196,924 research outputs found
The experimental setup of FAMU to measure the proton Zemach radius
No full textThe FAMU experiment data acquisition is approaching. During September 2022 the full experimental setup is going to measure for the first time the muonic hydrogen ground state hyperfine splitting and obtain a precise measurement of the proton Zemach radius, shedding some new light on the proton radius puzzle. This result will not be possible without a complete system which joins nuclear and laser physics. The FAMU setup is formed by a
gas cryogenic target filled with a mixture of hydrogen and oxygen in which muons injected from the RIKEN-RAL facility (UK) are stopped. The muonic hydrogen produced is then exposed to a tunable infrared laser beam, unique for its energy and narrow linewidth, able to induce the hyperfine energy jump. The transition will be measured as a variation of the muonic transfer rate from hydrogen to oxygen, observed through the detection of the X-rays
emitted during the de-exitation of muonic oxygen. This presentation will describe the final setup which is being installed in all its parts
Performance limiting MHD phenomena in fusion devices: physics and active control
No full textIn this thesis different aspects of MagnetoHydroDynamic phenomena that limit plasma performance and confinement in toroidal pinch devices will be addressed.
The thesis contains original work carried out in two different devices: the Joint European Torus (JET) tokamak, and the RFX-mod Reversed Field Pinch (RFP), which are both the largest magnetic confinement devices in operation for their configuration.
In the JET device focus was put on Neoclassical Tearing Modes (NTMs), which are resistive instabilities that tear magnetic field lines and reconnect them forming magnetic field islands. With the aim of studying the NTM physics, two radial localization techniques for magnetic islands have been developed, and their outputs have been compared with q profiles obtained with a Motional Stark Effect diagnostic. One of the studied localization techniques has been also used in a non conventional way to reconstruct the NTM m number spectrum, and to extract new
information on the tearing-kink structure of the mode. The impact of NTMs on JET advanced tokamak discharges has been documented, with the ultimate aim of quantifying the loss in plasma confinement induced by the mode as a function of the island radial localization.
Other chirping modes were encountered in JET, which are thought to be driven by energetic particles and dubbed q=2 fishbones. Their experimental signature and impact on the plasma discharge have been studied.
In the RFX-mod device the addressed topic was the study and control of Resistive Wall Modes (RWMs) in RFP configuration. The RWM is a branch of the ideal kink mode that grows on the time scale of current diffusion in the wall.
First of all a RWM growth rate database in RFX-mod was created, and it was subsequently used as a standard growth rate reference in the analysis of the couplings between different m and n harmonics.
Advanced feedback control topics were addressed as well, such as the development and benchmark of a dynamical RWM control simulator, and the RWM stabilization in control experiments using various sets of active saddle coils.In questa tesi saranno affrontati i diversi aspetti dei fenomeni magnetoidrodinamici che limitano le prestazioni ed il confinamento degli esperimenti toroidali di tipo pinch.
La tesi contiene il lavoro originale portato avanti in due diverse macchine, che sono entrambe i più grandi esperimenti a confinamento magnetico in operazione per rispettive configurazioni: il tokamak Joint European Torus (JET) ed il Reversed Field Pinch (RFP) RFX-mod.
Nel tokamak JET l’attività di ricerca si è concentrata sui Neoclassical Tearing Modes (NTM), che sono delle instabilità resistive che rompono le linee di campo magnetico e le riconnettono, formando delle isole di campo magnetico. Allo scopo di studiare la fisica dei NTM, sono state sviluppate due tecniche per la localizzazione radiale delle isole magnetiche, ed i risultati prodotti sono stati confrontati con i profili radiali di q ottenuti per mezzo della diagnostica Motional Stark Effect.
Una delle tecniche di localizzazione studiate è stata anche usata in modo non convenzionale per ricostruire lo spettro del numero d’onda m poloidale dei NTM, e per ricavare informazioni sulla struttura kink-tearing di queste instabilità. E’ stato pure documentato l’impatto dei NTM sulle scariche advanced tokamak, allo scopo di quantificare il peggioramento nel confinamento del plasma che queste inducono, in funzione della localizzazione radiale dell’isola magnetica da loro generata.
Durante l’attività su JET sono state incontrate anche delle altre instabilità, che si ritiene siano eccitate dalla popolazione di particelle veloci nel plasma, e che sono soprannominate fishbone q = 2. Sono state caratterizzate le loro evidenze sperimentali ed il loro impatto sugli impulsi di plasma.
Nel RFP RFX-mod il lavoro è stato concentrato sullo studio e controllo dei Resistive Wall Modes (RWM), che sono una branca dei modi kink ideali che cresce selle scale dei tempi della diffusione delle correnti all’interno delle strutture conduttrici attorno al plasma.
Inizialmente è stato creato un database contenente i tassi di crescita di tutte le instabilità di tipo RWM rilevate in RFX-mod, ed il database è stato in seguito usato come riferimento nell’analizzare gli accoppiamenti tra le diverse armoniche m ed n dei RWM.
Sono stati affrontati anche problemi di controllo in feedback avanzato, come lo sviluppo ed il benchmark di un simulatore dinamico del controllo attivo RWM, e la sperimentazione del controllo RWM usando diversi gruppi di bobine attive
Stacking of predictors for the automatic classification of disruption types to optimize the control logic
No full textNowadays, disruption predictors, based on machine learning techniques, can perform well but they typically do not provide any information about the type of disruption and cannot predict the time remaining before the current quench. On the other hand, the automatic identification of the disruption type is a crucial aspect required to optimize the remedial actions and a prerequisite to forecasting the time left for intervening. In this work, a stack of machine learning tools is applied to the task of automatic classification of the disruption types. The strategy is implemented from scratch and completely adaptive; the predictors start operating after the first disruption and update their own models, following the evolution of the experimental program, without any human intervention. Moreover, they are designed to implement a form of transfer learning, in the sense that they identify autonomously the most important disruption classes, generating new ones when necessary. The results obtained are very encouraging in terms of both prediction performance and classification accuracy. On the other hand, regarding the narrowing of the warning times, some progress has been achieved, but new techniques will have to be devised to obtain fully satisfactory properties
Thermal conductivity modeling of refrigerant mixtures in a three-parameter corresponding states format.
No full textDr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
Stacking of predictors for the automatic classification of disruption types to optimise the control logic
No full textNowadays, disruption predictors, based on machine learning techniques, can perform well but they typically do not provide any information about the type of disruption and cannot predict the time remaining before the current quench. On the other hand, the automatic identification of the disruption type is a crucial aspect required to optimize the remedial actions and a prerequisite to forecasting the time left for intervening. In this work, a stack of machine learning tools is applied to the task of automatic classification of the disruption types. The strategy is implemented from scratch and completely adaptive; the predictors start operating after the first disruption and update their own models, following the evolution of the experimental program, without any human intervention. Moreover, they are designed to implement a form of transfer learning, in the sense that they identify autonomously the most important disruption classes, generating new ones when necessary. The results obtained are very encouraging in terms of both prediction performance and classification accuracy. On the other hand, regarding the narrowing of the warning times, some progress has been achieved, but new techniques will have to be devised to obtain fully satisfactory properties
A rule-based method to match Software Patterns against UML Models
No full textAbstractIn a UML model, different aspects of a system are covered by different types of diagrams and this bears the risk that an overall system specification becomes barely tractable by the designer. When the model grows, it is likely that the architectural integrity will be compromised by extensions and bug-fixing operations. Hence, it is important to provide means to help designers to search in big models for particular instances of some variable schema of UML models (design patterns) they construct. This can help them both to find potential problems in the architecture design and to ensure that intended architectural choices had not been broken by mistake. In this paper we propose a rule-based method to find matches of design patterns into a UML model. The method is general enough to tackle most patterns and antipatterns
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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