M. Gelfusa

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.

UMEL: A new regression tool to identify measurement peaks in LIDAR/DIAL systems for environmental physics applications

Recently, surveying large areas in an automatic way, for early detection of both harmful chemical agents and forest fires, has become a strategic objective of defence and public health organisations. The Lidar and Dial techniques are widely recognized as a cost-effective alternative to monitor large portions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi Event Locator, is applied to the problem of automatically identifying the time location of peaks in Lidar and Dial measurements for environmental physics applications. This analysis technique improves various aspects of the measurements, ranging from the resilience to drift in the laser sources to the increase of the system sensitivity. The method is also fully general, purely software, and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data of various instruments acquired during several experimental campaigns in the field.

Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

Over the last few years progress has been made on the front of disruption prediction in tokamaks. The less forgiving character of the new metallic walls at JET emphasized the importance of disruption prediction and mitigation. Being able not only to predict but also classify the type of disruption will enable one to better choose the appropriate mitigation strategy. From this perspective, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been applied to the JET disruption database. This approach allows the error bars of the measurements to be taken into account and has proved to clearly outperform the more traditional classification methods based on the Euclidean distance. The developed technique with the highest success rate manages to identify the type of disruption with 85% confidence, several hundreds of ms before the thermal quench. Therefore, the combined use of this method and the more traditional disruption predictors would significantly improve the mitigation strategy on JET and could contribute to the definition of an optimized approach for ITER.

Raman water vapour concentration measurements for reduction of false alarms in forest fire detection

Forest fires can be the cause of environmental catastrophe, with the natural outcomes of serious ecological and economic damages, together with the possibility to endanger human safety. At the aim to reduce this catastrophe several author have been shown that the Laser light scattering can be uses to reveals the particulate emitted in the smoke. Infact experimental and theoretical investigations have shown that lidar is a powerful tool to detect the tenuous smoke plumes produced by forest fires at an early stage. In early 90s Arbolino and Andreucci have shown the theoretical possibility to detect the particulate emitted in atmosphere from smoke forest fire. Vilar at all have shown experimentally the possibility to measure the density variation in atmosphere due to plume emitted in forest fire event. Gaudio at all. have already shown that it is possible to evaluate water vapor emitted in smoke of vegetable fuel using a CO2 dial system. In this paper a theoretical model to evaluate the capabilities of a lidar system in fire surveillance of wooded areas will be presented. In particular we intend propose a technique to minimizing the false alarm in the detection of forest fire by lidar based on a measurement of second components emitted in a combustion process. Usually to detect a fire alarm a rapid increase of aerosol amount is measured. If the backscattering signal report a peak, the presences of a forest fire will be probable. Our idea to confirm this hypothesis is measure the second components emitted in a forest fire at the aim to minimize the false alarm. The simulated measurements of the humidity amount within the smoke plume will be carried out by means of Raman analysis. Fixing the burning rate of the vegetable-fuels, the maximum range of detection will be evaluated.

Numerical simulations as tool to predict chemical and radiological hazardous diffusion in case of nonconventional events

CFD (Computational Fluid Dynamics) simulations are widely used nowadays to predict the behaviour of fluids in pure research and in industrial applications. This approach makes it possible to get quantitatively meaningful results, often in good agreement with the experimental ones. The aim of this paper is to show how CFD calculations can help to understand the time evolution of two possible CBRNe (Chemical-Biological-Radiological-Nuclear-explosive) events: (1) hazardous dust mobilization due to the interaction between a jet of air and a metallic powder in case of a LOVA (Loss Of Vacuum Accidents) that is one of the possible accidents that can occur in experimental nuclear fusion plants; (2) toxic gas release in atmosphere. The scenario analysed in the paper has consequences similar to those expected in case of a release of dangerous substances (chemical or radioactive) in enclosed or open environment during nonconventional events (like accidents or man-made or natural disasters).

A new calibration code for the JET polarimeter

An equivalent model of JET polarimeter is presented, which overcomes the drawbacks of previous versions of the fitting procedures used to provide calibrated results. First of all the signal processing electronics has been simulated, to confirm that it is still working within the original specifications. Then the effective optical path of both the vertical and lateral chords has been implemented to produce the calibration curves. The principle approach to the model has allowed obtaining a unique procedure which can be applied to any manual calibration and remains constant until the following one. The optical model of the chords is then applied to derive the plasma measurements. The results are in good agreement with the estimates of the most advanced full wave propagation code available and have been benchmarked with other diagnostics. The devised procedure has proved to work properly also for the most recent campaigns and high current experiments.

Early detection of small forest fire by dial technique

Forest fires can be the cause of serious environmental and economic damages. For this reason considerable effort has been directed toward forest protection and fire fighting. The means traditionally used for early fire detection mainly consist in human observers dispersed over forest regions. A significant improvement in early warning capabilities could be obtained by using automatic detection apparatus. In order to early detect small forest fires, the use of a dial system will be considered. A first evaluation of the lowest detectable concentration will be estimated by a numerical simulation. The theoretical model will be used also to get the capacities of a dial system in fire surveillance of wooded areas. Fixing the burning rate for several fuels, the maximum range of detection will be evaluated. The results of these simulations will be reported in the paper.

In-cell measurements of smoke backscattering coefficients using a CO2 laser system for application to lidar-dial forest fire detection

In the lidar-dial method, the amount of the water vapor present in the smoke of the vegetable fuel is detected to reduce the number of false alarms. We report the measurements of the smoke backscattering coefficients for the CO2 laser lines 10R20 and 10R18 as determined in an absorption cell for two different vegetable fuels (eucalyptus and conifer). These experimental backscattering coefficients enable us to determine the error to be associated to the water vapor measurements when the traditional first-order approximation is assumed. We find that this first- order approximation is valid for combustion rates as low as 100 g/s. C 2010

A statistical methodology to derive the scaling law for the H-mode power threshold using a large multi-machine database

In this paper, a refined set of statistical techniques is developed and then applied to the problem of deriving the scaling law for the threshold power to access the H-mode of confinement in tokamaks. This statistical methodology is applied to the 2010 version of the ITPA International Global Threshold Data Base v6b(IGDBTHv6b). To increase the engineering and operative relevance of the results, only macroscopic physical quantities, measured in the vast majority of experiments, have been considered as candidate variables in the models. Different principled methods, such as agglomerative hierarchical variables clustering, without assumption about the functional form of the scaling, and nonlinear regression, are implemented to select the best subset of candidate independent variables and to improve the regression model accuracy. Two independent model selection criteria, based on the classical (Akaike information criterion) and Bayesian formalism (Bayesian information criterion), are then used to identify the most efficient scaling law from candidate models. The results derived from the full multi-machine database confirm the results of previous analysis but emphasize the importance of shaping quantities, elongation and triangularity. On the other hand, the scaling laws for the different machines and at different currents are different from each other at the level of confidence well above 95%, suggesting caution in the use of the global scaling laws for both interpretation and extrapolation purposes.

Residual analysis of the equilibrium reconstruction quality on JET

An extended set of statistical tests, aimed at assessing the quality of the magnetic reconstructions in JET, obtained with the code EFIT using the external magnetic measurements, is described and the results reported in detail. In addition to the traditional analysis of the global distributions of the residuals (the difference between the actual measurements and their reconstructions from the equilibrium), to determine to what extent they approximate a Gaussian, more sophisticated correlation tests have been performed. Since EFIT solves a highly non-linear equation, tests adequate for multi-input multi-output, non-linear systems have been implemented. Not only the reconstruction of the pickup coil signals but also the accuracy of the plasma boundary has been investigated. The results indicate quite clearly that the errors in the reconstruction of the pickup coils are not negligible. The coils, whose residuals present skewed monomodal distributions (distributions asymmetric with respect to their maximum value), are affected by average errors of the order of more than one millitesla and multimodal distributions of the residuals (distributions presenting more than one local maximum) are quite common. Also the correlation of the residuals is typically outside the 95% limits for a good model in typically more than 70% of the cases. With regard to the plasma boundary, the situation is better since the errors in the distances of the plasma from the wall are typically of the order of 1?cm. On the other hand, in this case the autocorrelations of the residuals are also well outside the 95% confidence interval for random residuals. A detailed analysis of the correlations indicates that the main reasons for the imperfections in the magnetic reconstructions do not reside in the measurements, since there is no evidence of systematic errors or problems with the calibrations. Therefore, the main improvements are to be expected by refinements in the used equilibrium code EFIT, whose constraints and boundary conditions are probably not the most appropriate to model H mode plasmas.