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2. Analytic stability boundaries for compressional and global Alfven eigenmodes driven by fast ions. II. Interaction via Landau resonance.
- Author(s):
- Lestz, J.B.; Gorelenkov, N.N.; Belova, E.V.; Tang, S.X.; Crocker, N.A.
- Abstract:
- Conditions for net fast ion drive are derived for beam-driven, co-propagating, sub-cyclotron compressional (CAE) and global (GAE) Alfven eigenmodes driven by the Landau resonance with super-Alfvenic fast ions. Approximations applicable to realistic neutral beam distributions and mode characteristics observed in spherical tokamaks enable the derivation of marginal stability conditions for these modes. Such conditions successfully reproduce the stability boundaries found from numerical integration of the exact expression for local fast ion drive/damping. Coupling between the CAE and GAE branches of the dispersion due to finite \omega/\omega_{ci} and k_\parallel/k_\perp is retained and found to be responsible for the existence of the GAE instability via this resonance. Encouraging agreement is demonstrated between the approximate stability criterion, simulation results, and a database of NSTX observations of co-CAEs.
- Type:
- Dataset
- Issue Date:
- January 2020
3. Enhanced Pedestal H-mode at low edge ion collisionality on NSTX
- Author(s):
- Battaglia, D.J.; Guttenfelder, W.; Bell, R.E.; Diallo, A.; Ferraro, N.;, Fredrickson, E.; Gerhardt, S.P.; Kaye, S.M.; Maingi, R.; Smith, D.R.
- Abstract:
- The Enhanced Pedestal (EP) H-mode regime is an attractive wide-pedestal ELM-free high-betap scenario for NSTX-U and next-step devices as it achieves enhanced energy confinement (H98y,2 > 1.5), large normalized pressure (betaN > 5) and significant bootstrap fraction (f_BS > 0.6) at I_p/B_T = 2 MA/T. This regime is realized when the edge ion collisionality becomes sufficiently small that a positive feedback interaction occurs between a reduction in the ion neoclassical energy transport and an increase in the particle transport from pressure-driven edge instabilities. EP H-mode was most often observed as a transition following a large ELM in conditions with low edge neutral recycling. It is hypothesized that the onset of pressure-driven instabilities prior to the full recovery of the neutral density leads to a temporary period with elevated ion temperature gradient that triggers the transition to EP H-mode. Linear CGYRO and M3D-C1 calculations are compared to beam emission spectroscopy (BES) and magnetic spectroscopy in order to describe the evolution of the edge particle transport mechanisms during the ELM recovery and the saturated EP H-mode state. The observations are consistent with the hypothesis that the onset of pressure-driven edge instabilities, such as the KBM and kink-peeling, can be responsible for the increased particle transport in EP H-mode.
- Type:
- Dataset
- Issue Date:
- June 2020
4. MHD-blob correlations in NSTX
- Author(s):
- Zweben SJ; Fredrickson ED; Myra JR; Podesta M; Scotti F
- Abstract:
- This paper describes a study of the cross-correlations between edge fluctuations as seen in the gas puff imaging (GPI) diagnostic and low frequency coherent magnetic fluctuations (MHD) in H-mode plasmas in NSTX. The main new result was that large blobs in the SOL were significantly correlated with MHD activity the 3-6 kHz range in 21 of the 223 shots examined. There were also many other shots in which fluctuations in the GPI signal level and its peak radius Rpeak were correlated with MHD activity, but without any significant correlation of the MHD with large blobs. The structure and motion of the MHD is compared with that of the correlated blobs, and some possible theoretical mechanisms for the MHD-blob correlation are discussed.
- Type:
- Dataset
- Issue Date:
- May 2020
5. Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX
- Author(s):
- Woods, B. J. Q.; Duarte, V. N.; Fredrickson, E. D.; Gorelenkov, N. N.; Podestà, M.; Vann, R. G. L.
- Abstract:
- Abrupt large events in the Alfvenic and sub-Alfvenic frequency bands in tokamaks are typically correlated with increased fast-ion loss. Here, machine learning is used to speed up the laborious process of characterizing the behavior of magnetic perturbations from corresponding frequency spectrograms that are typically identified by humans. The analysis allows for comparison between different mode character (such as quiescent, fixed frequency, and chirping, avalanching) and plasma parameters obtained from the TRANSP code, such as the ratio of the neutral beam injection (NBI) velocity and the Alfven velocity (v_inj./v_A), the q-profile, and the ratio of the neutral beam beta and the total plasma beta (beta_beam,i / beta). In agreement with the previous work by Fredrickson et al., we find a correlation between beta_beam,i and mode character. In addition, previously unknown correlations are found between moments of the spectrograms and mode character. Character transition from quiescent to nonquiescent behavior for magnetic fluctuations in the 50200-kHz frequency band is observed along the boundary v_phi ~ (1/4)(v_inj. - 3v_A), where v_phi is the rotation velocity.
- Type:
- Dataset
- Issue Date:
- December 2019
6. Modeling of resistive plasma response in toroidal geometry using an asymptotic matching approach
- Author(s):
- Z. R. Wang; A. H. Glasser; D. Brennan; Y. Q. Liu; J-K. Park
- Abstract:
- The method of solving linear resistive plasma response, based on the asymptotic matching approach, is developed for full toroidal tokamaks by upgrading the Resistive DCON code [A.H. Glasser, Z.R. Wang and J.-K. Park, Physics of Plasmas, \textbf{23}, 112506 (2016)]. The derived matching matrix, asymptotically matching the outer and inner regions, indicates that the applied three dimension (3-D) magnetic perturbations contribute additional small solutions at each resonant surface due to the toroidal coupling of poloidal modes. In contrast, the resonant harmonic only affects the corresponding resonant surface in the cylindrical plasma. Since the solution of ideal outer region is critical to the asymptotic matching and is challenging to be solved in the toroidal geometry due to the singular power series solution at the resonant surfaces, systematic verification of the outer region $\Delta^\prime$ matrix is made by reproducing the well known analytical $\Delta^{\prime}$ result in [H.P. Furth, P.H. Rutherford and H. Selberg, The Physics of Fluids, \textbf{16}, 1054-1063 (1073)] as well as by making a quantitative benchmark with the PEST3 code [A. Pletzer and R.L. Dewar, J. Plasma Physics, \textbf{45}, 427-451 (1991)]. Finally, the reconstructed numerical solution of resistive plasma response from the toroidal matching matrix is presented. Comparing with the ideal plasma response, the global structure of the response can be affected by the small finite island at the resonant surfaces.
- Type:
- Dataset
- Issue Date:
- October 2020
7. Simulating pitch angle scattering using an explicitly solvable energy-conserving algorithm
- Author(s):
- Zhang, Xin; Fu, Yichen; Qin, Hong
- Abstract:
- Particle distribution functions evolving under the Lorentz operator can be simulated with the Langevin equation for pitch angle scattering. This approach is frequently used in particle based Monte-Carlo simulations of plasma collisions, among others. However, most numerical treatments do not guarantee energy conservation, which may lead to unphysical artifacts such as numerical heating and spectra distortions. We present a novel structure-preserving numerical algorithm for the Langevin equation for pitch angle scattering. Similar to the well-known Boris algorithm, the proposed numerical scheme takes advantage of the structure-preserving properties of the Cayley transform when calculating the velocity-space rotations. The resulting algorithm is explicitly solvable, while preserving the norm of velocities down to machine precision. We demonstrate that the method has the same order of numerical convergence as the traditional stochastic Euler-Maruyama method.
- Type:
- Dataset
- Issue Date:
- September 2020
8. Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models
- Author(s):
- Mark D. Boyer
- Abstract:
- One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.
- Type:
- Dataset
- Issue Date:
- May 2020