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261. Multi-species impurity granule injection and mass deposition projections in NSTX-U discharges Authors

Author(s):
Lunsford, R.; Bortolon, A.; Roquemore, A.L.; Mansfield, D.K.; Jaworski, M.A.; Kaita, R.; Maingi, R.; Nagy, A.
Abstract:
By employing a neutral gas shielding (NGS) model to characterize impurity granule injection the pedestal atomic deposition for three different species of granule: lithium, boron, and carbon are determined. Utilizing the duration of ablation events recorded on experiments performed at DIII-D to calibrate the NGS model we are able to quantify the ablation rate and mass deposition location with respect to the plasma density profile. The species specific granule shielding constant is then used to model granule ablation within NSTX-U discharges. Simulations of 300, 500 and 700 micron diameter granules injected at 50 m/sec are presented for NSTX-U L-mode type plasmas as well as H-mode discharges with low natural ELM frequencies. Additionally, ablation calculations of 500 micron granules of each species are presented at velocities ranging from 50 � 150 m/sec. In H-mode type discharges these simulations show that the majority of the injected granule is ablated within or just past the steep gradient region of the discharge. At this radial position, the perturbation to the background plasma generated by the ablating granule can lead to conditions advantageous for the rapid triggering of an ELM crash event.
Type:
Dataset
Issue Date:
July 2017

263. Neutral recycling effects on ITG turbulence

Author(s):
Stotler, D.P.; Lang, J.; Chang, C.S.; Churchill, R.M.; Ku, S.-H.
Abstract:
The effects of recycled neutral atoms on tokamak ion temperature gradient (ITG) driven turbulence have been investigated in a steep edge pedestal, magnetic separatrix configuration, with the full-f edge gryokinetic code XGC1. Ion temperature gradient turbulence is the most fundamental and robust edge plasma instability, having a long radial correlation length and an ability to impact other forms of pedestal turbulence. The neutral atoms enhance the ITG turbulence, first, by increasing the ion temperature gradient in the pedestal via the cooling effects of charge exchange and, second, by a relative reduction in the ExB shearing rate.
Type:
Dataset
Issue Date:
August 2017

264. Noise correlations in the human brain and their impact on pattern classification

Author(s):
Bejjanki, Vikranth R.; da Silveira, Rava Azeredo; Cohen, Jonathan D.; Turk-Browne, Nicholas B.
Abstract:
Multivariate decoding methods, such as multivoxel pattern analysis (MVPA), are highly effective at extracting information from brain imaging data. Yet, the precise nature of the information that MVPA draws upon remains controversial. Most current theories emphasize the enhanced sensitivity imparted by aggregating across voxels that have mixed and weak selectivity. However, beyond the selectivity of individual voxels, neural variability is correlated across voxels, and such noise correlations may contribute importantly to accurate decoding. Indeed, a recent computational theory proposed that noise correlations enhance multivariate decoding from heterogeneous neural populations. Here we extend this theory from the scale of neurons to functional magnetic resonance imaging (fMRI) and show that noise correlations between heterogeneous populations of voxels (i.e., voxels selective for different stimulus variables) contribute to the success of MVPA. Specifically, decoding performance is enhanced when voxels with high vs. low noise correlations (measured during rest or in the background of the task) are selected during classifier training. Conversely, voxels that are strongly selective for one class in a GLM or that receive high classification weights in MVPA tend to exhibit high noise correlations with voxels selective for the other class being discriminated against. Furthermore, we use simulations to show that this is a general property of fMRI data and that selectivity and noise correlations can have distinguishable influences on decoding. Taken together, our findings demonstrate that if there is signal in the data, the resulting above-chance classification accuracy is modulated by the magnitude of noise correlations.
Type:
Dataset
Issue Date:
August 2017

265. Optimization of the angular orientation for a fast ion loss detector in a tokamak

Author(s):
Darrow, D.
Abstract:
A scintillator type fast ion loss detector measures the gyroradius and pitch angle distribution of superthermal ions escaping from a magnetically confined fusion plasma at a single location. Described here is a technique for optimizing the angular orientation of such a detector in an axisymmetric tokamak geometry in order to intercept losses over a useful and interesting ranges of pitch angle. The method consists of evaluating the detector acceptance as a function of the fast ion constants of motion, i.e. energy, canonical toroidal momentum, and magnetic moment. The detector acceptance can then be plotted in a plane of constant energy and compared with the relevant orbit class boundaries and fast ion source distributions. Knowledge of expected or interesting mechanisms of loss can further guide selection of the detector orientation. The example of a fast ion loss detector for the National Spherical Torus Experiment-Upgrade (NSTX-U) is considered.
Type:
Dataset
Issue Date:
January 2017

266. Overview of NSTX Upgrade Initial Results and Modelling Highlights

Author(s):
Menard, J.E.; Allain, J.P.; Battaglia, D.J.; Bedoya, F.; Bell, R.E.; Belova, E.; Berkery, J.W.; Boyer, M.D.; Crocker, N.; Diallo, A.; Ebrahimi, F.; Ferrraro, N.; Fredrickson, E.; Frerichs, H.; Gerhardt, S.; Gorelenkov, N.; Guttenfelder, W.; Heidbrink, W.; Kaita, R.; Kaye, S.M.; Kriete, D.M.; Kubota, S.; LeBlanc, B.P.; Liu, D.; Lunsford, R.; Mueller, D.; Myers, C.E.; Ono, M.; Park, J.-K.; Podesta, M.; Raman, R.; Reinke, M.; Ren, Y.; Sabbagh, S.A.; Schmitz, O.; Scotti, F.; Sechrest, Y.; Skinner, C.H.; Smith, D.R.; Soukhanovskii, V.; Stoltzfus-Dueck, T.; Yuh, H.; Wang, Z.; Waters, I.; Ahn, J.-W.; Andre, R.; Barchfeld, R.; Beiersdorfer, P.; Bertelli, N.; Bhattacharjee, A.; Boyle, D.; Brennan, D.; Buttery, R.; Capece, A.; Canal, G.; Canik, J.; Chang, C.S.; Darrow, D.; Delgado-Aparicio, L.; Domier, C.; Ethier, S.; Evans, T.; Ferron, J.; Finkenthal, M.; Fonck, R.; Gan, K.; Gates, D.; Goumiri, I.; Gray, T.; Hosea, J.; Humphreys, D.; Jarboe, T.; Jardin, S.; Jaworski, M.A.; Koel, B.; Kolemen, E.; Ku, S.; LaHaye, R.J.; Levinton, F.; Luhmann Jr., N.; Maingi, R.; Maqueda, R.; McKee, G.; Meier, E.; Myra, J.; Perkins, R.; Poli, F.; Rhodes, T.; Riquezes, J.; Rowley, C.; Russell, D.; Schuster, E.; Stratton, B.; Stutman, D.; Taylor, G.; Tritz, K.; Wang, W.; Wirth, B.; Zweben, S.J.
Abstract:
The National Spherical Torus Experiment (NSTX) has undergone a major upgrade, and the NSTX Upgrade (NSTX-U) Project was completed in the summer of 2015. NSTX-U first plasma was subsequently achieved, diagnostic and control systems have been commissioned, H-Mode accessed, magnetic error fields identified and mitigated, and the first physics research campaign carried out. During 10 run weeks of operation, NSTX-U surpassed NSTX-record pulse-durations and toroidal fields, and high-performance ~1MA H-mode plasmas comparable to the best of NSTX have been sustained near and slightly above the n=1 no-wall stability limit and with H-mode confinement multiplier H98y2 above 1. Transport and turbulence studies in L-mode plasmas have identified the coexistence of at least two ion-gyro-scale turbulent micro-instabilities near the same radial location but propagating in opposite (i.e. ion and electron diamagnetic) directions. These modes have the characteristics of ion-temperature gradient and micro-tearing modes, respectively, and the role of these modes in contributing to thermal transport is under active investigation. The new second more tangential neutral beam injection was observed to significantly modify the stability of two types of Alfven Eigenmodes. Improvements in offline disruption forecasting were made in the areas of identification of rotating MHD modes and other macroscopic instabilities using the Disruption Event Characterization and Forecasting (DECAF) code. Lastly, the Materials Analysis and Particle Probe (MAPP) was utilized on NSTX-U for the first time and enabled assessments of the correlation between boronized wall conditions and plasma performance. These and other highlights from the first run campaign of NSTX-U are described.
Type:
Dataset
Issue Date:
October 2017

267. Sensitivity of WallDYN material migration modeling to uncertainties in mixed-material surface binding energies

Author(s):
Nichols, J.H.; Jaworski, M.A.; Schmid, K.
Abstract:
The WallDYN package has recently been applied to a number of tokamaks to self-consistently model the evolution of mixed-material plasma facing surfaces. A key component of the WallDYN model is the concentration-dependent surface sputtering rate, calculated using SDTRIM.SP. This modeled sputtering rate is strongly influenced by the surface binding energies (SBEs) of the constituent materials, which are well known for pure elements but often are poorly constrained for mixed-materials. This work examines the sensitivity of WallDYN surface evolution calculations to different models for mixed-material SBEs, focusing on the carbon/lithium/oxygen/deuterium system present in NSTX. A realistic plasma background is reconstructed from a high density, H-mode NSTX discharge, featuring an attached outer strike point with local density and temperature of 4e20 m^-3 and 4 eV, respectively. It is found that various mixed-material SBE models lead to significant qualitative and quantitative changes in the surface evolution profile at the outer divertor, with the highest leverage parameter being the C-Li binding model. Uncertainties of order 50%, appearing on time scales relevant to tokamak experiments, highlight the importance of choosing an appropriate mixed-material sputtering representation when modeling the surface evolution of plasma facing components. These results are generalized to other fusion-relevant materials with different ranges of SBEs.
Type:
Dataset
Issue Date:
2017

268. Stabilizing effect of resistivity towards ELM-free H-mode discharge in lithium-conditioned NSTX

Author(s):
Banerjee, D.; Zhu, P.; Maingi, R.
Abstract:
Linear stability analysis of the national spherical torus experiment (NSTX) Li-conditioned ELM-free H-mode equilibria is carried out in the context of the extended magneto-hydrodynamic (MHD) model in NIMROD. The purpose is to investigate the physical cause behind edge localized mode (ELM) suppression in experiment after the Li-coating of the divertor and the first wall of the NSTX tokamak. Besides ideal MHD modeling, including finite-Larmor radius effect and two-fluid Hall and electron diamagnetic drift contributions, a non-ideal resistivity model is employed, taking into account the increase of Z eff after Li-conditioning in ELM-free H-mode. Unlike an earlier conclusion from an eigenvalue code analysis of these equilibria, NIMROD results find that after reduced recycling from divertor plates, profile modification is necessary but insufficient to explain the mechanism behind complete ELMs suppression in ideal two-fluid MHD. After considering the higher plasma resistivity due to higher Z eff , the complete stabilization could be explained. A thorough analysis of both pre-lithium ELMy and with-lithium ELM-free cases using ideal and non-ideal MHD models is presented, after accurately including a vacuum-like cold halo region in NIMROD to investigate ELMs.
Type:
Dataset
Issue Date:
July 2017

269. Suppression of Alfvén modes on NSTX-U with outboard beam injection

Author(s):
Fredrickson, E.D.; Belova, E.V.; Battaglia, D.J.; Bell, R.E.; Crocker, N.A.; Darrow, D.S.; Diallo, A.; Gerhardt, S.P.; Gorelenkov, N.N.; LeBlanc, B.P.; Podesta, M.
Abstract:
In this paper we present data from experiments on NSTX-U where it is shown for the first time that small amounts of high pitch-angle beam ions can strongly suppress the counter-propagating Global Alfvén Eigenmodes (GAE). GAE have been implicated in the redistribution of fast ions and modification of the electron power balance in previous experiments on NSTX. The ability to predict the stability of Alfvén modes, and developing methods to control them, is important for fusion reactor like the International Tokamak Experimental Reactor (ITER) which are heated by a large population of non-thermal, super-Alfvénic ions consisting of fusion generated alphas and beam ions injected for current profile control. We present a qualitative interpretation of these observations using an analytic model of the Doppler-shifted ion-cyclotron resonance drive responsible for GAE instability which has an important dependence on k⊥ρL. A quantitative analysis of this data with the HYM stability code predicts both the frequencies and instability of the GAE prior to, and suppression of the GAE after the injection of high pitch-angle beam ions.
Type:
Dataset
Issue Date:
June 2017

270. The Structured `Low Temperature' Phase of the Retinal Population Code

Author(s):
Ioffe, Mark Lev; Berry II, Michael J.
Abstract:
Recent advances in experimental techniques have allowed the simultaneous recordings of populations of hundreds of neurons, fostering a debate about the nature of the collective structure of population neural activity. Much of this debate has focused on the empirical findings of a phase transition in the parameter space of maximum entropy models describing the measured neural probability distributions, interpreting this phase transition to indicate a critical tuning of the neural code. Here, we instead focus on the possibility that this is a first-order phase transition which provides evidence that the real neural population is in a `structured', collective state. We show that this collective state is robust to changes in stimulus ensemble and adaptive state. We find that the pattern of pairwise correlations between neurons has a strength that is well within the strongly correlated regime and does not require fine tuning, suggesting that this state is generic for populations of 100+ neurons. We find a clear correspondence between the emergence of a phase transition, and the emergence of attractor-like structure in the inferred energy landscape. A collective state in the neural population, in which neural activity patterns naturally form clusters, provides a consistent interpretation for our results.
Type:
Dataset
Issue Date:
2017