SEARCH · Engineering Papers

Results for “nbi”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Recent advance progress of HL-3 experiments

Since the first plasma realized in 2020, a series of key systems on HL-3 (known as HL-2M before) tokamak have been equipped/upgraded, including in-vessel components (the first wall, lower divertor, and toroidal cryogenic/water-cooling/baking/glow discharge systems, etc.), auxiliary heating system of 11 MW, and 28 diagnostic systems (to measure the plasma density, electron temperature, radiation, magnetic field, etc.). Magnet field systems were commissioned firstly for divertor plasma discharges. During the 2nd experimental campaign of HL-3 tokamak, several great progresses have been achieved. Firstly, the successful operation with plasma current larger than 1 MA was achieved under a divertor configuration. Secondly, the advanced divertor concept with two distinct snowflake configurations was realized. It is found that the distribution of ion saturation current and heat flux on bottom plate becomes wide due to magnetic surface expansion, demonstrating the advantage of such configuration in the heat flux mitigation. In addition, using the combination of NBI, ECRH and LHCD, the standard sawtoothing high confinement mode of megampere plasma was firstly accessed on the HL-3. The successful commissioning of HL-3 is beneficial for the initial operation of ITER.

1 MA plasma↗

DOE OSTI2024

Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction

Burning plasma performance, transport, and the effect of hydrogen isotope (H, D, D-T fuel mix) on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73), were used to predict profiles of T i , T e , and n e while including the effects of alpha heating, auxiliary power (NBI + ECH), collisional energy exchange, and radiation losses inside of $r/a$ = 0.9. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals ($P_\textrm{fusion} = 500$ MW at Q = 10) for the baseline scenario and exhibit energy confinement that is within 1σ of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential resonant magnetic perturbation (RMP) effects on performance with a minimal number of gyrokinetic profile iterations required (3–6). These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that $Q \gt$ 17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in IBS conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.

gyrokinetics↗

DOE OSTI2024

Performance prediction applying different reduced turbulence models to the SMART tokamak

The SMall Aspect Ratio Tokamak (SMART) is currently being commissioned at the University of Seville and will be able to compare the performance of positive and negative triangularity plasmas at low aspect ratio. Predictive simulations have been performed for different machine scenarios and heating schemes using the TRANSP code. The objectives of these simulations are to predict the parameters expected in positive triangularity plasmas, to guide diagnostic development, and to validate transport models. Several reduced turbulence models have been used to predict electron and ion temperatures for the operational phase 2. All models provide similar results from approximately mid-radius to the separatrix but important discrepancies are found in the core region. These positive triangularity results are compared with experiments from a similar size machine like GLOBUS-M2. The multi-mode model (MMM) shows the best agreement. Simulations with different boundary conditions have been performed and no strong differences have been observed between them. The impact of neutral beam injection (NBI) on the predicted profiles has also been addressed. Rotation reduces turbulence levels so higher temperatures are achieved when included in the simulations. Studying the different contributions to the thermal diffusivities, it is observed that electron temperature gradient (ETG) turbulence dominates at the plasma core while micro-tearing modes (MTM) dominate at the edge in the electron channel. In the ion channel, the neoclassical contribution is dominant at the core and at the very edge while the Weiland component, which includes ion temperature gradient mode (ITG), trapped electron mode (TEM), kinetic ballooning mode (KBM), peeling mode (PM) and collisionless and collision dominated magnetohydrodynamic (MHD) modes governs the mid-radius region. For phase 3, two plasmas with different electron densities have been studied. The case with lower density matches well a specific discharge of GLOBUS-M2. The higher density plasma shows high performance with β N ≈ 3.8.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Generation of shear flows induced by AE / EPM in LHD plasma

The generation of shear flows (SFs) by Alfven Eigenmodes (AEs) and energetic particle modes (EPMs) have important effects on the operation of future nuclear fusion reactors, because SFs regulate the saturation of the AEs/EPMs, the transport of EPs and thermal plasma, as well as the formation of transport barriers among other consequences. The aim of this study is the analysis of SFs generation during the saturation phase of AEs and EPMs in LHD plasma. Experiments performed in the 23rd and 24th LHD experimental campaigns are dedicated to explore the destabilization of AEs/EPMs in discharges with different heating patterns, thermal plasma and magnetic field configurations. In particular, the shots 176490 and 179697 show the destabilization of MHD bursts and energetic-ion-driven resistive interchange modes (EIC), respectively. Charge exchange spectroscopy measurements in both discharges indicate that the generation of SFs by AE/EPM is uncorrelated with the perturbation induced by the neutral beam injector (NBI). Nonlinear simulations performed using the gyro-fluid code FAR3d show the generation of zonal structures, especially SFs, induced during the saturation phase of Toroidal Alfven Eigenmodes (TAEs) triggered in the MHD burst as well as by the 1/1 EIC in the bursting phase. The simulations indicate that SFs are caused by the radial electric fields powered by energy transfers from the unstable AE/EPM towards the thermal plasma. The strongest SFs are measured during the EIC bursting phase once the 1/1 EPM overlaps with nearby resonances at the plasma periphery. Likewise, the largest SFs during the MHD burst are observed once TAEs radially overlap in the inner-middle plasma region.

AE↗

DOE OSTI2026

Real-time avoidance of the L-mode and H-mode density limit via machine-learned stability metrics

Reliable operation of burning plasma tokamaks will require robust control strategies to avoid macroscopic instability limits such as the L-mode and H-mode density limits (LDL, HDL). In this work, we explore closed-loop avoidance of these phenomena at DIII-D using machine-learned risk metrics. Feedback control is implemented via the ‘DL Supervisor’ scheme, which regulates the chosen risk metric by reducing the density target or increasing NBI heating in real-time. Using the LDL 25 risk metric, the LDL is reproducibly suppressed. We also introduce an HDL risk metric in this study, HDL 25 , which reduces the False Positive Rate by 2x compared to the Greenwald fraction. Applying this scaling to a plasma current ramp-down, we successfully avoid an HDL-driven H/L back-transition. These experiments constitute the first demonstration of real-time DL avoidance using machine-learned risk metrics. These instability metrics outline a path to safer high-density operation, more reliable ramp-down scenarios, and improved off-normal control for next-step devices such as ITER and SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Overview of Wendelstein 7-X high-performance operation

The Wendelstein 7-X (W7-X) stellarator has completed two consecutive experimental campaigns OP 2.2 (Sep.-Dec. 2024) and OP 2.3 (Feb.-May 2025) under a new operational strategy enabling more than one year of uninterrupted device availability. This approach, supported by exceptionally high subsystem reliability, allowed sustained high-efficiency plasma operations with up to 80–100 discharges per day across a broad range of magnetic configurations. Several key technical upgrades-most notably the first operation of a 1.5 MW class steady-state gyrotron, a new steady-state pellet injector, and advanced real-time feedback control systems significantly enhanced heating, fueling, and plasma control capabilities. Together, these improvements enabled major advances in long-pulse performance, high-β operation, and confinement optimization. Long-pulse discharges achieved 1.8 GJ of injected energy under fully detached divertor conditions, while reduced-field scenarios facilitated record volume-averaged β values approaching 3%. High-performance plasmas with centrally peaked density profiles, created via neutral beam injection (NBI) or sustained pellet fueling, demonstrated strongly reduced turbulent transport and stellarator-record fusion triple products. Complementary studies of power exhaust and divertor heat loads revealed the role of scrape-off-layer drift physics in shaping strike-line patterns under attached conditions. Together, the results from OP 2.2 and OP 2.3 significantly expand the operational space of W7-X and strengthen its role as a leading platform for steady-state stellarator research and reactor-relevant plasma scenarios.

Wendelstein 7-X↗

DOE OSTI2020

Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

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 behaviour of magnetic perturbations from corresponding frequency spectrograms that are typically identified by humans. Analysis allows for comparison between different mode character (such as quiescent, fixedfrequency, 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 (β beam,i /β). In agreement with previous work by Fredrickson et al., in this work, we find correlation between β 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 non-quiescent behaviour for magnetic fluctuations in the 50 - 200 kHz frequency band is observed along the boundary v Φ ≲ (1/4) (v inj. - 3v A ) where v Φ is the rotation

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Conceptual Design of a Scintillator-Based Fast-Ion Loss Detector for the Wendelstein 7-X Stellarator

Here, a conceptual design of a scintillator-based fast-ion loss detector (FILD) has been developed for the Wendelstein 7-X stellarator (W7-X). Simulations using the Monte Carlo codes ASCOT5 and BEAMS3D have been performed to calculate the expected flux of neutral beam injection (NBI)-generated fast hydrogen ions onto the conceptual detector probe head. These fast-ion loss fluxes have been calculated for several magnetic field configurations as well as probe insertion positions. At the maximum insertion position, both co-and counter-going losses with high incident pitch angles are observed; however, at retracted positions, only co-going fast ions reach the probe head. The FILDSIM code has been used to optimize the geometry of the detector entrance and collimating elements to achieve a wide velocity space coverage as well as a high velocity–space resolution. A synthetic FILD signal is calculated for the expected loss distribution via forward modeling using the instrument response function. The synthetic signal is found to largely retain the velocity space features of the loss distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Neural-Network-Enhanced COTSIM: Advancing Predictive Capabilities for Fast DIII-D Simulations

Sustaining fusion reactions in tokamaks requires heating plasma to thermonuclear temperatures while maintaining confinement and stability. Neutral beam injection (NBI) provides heating, current drive, torque, and fueling, while electron cyclotron (EC) waves are widely used for heating and current drive; together, these actuators shape the plasma current, temperature, and density profiles. The control-oriented tokamak simulator (COTSIM), a predictive, control-oriented code, has been enhanced with neural-network surrogates for transport and sources. Turbulent transport is predicted by MMMnet—a neural-network version of the updated multimode model (MMM 9.0.10)—with significantly reduced computation time relative to MMM; neoclassical transport follows the Chang–Hinton model. NUBEAMnet, a surrogate of the Monte Carlo NUBEAM module, predicts beam-driven heating, current, and torque. EC heating and current drive use a control-oriented, empirically scaled source model; plasma resistivity follows the Spitzer formulation; bootstrap current uses the Sauter model. Equilibrium is computed using both prescribed and fixed-boundary solvers (FBSs), and the pedestal structure is modeled with an empirical pedestal model. For a representative DIII-D discharge, COTSIM predicts electron and ion temperature and safety-factor profiles in close agreement with TRANSP predictive and interpretive simulations while extending predictions through the pedestal region to the plasma edge (versus 80% of the minor radius in TRANSP). Furthermore, the equivalent COTSIM simulation runs in under 3 min compared to about 2 h for TRANSP, enabling rapid scenario planning, optimization of tokamak operation, and between-pulse control design.

Control-oriented tokamak simulator (COTSIM)↗

DOE OSTI2017

Advances in boronization on NSTX-Upgrade

Boronization has been effective in reducing plasma impurities and enabling access to higher density, higher confinement plasmas in many magnetic fusion devices. The National Spherical Torus eXperiment, NSTX, has recently undergone a major upgrade to NSTX-U in order to develop the physics basis for a ST-based Fusion Nuclear Science Facility (FNSF) with capability for double the toroidal field, plasma current, and NBI heating power and increased pulse duration from 1–1.5 s to 5–8 s. A new deuterated tri-methyl boron conditioning system was implemented together with a novel surface analysis diagnostic. We report on the spatial distribution of the boron deposition versus discharge pressure, gas injection and electrode location. The oxygen concentration of the plasma facing surface was measured by in-vacuo XPS and increased both with plasma exposure and with exposure to trace residual gases. This increase correlated with the rise of oxygen emission from the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Scenario Development During Commissioning Operations on the National Spherical Torus Experiment Upgrade

The National Spherical Torus Experiment Upgrade (NSTX-U) will advance the physics basis required for achieving steady-state, high-beta, and high-confinement conditions in a tokamak by accessing high toroidal field (1 T) and plasma current (1.0 - 2.0 MA) in a low aspect ratio geometry (A = 1.6 - 1.8) with flexible auxiliary heating systems (12 MW NBI, 6 MW HHFW). This paper describes progress in the development of L- and H-mode discharge scenarios and the commissioning of operational tools in the first ten weeks of operation that enable the scientific mission of NSTX-U. Vacuum field calculations completed prior to operations supported the rapid development and optimization of inductive breakdown at different values of ohmic solenoid current. The toroidal magnetic field (B_T0 = 0.65 T) exceeded the maximum values achieved on NSTX and novel long-pulse L-mode discharges with regular sawtooth activity exceeded the longest pulses produced on NSTX (tpulse > 1.8s). The increased flux of the central solenoid facilitated the development of stationary L-mode discharges over a range of density and plasma current (Ip). H-mode discharges achieved similar levels of stored energy, confinement (H98y,2 > 1) and stability (beta_N/beta_N-nowall > 1) compared to NSTX discharges for Ip < 1 MA. High-performance H-mode scenarios require an L-H transition early in the Ip ramp-up phase in order to obtain low internal inductance (li) throughout the discharge, which is conducive to maintaining vertical stability at high elongation (kappa > 2.2) and achieving long periods of MHD quiescent operations. The rapid progress in developing L- and H-mode scenarios in support of the scientific program was enabled by advances in real-time plasma control, efficient error field identification and correction, effective conditioning of the graphite wall and excellent diagnostic availability.

Error field correction↗

DOE OSTI2019

TRANSP-based Optimization Towards Tokamak Scenario Development

An optimization approach that incorporates the predictive transport code TRANSP is proposed for tokamak scenario development. Optimization methods are often employed to develop open-loop control strategies to aid access to high performance tokamak scenarios. In general, the optimization approaches use control-oriented models, i.e. models that are reduced in complexity and prediction accuracy as compared to physics-oriented transport codes such as TRANSP. In the presented approach, an optimization procedure using the TRANSP code to simulate the tokamak plasma is considered for improved predictive capabilities. As a test case, the neutral beam injection (NBI) power is optimized to develop a control strategy that maximizes the non-inductive current fraction during the ramp-up phase for NSTX-U. Simulation studies towards the achievement of non-inductive ramp up in NSTX-U have already been carried out with the TRANSP code. The optimization-based approach proposed in this work is used to maximize the non-inductive current fraction during ramp-up in NSTX-U, demonstrating that the scenario development task can be automated. An additional test case considers optimization of the current ramp rate in DIII-D for obtaining a stationary plasma characterized bya flat loop voltage profile in the flattop phase.

DIII-D↗

DOE OSTI2019

Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

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.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

machine learning↗

DOE OSTI2020

First impurity powder injection experiments in LHD

Injection of impurities in the form of sub-millimeter powder grains is performed for the first time in the Large Helical Device (LHD) plasma, employing the Impurity Powder Dropper (IPD) [A. Nagy et al., RSI 2018], developed and built by PPPL. Controlled amounts of boron (B) and boron nitride (BN) powder are injected into the helical plasma. Visible camera imaging, UV and charge exchange spectroscopy measurements show that the injected impurities effectively penetrate into the plasma in two different magnetic configurations.The prompt effects of the impurities on the plasma are characterized as the injection rate is scanned. The injected impurities provide a supplemental electron source, causing the plasma density to increase, together with the radiated power. Beneficial effects on the confined plasma temperature are observed at low plasma densities, due to an increased efficiency in NBI power absorption. For $n_{e,av}<10^{19}m^{-3}$ the powder grains penetrate deeper into the plasma, as they can be less effectively deflected by the plasma flow in the divertor leg, which they have to cross first as they are injected from the top of the machine.In this case, the created B ions are observed to move outwards from UV spectroscopy and charge exchange measurements, due to the outwards direction of the radial electric field. This makes low density plasmas a better candidate for powder boronization techniques.

Boron↗

DOE OSTI2013

Four-Dimensional Finite-Orbit-Width Fokker-Planck Code with Sources, for Neoclassical/Anomalous Transport Simulation of Ion and Electron (Final Technical Report)

Within the US Department of Energy/Office of Fusion Energy magnetic fusion research program, there is an important whole-plasma-modeling need for a radio-frequency/neutral-beam-injection (RF/NBI) transport-oriented finite-difference Fokker-Planck (FP) code with combined capabilities for 4D (2R2V) geometry near the fusion plasma periphery, and computationally less demanding 3D (1R2V) bounce-averaged capabilities for plasma in the core of fusion devices. Demonstration of proof-of-principle achievement of this goal has been carried out in research carried out under Phase I of the SBIR award. Two DOE-sponsored codes, the CQL3D bounce-average Fokker-Planck code in which CompX has specialized, and the COGENT 4D, plasma edge-oriented Fokker-Planck code which has been constructed by Lawrence Livermore National Laboratory and Lawrence Berkeley Laboratory scientists, where coupled. Coupling was achieved by using CQL3D calculated velocity distributions including an energetic tail resulting from NBI, as boundary conditions for the COGENT code over the two-dimensional velocity space on a spatial interface (flux) surface at a given radius near the plasma periphery. The finite-orbit-width fast ions from the CQL3D distributions penetrated into the peripheral plasma modeled by the COGENT code. This combined code demonstrates the feasibility of the proposed 3D/4D code. By combining these codes, the greatest computational efficiency is achieved subject to present modeling needs in toroidally symmetric magnetic fusion devices. The more efficient 3D code can be used in its regions of applicability, coupled to the more computationally demanding 4D code in higher collisionality edge plasma regions where that extended capability is necessary for accurate representation of the plasma. More efficient code leads to greater use and utility of the model. An ancillary aim of the project is to make the combined 3D/4D code user friendly. Achievement of full-coupling of these two Fokker-Planck codes will advance computational modeling of plasma devices important to the USDOE magnetic fusion energy program, in particular the DIII-D tokamak at General Atomics, San Diego, the NSTX spherical tokamak at Princeton, New Jersey, and the MST reversed-field-pinch Madison, Wisconsin. The validation studies of the code against the experiments will improve understanding of physics important for magnetic fusion, and will increase our design capabilities for achieving the goals of the International Tokamak Experimental Reactor (ITER) project in which the US is a participant and which seeks to demonstrate at least a factor of five in fusion power production divided by input power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

BEAMS3D Neutral Beam Injection Model

With the advent of applied 3D fields in Tokamaks and modern high performance stellarators, a need has arisen to address non-axisymmetric effects on neutral beam heating and fueling. We report on the development of a fully 3D neutral beam injection (NBI) model, BEAMS3D, which addresses this need by coupling 3D equilibria to a guiding center code capable of modeling neutral and charged particle trajectories across the separatrix and into the plasma core. Ionization, neutralization, charge-exchange, viscous velocity reduction, and pitch angle scattering are modeled with the ADAS atomic physics database. Benchmark calculations are presented to validate the collisionless particle orbits, neutral beam injection model, frictional drag, and pitch angle scattering effects. A calculation of neutral beam heating in the NCSX device is performed, highlighting the capability of the code to handle 3D magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗