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Proton deflectometry analysis in magnetized plasmas: Magnetic field reconstruction in one dimension
Proton deflectometry is used in magnetized high-energy-density plasmas to observe electromagnetic fields. Here we describe a reconstruction algorithm to recover the electromagnetic fields from proton fluence data in 1-D. The algorithm is verified against analytic solutions and applied to example data. Next, we study the role of source fluence uncertainty for 1-D reconstructions. We show that reconstruction boundary conditions can be used to constrain the source fluence profile and use this to develop a reconstruction using a specified pair of boundary conditions on the magnetic field. From these considerations, we experimentally demonstrate a hybrid mesh-fluence reconstruction technique where fields are reconstructed from fluence data in an interior region with boundary conditions supplied by direct mesh measurements at the boundary.
The 2022 applied physics by pioneering women: a roadmap
Abstract Women have made significant contributions to applied physics research and development, and their participation is vital to continued progress. Recognizing these contributions is important for encouraging increased involvement and creating an equitable environment in which women can thrive. This Roadmap on Women in Applied Physics, written by women scientists and engineers, is intended to celebrate women’s accomplishments, highlight established and early career researchers enlarging the boundaries in their respective fields, and promote increased visibility for the impact women have on applied physics research. Perspectives cover the topics of plasma materials processing and propulsion, super-resolution microscopy, bioelectronics, spintronics, superconducting quantum interference device technology, quantum materials, 2D materials, catalysis and surface science, fuel cells, batteries, photovoltaics, neuromorphic computing and devices, nanophotonics and nanophononics, and nanomagnetism. Our intent is to inspire more women to enter these fields and encourage an atmosphere of inclusion within the scientific community.
INGRID: An interactive grid generator for 2D edge plasma modeling
A fusion boundary-plasma domain is defined by axisymmetric magnetic surfaces where the geometry is often complicated by the presence of one or more X-points; and modeling boundary plasmas usually relies on computational grids that account for the magnetic field geometry. The new grid generator INGRID (Interactive Grid Generator) presented in this work is a Python-based code for calculating grids for fusion boundary plasma modeling, for a variety of configurations with one or two X-points in the domain. INGRID first performs partitioning over the domain consisting of a small number of patches conforming to the magnetic field and wall geometry; then it generates a subgrid on each of the patches and joins them into a global grid. This domain partitioning strategy makes possible a uniform treatment of various configurations with one or two X-points in the domain. This includes single-null, double-null, and other configurations with two X-points in the domain. The INGRID design allows generating grids either interactively, via a parameter-file driven GUI, or using a non-interactive script-controlled workflow. Results of testing demonstrate that INGRID is a flexible, robust, and user-friendly grid-generation tool for fusion boundary-plasma modeling.
Uncovering turbulent plasma dynamics via deep learning from partial observations
One of the most intensely studied aspects of magnetic confinement fusion is edge plasma turbulence which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied to model boundary plasmas with varying success. Towards better understanding edge turbulence in both theory and experiment, we demonstrate that a novel multi-network physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent with the two-fluid theory from partial observations of electron pressure which is not otherwise possible using conventional equilibrium models. Furthermore, this technique presents a novel paradigm for the advanced design of plasma diagnostics and validation of magnetized plasma turbulence theories in challenging thermonuclear environments.
Uncovering turbulent plasma dynamics via deep learning from partial observations
One of the most intensely studied aspects of magnetic confinement fusion is edge plasma turbulence which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied to model boundary plasmas with varying success. Towards better understanding edge turbulence in both theory and experiment, we demonstrate that a novel multi-network physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent with the two-fluid theory from partial observations of electron pressure which is not otherwise possible using conventional equilibrium models. This technique presents a novel paradigm for the advanced design of plasma diagnostics and validation of magnetized plasma turbulence theories in challenging thermonuclear environments.
A phase-shift-periodic parallel boundary condition for low-magnetic-shear scenarios
Abstract We formulate a generalized periodic boundary condition as a limit of the standard twist-and-shift parallel boundary condition that is suitable for simulations of plasmas with low magnetic shear. This is done by applying a phase shift in the binormal direction when crossing the parallel boundary. While this phase shift can be set to zero without loss of generality in the local flux-tube limit when employing the twist-and-shift boundary condition, we show that this is not the most general case when employing periodic parallel boundaries, and may not even be the most desirable. A non-zero phase shift can be used to avoid the convective cells that plague simulations of the three-dimensional Hasegawa–Wakatani system, and is shown to have measurable effects in periodic low-magnetic-shear gyrokinetic simulations. We propose a numerical program where a sampling of periodic simulations at random pseudo-irrational flux surfaces are used to determine physical observables in a statistical sense. This approach can serve as an alternative to applying the twist-and-shift boundary condition to low-magnetic-shear scenarios, which, while more straightforward, can be computationally demanding.
Influence of elongation and triangularity on plasma response to resonant magnetic perturbations
Abstract Systematic toroidal modeling of the plasma response to the n = 1–4 ( n is the toroidal mode number) resonant magnetic perturbation (RMP) field is carried out in order to understand the plasma-shaping effect on controlling the type-I edge-localized modes (ELMs) in tokamak experiments. Considered are large variations of the plasma elongation and triangularity at a fixed edge safety factor q a , for limiter plasmas with both single-null (SN) and double-null (DN) divertor-like boundary shapes. Numerical results assuming conformal 3D RMP coils show that (i) the optimum coil phasing between the upper and lower rows for ELM control becomes increasingly sensitive to the plasma elongation with higher- n toroidal spectra, (ii) the optimum coil phasing is however essentially independent of the plasma triangularity for all n = 1–4 RMP fields, (iii) with the same coil current and the optimum coil phasing, high elongation generally favors ELM control but it may be more challenging for plasmas with intermediate elongation and with lower- n ( n = 1–2) RMPs, and (iv) higher triangularity is generally always better for ELM control with all n = 1–4 fields for both DN and SN divertor-like plasma boundary shapes.
Combined Influence of Rotation and Scrape-Off Layer Drifts on Recycling Asymmetries in Tokamak Plasmas
Coupled 2D fluid-kinetic simulations of a DIII-D high confinement tokamak plasma show that plasma rotation coupled with drift effects near the plasma edge play a significant role in the creation of the observed poloidal distribution of neutrals. It is observed that including either drift or rotation effects enhances particle flux at the inner target in the case of ion 𝐵×∇𝐵 drift toward the 𝑋-point. However, the particle flux asymmetry is significantly higher with the combination of drifts and rotation than either effect alone. The heightened particle flux asymmetry allows for improved simulation of the strong in-out asymmetry of the Lyman-𝛼 brightness profiles measured in the experiment. Enhancement of radial transport of parallel momentum changes the upstream scrape-off layer flow pattern, increasing the fraction of deuterium flux that reaches the inboard divertor entrance while lowering that which arrives at the outboard. In conclusion, this Letter indicates that by combining drifts, rotation, and viscous coupling, existing boundary plasma models can achieve a satisfactory agreement with experimentally measured neutral asymmetries.
INGRID: An interactive grid generator for 2D edge plasma modeling
A fusion boundary-plasma domain is defined by axisymmetric magnetic surfaces where the geometry is often complicated by the presence of one or more X-points; and modeling boundary plasmas usually relies on computational grids that account for the magnetic field geometry. The new grid generator INGRID (Interactive Grid Generator) presented here is a Python-based code for calculating grids for fusion boundary plasma modeling, for a variety of configurations with one or two X-points in the domain. INGRID first performs partitioning over the domain consisting of a small number of patches conforming to the magnetic field and wall geometry; then it generates a subgrid on each of the patches and joins them into a global grid. This domain partitioning strategy makes possible a uniform treatment of various configurations with one or two X-points in the domain. This includes single-null, double-null, and other configurations with two X-points in the domain. The INGRID design allows generating grids either interactively, via a parameterfile driven GUI, or using a non-interactive script-controlled workflow. Results of testing demonstrate that INGRID is a flexible, robust, and user-friendly grid-generation tool for fusion boundary-plasma modeling.
Q2 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment
This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q2: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $\circ$ Run CESOL with BOUT++/Hermes-3 and immersed boundary condition to directly map to wall: • Run BOUT++/Hermes-3 through the IPS workflow to find radial particle and energy diffusivities to match either the Eich or the physics-based scaling of the SOL heat flux width, and • Expand source of first wall heat flux to include charged particles, neutrals, and radiation from the core+edge. 2. Generate medium fidelity parametrized CAD: $\circ$ Develop the TRACER tool to read an existing CAD, regenerate the geometry based on vertex location and connectivity information, define vertex translation and parameters needed for scaling the CAD, and $\circ$ Utilize the FreeGS code to determine CAT PF coil placement, including minimizing the number of coils, coil current, and electromechanical stresses. 3. Utilize plasma loading for engineering analysis: $\circ$ Couple the plasma loading to input for OpenFOAM and demonstrate initial test of thermal analysis of CAT first wall loading with typical DCLL blanket component cooling boundary conditions. 4. Demonstrate nuclear analysis: $\circ$ Apply initial analysis of tritium transport in DCLL blanket by evaluating spatially resolved tritium generation rates, tritium diffusion and convection.
Data-driven linear time advance operators for the acceleration of plasma physics simulation
In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.
Mechanisms of energetic-particle transport in magnetically confined plasmas
Super-thermal ions and electrons occur in both space and fusion plasmas. Because these energetic particles (EP) have large velocities, EP orbits necessarily deviate substantially from magnetic surfaces. Orbits are described by conserved constants of motion that define topological boundaries for different orbit types. Electric and magnetic field perturbations produced by instabilities can disrupt particle orbits, causing the constants of motion to change. The statistics of the “kicks” associated with these perturbations determines the resulting cross field transport. A unifying theme of this tutorial is the importance of the perturbation’s phase at the particle’s position Θ = k • r – ωt, where k and ω are the wavevector and frequency of the perturbation, r is the EP position, and t is the time. A distinction is made between field perturbations that resonate with an aspect of the orbital motion and those that do not. Resonance occurs when the wave phase returns to its initial value in an integer multiple of an orbital period. Convective transport occurs when resonant particles experience an unvarying wave phase. Alternatively, multiple wave-particle resonances usually decorrelate the phase, resulting in diffusive transport. Large orbits increase the number of important resonances and can cause chaotic orbits even for relatively small amplitude waves. In contrast, in the case of non-resonant perturbations, orbital phase averaging reduces transport. Here, large field perturbations introduce additional effects, including nonlinear resonances at fractional values of the orbital motion. In summary, large orbits are a blessing and a curse: For non-resonant modes, orbit-averaging reduces transport but, for resonant transport, large orbits facilitate jumps across topological boundaries and enhance the number of important resonances.
Plasma-droplet interaction study to assess transport limitations and the role of • OH, O • ,H • ,O 2 (a 1 Δ g ),O 3 , He(2 3 S) and Ar(1s 5 ) in formate decomposition
Plasmas interacting with liquid microdroplets are gaining momentum due to their ability to significantly enhance the reactivity transfer from the gas phase plasma to the liquid. This is, for example, critically important for efficiently decomposing organic pollutants in water. In this contribution, the role of •OH as well as non-•OH-driven chemistry initiated by the activation of small water microdroplets in a controlled environment by diffuse RF glow discharge in He with different gas admixtures (Ar, O 2 and humidified He) at atmospheric pressure is quantified. The effect of short-lived radicals such as O• and H• atoms, singlet delta oxygen (O 2 (a 1 Δ g )), O 3 and metastable atoms of He and Ar, besides •OH radicals, on the decomposition of formate dissolved in droplets was analyzed using detailed plasma diagnostics, droplet characterization and ex situ chemical analysis of the treated droplets. The formate decomposition increased with increasing droplet residence time in the plasma, with ~70% decomposition occurring within ~15 ms of the plasma treatment time. The formate oxidation in the droplets is shown to be limited by the gas phase •OH flux at lower H 2 O concentrations with a significant enhancement in the formate decomposition at the lowest water concentration, attributed to e – /ion-induced reactions. However, the oxidation is diffusion limited in the liquid phase at higher gaseous •OH concentrations. Here, the formate decomposition in He/O 2 plasma was similar, although with an order of magnitude higher O• radical density than the •OH density in the corresponding He/H 2 O plasma. Using a one-dimensional reaction–diffusion model, we showed that O 2 (a 1 Δ g ) and O 3 did not play a significant role and the decomposition was due to O•, and possibly •OH generated in the vapor containing droplet-plasma boundary layer.
Validation of the imaging neutral particle analyzer in nearly MHD quiescent plasmas using injected beam ions on DIII-D
The imaging neutral particle analyzer (INPA) is a scintillator-based diagnostic that provides energy and radially resolved measurements of confined fast ions. To verify operation, understanding, and modeling of the diagnostic performance, distributions of deuterium beam ions in low density, nearly MHD-quiescent plasmas are measured on the DIII-D tokamak using the INPA. Here, the distribution is altered by changing the pitch-angle scattering rate with electron cyclotron heating (ECH). Experimental images are mostly reproduced with simulation of core fast ions charge exchanging with injected beam and edge cold neutrals in classical cases. Image comparisons between the experiment and simulation show agreement with less than 25% discrepancies near the beam injection energy of 50 keV. Other strong passive signals, observed in a localized region on the image, are suggested to come from charge exchange between cold neutrals and fast ions around the plasma boundary.
Burning plasma achieved in inertial fusion
Obtaining a burning plasma is a critical step towards self-sustaining fusion energy. A burning plasma is one in which the fusion reactions themselves are the primary source of heating in the plasma, which is necessary to sustain and propagate the burn, enabling high energy gain. After decades of fusion research, here we achieve a burning-plasma state in the laboratory. These experiments were conducted at the US National Ignition Facility, a laser facility delivering up to 1.9 megajoules of energy in pulses with peak powers up to 500 terawatts. We use the lasers to generate X-rays in a radiation cavity to indirectly drive a fuel-containing capsule via the X-ray ablation pressure, which results in the implosion process compressing and heating the fuel via mechanical work. The burning-plasma state was created using a strategy to increase the spatial scale of the capsule through two different implosion concepts. These experiments show fusion self-heating in excess of the mechanical work injected into the implosions, satisfying several burning-plasma metrics. Additionally, we describe a subset of experiments that appear to have crossed the static self-heating boundary, where fusion heating surpasses the energy losses from radiation and conduction. These results provide an opportunity to study α-particle-dominated plasmas and burning-plasma physics in the laboratory.
Constrained stellarator coil curvature optimization with FOCUS
Finding less complicated coils that have adequately low field errors is a crucial step in stellarator development. One coil metric that is of high importance is the maximum curvature of the coil centreline, or coil single filament. Conductors cannot be bent below some threshold minimum radius of curvature. High coil curvatures can cause strains to exceed acceptable levels, especially in superconducting coils. We investigate three ways to optimize coil curvature and find that applying penalty functions to the coil curvature solves for coils that have a constrained maximum curvature and low field error. Penalty functions are implemented in FOCUS and coil solutions optimized for an HSX-like ‘plasma boundary’ are presented.
Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space
We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion are akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.