13 research outputs found
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Robust Detection of Dynamical Change in Scalp EEG
We present a robust, model-independent technique for measuring changes in the dynamics underlying nonlinear time-serial data. We define indicators of dynamical change by comparing distribution functions on the attractor via L{sub 1}-distance and X{sup 2} statistics. We apply the measures to scalp EEG data with the objective of capturing the transition between non-seizure and epileptic brain activity in a timely, accurate, and non-invasive manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of dynamical change
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Problems in modeling TF ripple loss of fast alphas from a tokamak reactor
The present status of modeling TF ripple loss of fast alphas from tokamaks is summarized. The modeling issues are discussed, and several new aspects of this problem are described, including gyromotion, radial electric field, and sawtoothing. Existing models predict that TF ripple loss of fast alphas will have a low-to-moderate impact on the design of a tokamak engineering test reactor (ETR). 52 refs., 3 figs., 2 tabs
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Plasma performance of TFCX and JET with sawtoothing
The plasma performance is assessed for two tokamak reactor experiments, the Tokamak Fusion Core Experiment (TFCX) and the Joint European Torus (JET). Both machines appear ignitable for a reasonable range of transport assumptions
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Sensitivity studies on 3. 5-MeV alpha bombardment of a tokamak first wall
High-energy fusion-product losses to the first wall of a fusion reactor cause wall damage and may seriously contaminate the plasma with material ejected from the wall. Present studies extend previous results by considering the sensitivity of the loading to various parameters such as major-minor radii and plasma current. (MHR
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Sensitive Measures of Condition Change in EEG Data
We present a new, robust, model-independent technique for measuring condition change in nonlinear data. We define indicators of condition change by comparing distribution functions (DF) defined on the attractor for time windowed data sets via L{sub 1}-distance and {chi}{sup 2} statistics. The new measures are applied to EEG data with the objective of detecting the transition between non-seizure and epileptic brain activity in an accurate and timely manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of condition change
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Prospects for chaos control of machine tool chatter
The authors analyze the nonlinear tool-part dynamics during turning of stainless steel in the nonchatter and chatter regimes, toward the ultimate objective of chatter control. Their previous work analyzed tool acceleration in three dimensions at four spindle speeds. In the present work, the authors analyze the machining power and obtain nonlinear measures of this power. They also calculate the cycle-to-cycle energy for the turning process. Return maps for power cycle times do not reveal fixed points or (un)stable manifolds. Energy return maps do display stable and unstable directions (manifolds) to and from an unstable period-1 orbit, which is the dominant periodicity. Both nonchatter and chatter dynamics have the unusual feature of arriving at the unstable period-1 fixed point and departing from that fixed point of the energy return map in a single step. This unusual feature makes chaos maintenance, based on the well-known Ott-Grebogi-Yorke scheme, a very difficult option for chatter suppression. Alternative control schemes, such as synchronization of the tool-part motion to prerecorded nonchatter dynamics or dynamically damping the period-1 motion, are briefly discussed