Bulletin of the American Physical Society
64th Annual Meeting of the APS Division of Plasma Physics
Volume 67, Number 15
Monday–Friday, October 17–21, 2022; Spokane, Washington
Session VI02: Magnetic Confinement Fusion/Fundamental PlasmasLive Streamed
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Chair: Valerie Izzo, Fiat Lux Room: Ballroom 100 B |
Thursday, October 20, 2022 3:00PM - 3:30PM |
VI02.00001: Bringing advanced sparse system identification to plasma physics Invited Speaker: Alan Kaptanoglu Many tasks in fluid and plasma physics, such as design optimization and control, are challenging because of nonlinearity and a large range of scales in both space and time. This range of scales necessitates exceedingly high-dimensional measurements and computational discretization to resolve all relevant features, resulting in vast data sets and time-intensive computations. Machine learning constitutes a growing set of powerful techniques to extract patterns and build models from nonlinear systems data, complementing existing theoretical, numerical, and experimental efforts. The sparse identification of nonlinear dynamics (SINDy) algorithm is one such method that identifies a minimal dynamical system model while balancing model complexity with accuracy, avoiding overfitting. This approach tends to promote models that are interpretable and generalizable, capturing the essential physics of the system. We discuss recent advances with the SINDy method, including the identification of PDE systems, the incorporation of physical constraints from global conservation laws, promoting global stability, solving for weak-formulation differential equations, and more. These advances have been consolidated into the open-source PySINDy code, enabling anyone with access to measurement data to engage in scientific model discovery. We conclude with recent work that explores connections with permanent magnet optimization for stellarators. |
Thursday, October 20, 2022 3:30PM - 4:00PM |
VI02.00002: Data-driven discovery of reduced plasma physics models from fully-kinetic simulations Invited Speaker: E. Paulo Alves At the core of some of the most important problems in plasma physics — from controlled nuclear fusion to the acceleration of cosmic rays — is the challenge to describe nonlinear, multi-scale plasma dynamics. The development of reduced plasma models that balance between accuracy and complexity is critical to advancing theoretical comprehension and enabling holistic computational descriptions of these problems. In this talk, I will discuss how techniques from statistical and machine learning are offering new ways of inferring reduced plasma physics models from the increasingly abundant data of plasma dynamics produced by experiments, observations and simulations. In particular, I will focus on how sparse regression techniques can be used to infer interpretable plasma physics models (in the form of nonlinear partial differential equations) directly from the data of fully-kinetic particle-in-cell (PIC) simulations. I will demonstrate the potential of this approach by recovering the fundamental hierarchy of plasma physics models — from the kinetic Vlasov equation to single-fluid magnetohydrodynamics — based solely on data of complex plasma dynamics from first-principles PIC simulations. I will give some perspectives about how this data-driven methodology offers a promising new tool to accelerate the development of reduced theoretical models of complex nonlinear plasma phenomena and to design computationally efficient algorithms for multi-scale plasma simulations. |
Thursday, October 20, 2022 4:00PM - 4:30PM |
VI02.00003: Intrinsic rotation driven by the radial variation of phase velocity and turbulence intensity in tokamaks Invited Speaker: Denis A St-Onge Tokamak plasmas can spontaneously develop differential toroidal rotation without external torque. This 'intrinsic rotation', which may be necessary for the success of future fusion devices, has proven difficult to model. This is partly due to the fact that for up-down symmetric plasmas with no equilibrium flow shear, symmetries of the lowest-order gyrokinetic equation prohibit the transport of toroidal angular momentum, and so intrinsic rotation depends on next-order terms in the gyrokinetic expansion that are typically not included in simulations. Terms dealing with system-scale radial variation are particularly problematic, as they necessitate a global approach. We present a study on intrinsic rotation due to radial variation of the equilibrium gradients and intensity of turbulent fluctuations using the recently developed global version of the gyrokinetic code stella, whose approach allows for precise control over the next-order corrections to the equilibrium kinetic and magnetic profiles. It is found that intrinsic rotation is insensitive to the radial profile variation of turbulent intensity; rather, profile variation of the phase velocity plays the dominant role in setting the transport of toroidal angular momentum. This mode of transport is shown to be analogous to that driven by equilibrium flow shear, biasing the radial wavenumber at the outboard midplane which, by acting with the radial magnetic drift, provides the required symmetry breaking for the net generation of intrinsic rotation. |
Thursday, October 20, 2022 4:30PM - 5:00PM |
VI02.00004: Kinetic Landau-fluid closures of non-Maxwellian distribution plasmas Invited Speaker: Kaixuan kaixuan Non-Maxwellian plasmas are in fact fairly common in the laboratory, space, and astrophysical environment, and yet most of the theoretical studies so far on heat flux closure are performed under the near-Maxwellian assumption. In this work, new kinetic Landau-fluid closures are derived for non-Maxwellian distribution plasmas. A special static case (i.e., zero mode frequency) is first considered for plasmas with cutoff Maxwellian distribution. In the strongly collisional regime, this model reduces to Braginskii’s local heat flux model; while in the weak collisional regime, the heat flux becomes non-local and recovers the Hammett–Perkins model when the value of the cutoff velocity approaches infinity. Comparison of the thermal transport coefficient for Maxwellian, cutoff Maxwellian, and super-Gaussian distributions shows that the reduction of the high-speed tail particles leads to the corresponding reduction of the thermal transport coefficient across the entire range of collisionality, more reduction of the free streaming transport toward the weak collisional regime. In the collisionless limit, \chi approaches zero for the cutoff Maxwellian and the super-Gaussian distribution but remains finite for Maxwellian distribution. Interestingly, \chi is complex if the cutoff Maxwellian distribution is asymmetric, and Im(\chi) yields an additional streaming heat flux in comparison with the symmetric cutoff Maxwellian distribution. The derived Landau-fluid closures are general for fluid moment models, and applicable for the cutoff Maxwellian distribution in an open magnetic field line region, such as the scape-off-layer plasmas, the thermal quench plasmas during a tokamak disruption, and the solar corona, and the super-Gaussian electron distribution function due to inverse bremsstrahlung heating in laser-plasma studies. |
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