the boundary conditions of the system, such as the weather and experimental apparatus issues. The method has been tested on an experimental campaign of 227 pulses and the performances have been analyzed in terms of sensitivity and specificity

Safety analysis in large volume vacuum systems like tokamak: Experiments and numerical simulation to analyze vacuum ruptures consequences

The large volume vacuum systems are used in many industrial operations and research laboratories. Accidents in these systems should have a relevant economical and safety impact. A loss of vacuum accident (LOVA) due to a failure of the main vacuum vessel can result in a fast pressurization of the vessel and consequent mobilization dispersion of hazardous internal material through the braches. It is clear that the influence of flow fields, consequence of accidents like LOVA, on dust resuspension is a key safety issue. In order to develop this analysis an experimental facility is been developed: STARDUST. This last facility has been used to improve the knowledge about LOVA to replicate a condition more similar to appropriate operative condition like to kamaks. By the experimental data the boundary conditions have been extrapolated to give the proper input for the 2D thermofluid-dynamics numerical simulations, developed by the commercial CFD numerical code. The benchmark of numerical simulation results with the experimental ones has been used to validate and tune the 2D thermofluid-dynamics numerical model that has been developed by the authors to replicate the LOVA conditions inside STARDUST. In present work, the facility, materials, numerical model, and relevant results will be presented. © 2014 A. Malizia et al

The Reciprocal Influence Criterion: An Upgrade of the Information Quality Ratio

Understanding and quantifying the mutual influence between systems remain crucial but challenging tasks in any scientific enterprise. The Pearson correlation coefficient, the mutual information, and the information quality ratio are the most widely used indicators, only the last two being valid for nonlinear interactions. Given their limitations, a new criterion is proposed, the reciprocal influence criterion, which is very simple conceptually and does not make any assumption about the statistics of the stochastic variables involved. In addition to being normalised as the information quality ratio, it provides a much better resilience to noise and much higher stability to the issues related to the determination of the involved probability distribution functions. A conditional version, to counteract the effects of confounding variables, has also been developed, showing the same advantages compared to the more traditional indicators. A series of systematic tests with numerical examples is reported, to compare the properties of the new indicator with the more traditional ones, proving its clear superiority in practically all respects

Data driven theory for knowledge discovery in the exact sciences with applications to thermonuclear fusion

In recent years, the techniques of the exact sciences have been applied to the analysis of increasingly complex and non-linear systems. The related uncertainties and the large amounts of data available have progressively shown the limits of the traditional hypothesis driven methods, based on first principle theories. Therefore, a new approach of data driven theory formulation has been developed. It is based on the manipulation of symbols with genetic computing and it is meant to complement traditional procedures, by exploring large datasets to find the most suitable mathematical models to interpret them. The paper reports on the vast amounts of numerical tests that have shown the potential of the new techniques to provide very useful insights in various studies, ranging from the formulation of scaling laws to the original identification of the most appropriate dimensionless variables to investigate a given system. The application to some of the most complex experiments in physics, in particular thermonuclear plasmas, has proved the capability of the methodology to address real problems, even highly nonlinear and practically important ones such as catastrophic instabilities. The proposed tools are therefore being increasingly used in various fields of science and they constitute a very good set of techniques to bridge the gap between experiments, traditional data analysis and theory formulation

Hardware prototyping and validation of a W-ΔDOR digital signal processor

Microwave tracking, usually performed by on ground processing of the signals coming from a spacecraft, represents a crucial aspect in every deep-space mission. Various noise sources, including receiver noise, affect these signals, limiting the accuracy of the radiometric measurements obtained from the radio link. There are several methods used for spacecraft tracking, including the Delta-Differential One-Way Ranging (ΔDOR) technique. In the past years, European Space Agency (ESA) missions relied on a narrowband ΔDOR system for navigation in the cruise phase. To limit the adverse effect of nonlinearities in the receiving chain, an innovative wideband approach to ΔDOR measurements has recently been proposed. This work presents the hardware implementation of a new version of the ESA X/Ka Deep Space Transponder based on the new tracking technique named Wideband ΔDOR (W-ΔDOR). The architecture of the new transponder guarantees backward compatibility with narrowband ΔDOR

A new class of indicators for the model selection of scaling laws in nuclear fusion

The development of computationally efficient model selection strategies represents an important problem facing the analysis of Nuclear Fusion experimental data, in particular in the field of scaling laws for the extrapolation to future machines, and image processing. In this paper, a new model selection indicator, named Model Falsification Criterion (MFC), will be presented and applied to the problem of choosing the most generalizable scaling laws for the power threshold to access the H-mode of confinement in Tokamaks. The proposed indicator is based on the properties of the model residuals, their entropy and an implementation of the data falsification principle. The model selection ability of the proposed criterion will be demonstrated in comparison with the most widely used frequentist (Akaike Information Criterion) and bayesian (Bayesian Information Criterion) indicators.Comment: 4 pages, 2 figure

Detection of Causal Relations in Time Series Affected by Noise in Tokamaks Using Geodesic Distance on Gaussian Manifolds

Modern experiments in Magnetic Confinement Nuclear Fusion can produce Gigabytes of data, mainly in form of time series. The acquired signals, composing massive databases, are typically affected by significant levels of noise. The interpretation of the time series can therefore become quite involved, particularly when tenuous causal relations have to be investigated. In the last years, synchronization experiments, to control potentially dangerous instabilities, have become a subject of intensive research. Their interpretation requires quite delicate causality analysis. In this paper, the approach of Information Geometry is applied to the problem of assessing the effectiveness of synchronization experiments on JET (Joint European Torus). In particular, the use of the Geodesic Distance on Gaussian Manifolds is shown to improve the results of advanced techniques such as Recurrent Plots and Complex Networks, when the noise level is not negligible. In cases affected by particularly high levels of noise, compromising the traditional treatments, the use of the Geodesic Distance on Gaussian Manifolds allows deriving quite encouraging results. In addition to consolidating conclusions previously quite uncertain, it has been demonstrated that the proposed approach permit to successfully analyze signals of discharges which were otherwise unusable, therefore salvaging the interpretation of those experiments.EURATOM 63305

Detection of pollutant sources in the atmosphere with Lidar/Dial techniques: Results of an experimental campaign in the south of Italy

In the last years, surveying large regions of the atmosphere in an automatic way, for early detection of pollutant sources in urban and industrial areas, has become a strategic objective of various public health organizations. The Lidar/Dial technique has become a well-established laser remote sensing method for atmosphere monitoring. It is often used to probe almost any level of the atmosphere and to acquire information necessary to validate theoretical models about different topics of atmospheric physics. It can also be deployed for environment surveying by monitoring particles, aerosols and molecules. For these reasons, an experimental campaign for evaluating the performances of a Lidar/Dial system in detecting pollutants (particulate and/or chemical compounds) has been carried out in an industrial area in the south of Italy. In this work, a homemade Lidar/Dial system (developed and built by the authors) and the results of the experimental campaign will be presented and discussed. © 2014 AEIT