Plasma Transport Research Articles

Full radius integrated modelling of ohmic ramp-up at TCV including self consistent density prediction

Abstract The ramp-up is a critical phase in the operations of a Tokamak, during which engineering and physics aspects must be taken into account to ensure stability, minimize flux consumption and avoid disruptions. Predicting ramp-up phases faces challenges such as nonlinearity, uncertainty on boundary and initial conditions and changes in the magnetic equilibrium. Our work uses the High-Fidelity Pulse Simulator (HFPS), a Python workflow based on JINTRAC. The input and output are in machine and code generic IMAS data format. The HFPS predicts the evolution of the current, temperature, main ion density and impurity density up to the separatrix. The self-consistent prediction of the density during the ramp-up represents the main element of novelty in this work. To this end, a closed feedback loop is set to match experimental line averaged density. QuaLiKiz [1], TGLF [2] and FRANTIC [3] are used to calculate turbulent fluxes and the source of neutrals respectively. QuaLiKiz and TGLF predict a transition from Trapped Electron Mode early in the discharge to Ion Temperature Gradient dominated turbulence. The results are compared to higher fidelity simulations with GKW, which show qualitative agreement. Good general agreement is reached between integrated modelling and experimental data, quantified by proposed measures of agreement. A large set of sensitivities to modeling choices and initial and boundary conditions is performed on four different discharges, to assess the robustness of the approach.

[1] J. Citrin et al. “Tractable flux-driven temperature, density, and rotation profile evolution with the quasilinear gyrokinetic transport model QuaLiKiz”. PPCF 59.12 (2017), p. 124005
[2] G. M. Staebler et al. “The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence”. PoP 23.6 (2016).
[3] S Tamor. “ANTIC: A code for Calculation of Neutral Transport in Cylindrical Plasmas”. Journal of Computational Physics 40.1 (1981),
p. 104119.

Transport and profile broadening in the private flux region of ASDEX upgrade and role for power exhaust

Abstract Understanding the transport processes that determine the plasma profile widths in the scrape-off layer (SOL) and divertor region of tokamaks is crucial for successful power and particle exhaust management in future devices. Plasma transport from the SOL into the Private Flux Region (PFR) broadens the profiles and could mitigate the power exhaust challenge. Analysis of ion current profiles, measured by Langmuir probes in the ASDEX Upgrade (AUG) tokamak, shows that the ion current width in the PFR, normalized by the flux expansion between outer target and midplane, is about \SI{1.5}{mm} in L-mode and \SI{1}{mm} in inter-ELM H-mode plasmas. The measured widths agree within a factor of two with predictions from an analytical model, based on Pfirsch-Schl"uter flows. According to the model, the ion PFR width increases with the distance $\Delta R$ between the outer target and X-point major radii, and scales inversely with the poloidal magnetic field $B_p$. For the tokamaks ITER and SPARC the model predicts PFR widths below \SI{0.2}{mm}, i.e.\ no significant broadening is expected.

The impact of interplanetary magnetic field intensity on the Martian ionosphere

The interplanetary magnetic field (IMF) is one of the important external drivers that controls the Martian-induced magnetosphere and ionosphere. Previous studies have shown that the ion escape process is highly influenced by both the direction and intensity of the IMF. The enhanced IMF may decrease the ion escape rate by inducing a stronger magnetosphere that protects the Martian ionosphere, but the mechanisms have not been investigated thoroughly. Further studies are needed to reveal the response of ionospheric heavy ions to IMF variation as well as the underlying physical mechanism. This study aims to investigate the influence the IMF strength has on the Martian ionosphere. We adopted a multifluid magnetohydrodynamic (MHD) model in this study, which can self-consistently simulate the interaction between solar wind and Mars. By comparing different cases, we analyzed the ionospheric structure on the dayside and near nightside as well as the ion transport process. We aim to obtain a deeper understanding of how the IMF intensity variation impacts the Martian ionosphere and the escape of planetary ions. A three-dimensional multifluid MHD model was used to simulate the interaction between the upstream solar wind and Mars. Four major species in the Martian ionosphere, H^+, O_ O^+, and CO_ are considered in the model, with the chemical reactions and particle collisions included to calculate ion distribution and ion motions. We analyzed three cases where the IMF strength was set to nT ， nT and nT The enhancement of the IMF produces a stronger electromagnetic field in the Martian plasma environment. Both the electric field and magnetic field intensity increase, which provides a shielding effect to the Martian ionosphere, hindering the intrusion of solar wind particles. Thus, less planetary ions are produced by the chemical reactions between the solar wind and the Martian neutral particles, leading to shrinkage of the ionospheric upper boundary. As the IMF strength increases, both the day-to-night plasma transport and the ion outflow decreases. Thus, a more depleted nightside ionosphere is formed, and the tailward ion escape may be weakened, decreasing the global ion escape rate. Moreover, the strong crustal fields in the southern hemisphere enhance the electromagnetic field on the southern dayside, which withstand the penetration of solar wind plasma more effectively, resulting in asymmetry structures in the ionosphere.

Experimental study and gyrokinetic simulations of isotope effects on core heat transport in JET tokamak deuterium and tritium plasmas

Abstract This paper presents a study on the dependence of the ion temperature stiffness on the plasma main ion isotope mass in JET ITER-like wall and C wall discharges. To this aim, a database of H, D and T shots is analyzed, including new dedicated shots, comparing experiments with lower and higher power injected by the NBI system. In order to characterize the turbulence dependence on the isotope mass, three of these discharges (two in T and one in D) with same external heating scheme are studied in detail and interpreted with gyrokinetic linear and nonlinear simulations. The analysis is performed at fixed radius ρtor = 0.33, selected in order to maximize the electromagnetic stabilizing effects on turbulence, both from thermal and suprathermal particles. The experimental results show a clear ion temperature stiffness reduction when heavier isotopes are considered, thus moving from H to D to T, which is attributed to an increasing thermal electromagnetic stabilization with increasing main isotope mass.

The joint recognition of multi-MHD instabilities on HL-2A

Abstract In tokamak plasmas, various Magnetohydrodynamic (MHD) instabilities could be driven by free energy, which enhance the plasma's transportation, leading to a reduction in critical fusion parameters such as temperature and density, and in severe cases, can even cause major plasma disruptions.This study employs deep learning techniques to learn from 1000 shots manually labelled as three types of MHD instabilities: fishbone mode, long-lived mode, and tearing mode, enabling real-time automated recognition of the instabilities. High accuracies of 97.83%, 95.32%, 94.84% are obtained on 200 testing shots, which are measured by area under the receiver-operator characteristic curve (AUC). Data processing methods that conform to the intuition of physics experts, such as Short Time Fourier Transform (STFT), have been retained, and advanced Artificial Intelligence (AI) algorithms such as Resnet have been combined to achieve a high accuracy rate. It also demonstrated the robustness in fully automatic detections over thousands of discharges. Furthermore, this study explores multitask learning techniques. Instead of using three individual neural network to recognize the different instabilities, a joint recognition algorithm is proposed. The joint algorithm shares the encoder of the three networks and use separate decoder branches to output the result of different instabilities. An inspiring outcome is found that the joint algorithm outperforms the individual ones on all of the instability recognition tasks. Implementing multiple MHD recognition tasks jointly can comprehensively improve the model's performance on each task by sharing related information between intrinsically related tasks. This means that in the future, the model can further develop as more tasks are added, revealing a possible technique routine to build an accurate and comprehensive large-scale model for fusion applications.

Predictions of gyrokinetic turbulent transport in hydrogen-boron plasmas on EHL-2 spherical torus

Abstract The EHL-2 spherical torus at ENN is the next-generation experimental platform under conceptual design, aiming at realizing hydrogen-boron (H-B11) thermonuclear fusion which is an attractive pathway towards neutron-free fusion. In order to achieve high performance steady-state plasma, it is extremely necessary to study the turbulence transport characteristics with high boron content in the plasma core. This work investigates the transport properties in the core internal transport barrier (ITB) region of hydrogen-boron plasma utilizing the gyrokinetic code GENE in view of the high ion temperature scenario of EHL-2, specifically focusing on the impact of boron fractions and plasma β on the microinstabilities and corresponding transport features. Numerical findings indicate that the inclusion of boron species effectively suppresses the trapped electron modes (TEMs) as well as promoting a transition from electromagnetic to electrostatic turbulence with increased boron fraction, which is a result of the suppression of microinstabilities by effective charge and mass. Moreover, it has been identified that the external E×B rotational shear has a notable inhibitory influence on transport which can reduce the transport level by 2-3 orders of magnitude especially at medium boron contents. The suppressive effects of E×B on turbulence is weakened once the kinetic ballooning mode (KBM) is excited and the transport shows a rapid increase with β together with a reduction in zonal flow amplitude which is consistent with previous findings. Therefore, it is strongly suggested that exploring advanced strategies for mitigating turbulent transport at high β regimes are necessary for the active control of plasma behavior regarding H-B11 plasma based fusion devices such as EHL-2.

Drift-Alfvén wave turbulence induced particle and heat transport in I-mode pedestal plasmas

Drift-Alfvén wave turbulence induced particle and heat transport in I-mode pedestal plasmas

Effects of turbulence spreading and symmetry breaking on edge shear flow during sawtooth cycles in J-TEXT tokamak

The effect of sawteeth on plasma performance and transport in the plasmas of tokamak is an important issue in the fusion field. Sawtooth oscillations can trigger heat and turbulence pulses that propagate into the edge plasmas, and thus enhance the edge shear flow and induce a transition from low confinement mode to high confinement mode. The influences of turbulence spreading and symmetry breaking on edge shear flow with sawtooth crashes are observed in the J-TEXT tokamak. The edge plasma turbulence and shear flow were measured using a fast reciprocating electrostatic probe array. The experimental data were analyzed using methods such as conditional average and probability distribution function. After sawtooth crashes, the heat and turbulence pulses in the core propagate to the edge, with the turbulence pulse being faster than the heat pulse. Figures 1 (a)-(e) show the core electron temperature, and the edge electron temperature, turbulence intensity, turbulence drive and spreading rates, Reynolds stress and its gradient, and shearing rates, respectively. Following sawtooth crashes, the edge electron temperature increases and the edge turbulence is enhanced, with turbulence preceding temperature. The enhanced edge turbulence is mainly composed of two parts: turbulence driven by local gradient and turbulence spreading from core to edge. The development of the estimated turbulence spreading rates is prior to that of the turbulence driving rates. The increase in the turbulence intensity can cause the enhancements of the turbulent Reynold stresses and its gradient, thereby enhancing shear flows and radial electric fields. Turbulence spreading leads to the development of edge Reynolds stresses and shear flow faster than edge electron temperature. The Reynolds stress arises from the symmetry breaking of the turbulence wave number spectrum. After sawtooth collapse, the joint probability density function of radial and poloidal wave numbers of turbulence intensity became highly skewed and anisotropic, exhibiting strong asymmetry, as seen in the figures 1 (f) and (g). The development of turbulence spreading flux at the edge is also prior to the particle flux driven by turbulence, indicating that turbulent energy transport is not simply accompanied by turbulent particle transport. These results show that turbulence spreading and symmetry breaking can enhance turbulent Reynolds stress, thereby driving shear flows, after sawtooth crashes.

Mars Nightside Ionospheric Response During the Disappearing Solar Wind Event: First Results

AbstractWe investigated, for the first time, the impact of the disappearing solar wind (DSW) event [26–28 December 2022] on the deep nightside ionospheric species using MAVEN data sets. An enhanced plasma density has been observed in the Martian nightside ionosphere during extreme low solar wind density and pressure periods. At a given altitude, the electron density surged by ∼2.5 times, while for ions (NO+, O2+, CO2+, C+, N+, O+, and OH+), it enhanced by > 10 times, respectively, compared to their typical average quiet‐time periods. This investigation suggests that an upward ionospheric expansion likely took place in a direct consequence to the contrasting low dynamic/magnetic pressure and relatively higher nightside ionospheric pressure (by 1–2 orders) causing an increased ionospheric density. Moreover, the day‐to‐night plasma transport may also be a contributing factor to the increased plasma density. Thus, this study offers a new insight about planetary atmosphere/ionosphere during extreme quiescent solar wind periods.

EMC3-EIRENE simulations of edge plasma and impurity transport by toroidally localized argon seeding on CFETR X-divertor

Abstract Three-dimensional (3D) Edge Monte Carlo transport code EMC3-EIRENE has been employed to study edge plasma and impurity transport with toroidally localized argon seeding on Chinese fusion engineering testing reactor (CFETR) X-divertor configuration. The argon impurity seeded at different poloidal locations has been investigated to evaluate the varied profile of the main plasma in the scrape-off layer (SOL) and on the divertor targets, which shows a strong dependence on the poloidal position of argon gas puffing. The argon impurity seeded at the upstream SOL regions can result in a toroidally asymmetric distribution of electron density and temperature, while a toroidally symmetric distribution is obtained for argon seeded at the strike point regions. The deposition pattern of electron density and temperature shows the several lobe-like and island-like structures on the 3D divertor targets of CFETR with upstream argon injections, whereas the perturbed profile is achieved for argon seeding at the strike point regions. In order to verify the toroidal asymmetry of heat loads distribution, the argon impurity seeded at different poloidal locations has been investigated to estimate its influence on toroidal heat loads on divertor plates. The argon injected at the strike point regions gives rise to a toroidal asymmetry of heat loads distribution on divertor targets, while a toroidal symmetry of heat loads distribution is gained for argon injected at the upstream SOL locations.

Theory-based integrated modelling of tungsten transport in ITER plasmas

Theory-based integrated modelling of tungsten transport in ITER plasmas

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

Abstract 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.

Multi-fidelity information fusion for turbulent transport modeling in magnetic fusion plasma

Maintaining the high-temperature and pressure conditions required for sustained nuclear fusion is challenging due to the turbulent transport that naturally occurs in the plasma. Developing reliable models for turbulent transport is essential for progress in fusion research and development. This study proposes multi-fidelity modeling for the improved accuracy of regression models for turbulent transport in magnetic fusion plasma. Multi-fidelity modeling combines low-fidelity data, which have low accuracy but many data points, with high-fidelity data, which are highly accurate but have few data points or small parameter ranges, to enhance the overall predictive accuracy of a model. We used a multi-fidelity information fusion technique, Nonlinear AutoRegressive Gaussian Process regression (NARGP), to solve the regression problems associated with turbulent transport in plasma. We applied NARGP to (i) merge the low-resolution and high-resolution simulation results, (ii) apply regression of turbulence diffusivity to the experimental dataset using linear analyses, and (iii) adapt the quasi-linear transport model to nonlinear simulation results of a particular discharge. We demonstrated that NARGP improved the prediction accuracy of the plasma turbulent transport model. NARGP offers a robust and versatile method for integrating multi-fidelity data, and its broad applicability may contribute to optimizing fusion reactor design and operation.

Saturation of fishbone instability through zonal flows driven by energetic particle transport in tokamak plasmas

Abstract Gyrokinetic and kinetic-MHD simulations are performed for the fishbone instability in the DIII-D discharge #178631, chosen for validation of first-principles simulations to predict the energetic particle (EP) transport in an ITER pre-fusion baseline scenario. Fishbone modes are found to generate zonal flows, which dominate the fishbone saturation. The underlying mechanisms of the two-way fishbone-zonal flows nonlinear interplay are discussed in details. Numerical and analytical analyses identify the fishbone-induced EP redistribution as the dominant generation mechanism for zonal flows. The zonal flows modify the nonlinear dynamics of phase space zonal structures, which reduces the amount of EPs able to resonate with the mode, leading to a lower saturation amplitude. Simulation results including zonal flows agree quantitatively with DIII-D experimental measurements of the fishbone saturation amplitude and EP transport, supporting this novel saturation mechanism by self-generated zonal flows. Moreover, the wave-particle mode-locking mechanism is shown to determine quantitatively the fishbone frequency down-chirping, as evident in GTC simulation results in agreement with predictions from analytical theory. Finally, the fishbone-induced zonal flows are possibly responsible for the formation of an ion internal transport barrier (ITB) in the DIII-D discharge. Based on the low EP transport and the large zonal flow shearing rates associated with the fishbone instability in gyrokinetic simulations of the ITER scenario, it is conjectured that high performance scenarios could be designed in ITER burning plasmas through fishbone-induced ITBs.

Experimental study on metallic impurity behavior with boronization wall conditioning in EAST tokamak

Operation of EAST tokamak with full metal wall without any wall conditioning are attempted in 2023 and 2024 experimental campaign to address the issues related to ITER tungsten wall operation. It is found that H-mode plasma could be sustained even with a substantial increase in metallic impurity content caused by strong plasma-wall interaction under uncoated metal wall. Boronization wall conditioning is therefore performed to improve the plasma performance with higher injected power. This study aims to quantitatively assess the impact of boronization wall conditioning on metallic impurity concentration and behavior in the EAST tokamak. It is then proved to be an effective wall conditioning approach for significantly controlling high-Z impurity content. In this work, the impurity spectra at extreme ultraviolet (EUV) wavelength range measured by sets of fast-time-response and space-resolved EUV spectrometers are widely used in the data analysis. The variation in the boron content in plasma after boronization are investigated by monitoring the 2nd order of B V line at 48.59 Å. It is found that the persistence time of boron in EAST device after a boronization with 10 g of carborane (C2B10H12) is about 2000 s (∼150 shots) of discharge duration. The impact of different wall conditions (uncoated metal wall and boron coated wall) on metallic impurity content are then quantitatively studied. After boronization, the concentration of tungsten (CW) and molybdenum (CMo) dropped by 85 %, e. g., from 2.0 × 10-4 to 4.1 × 10-5 and from 4.6 × 10-5 to 6.3 × 10-6, respectively. While the concentration of copper (CCu) and iron (CFe) decreased by approximately 50 % and 65 %, respectively, e. g., from 4.3 × 10-5 to 2.1 × 10-5 and from 2.0 × 10-4 to 6.9 × 10-5. A comparison of the line emission profiles from tungsten ions of W26+ − W32+ and W43+ before and after boronization reveals an overall reduction in the intensity while without obvious change in the profile shape, which suggests a reduction in metallic impurities source after boronization instead of altering impurity transport in core plasma significantly.

Drift kinetic electrostatic simulations of the edge localized mode heat pulse

In the present work, electrostatic drift kinetic simulations of parallel plasma transport within the tokamak scrape-off layer (SOL) are conducted using the COGENT code. The SOL configuration is represented in one-dimensional slab geometry, incorporating a heat source localized in the midplane. The heat source parameters correspond to those characterizing edge-localized modes observed in the Joint European Torus (JET) tokamak. The numerical model includes kinetic treatment of both ions and electrons, a simplified model for the gyrokinetic Poisson equation that allows one to step over short time scales associated with fast electrostatic shear Alfvèn waves, and the logical sheath boundary condition (LSBC) that enforces global system quasineutrality. A third-order accurate LSBC is derived to be consistent with the third-order accurate upwind advection scheme utilized in the code, and it was shown to noticeably impact the simulation results, especially parallel heat flux at the target plate. The findings of this study are in agreement with results from preceding fluid and kinetic simulations.

Numerical study of turbulent eddy self-interaction in tokamaks with low magnetic shear. Part I: Linear simulations

Abstract This study examines the impact of low and zero magnetic shear, along with rational values of safety factor, on linear mode behavior in tokamak plasmas. We focus on how magnetic field line topology and parallel domain length influence linear mode structures and growth rates as magnetic shear decreases. Our results show that as magnetic shear is reduced to low values, linear modes can transition between different branches, significantly affecting their characteristics. At zero magnetic shear, accurate modeling requires precisely capturing magnetic topology, as small deviations near rational surfaces can greatly impact growth rates.

Anisotropic charge transport in strongly magnetized relativistic matter

We investigate electrical charge transport in hot magnetized plasma using first-principles quantum field theoretical methods. By employing Kubo’s linear response theory, we express the electrical conductivity tensor in terms of the fermion damping rate in the Landau-level representation. Utilizing leading-order results for the damping rates from a recent study within a gauge theory, we derive the transverse and longitudinal conductivities for a strongly magnetized plasma. The analytical expressions reveal drastically different mechanisms that explain the high anisotropy of charge transport in a magnetized plasma. Specifically, the transverse conductivity is suppressed, while the longitudinal conductivity is enhanced by a strong magnetic field. As in the case of zero magnetic field, longitudinal conduction is determined by the probability of charge carriers to remain in their quantum states without damping. In contrast, transverse conduction critically relies on quantum transitions between Landau levels, effectively lifting charge trapping in localized Landau orbits. We examine the temperature and magnetic field dependence of the transverse and longitudinal electrical conductivities over a wide range of parameters and investigate the effects of a nonzero chemical potential. Additionally, we extend our analysis to strongly coupled quark-gluon plasma and study the impact of the coupling constant on the anisotropy of electrical charge transport.

Surrogate model of turbulent transport in fusion plasmas using machine learning

Abstract The advent of machine learning (ML) has revolutionized the research of plasma confinement, offering new avenues for exploration. It enables the construction of models that effectively streamline the simulation process. While previous first-principles simulations have provided physics-based transport information, they have been inadequate fast for real-time applications or plasma control. In order to address this challenge, we introduce SExFC, a surrogate model based on the Gyro-Landau Extended Fluid Code (ExFC). An approach of physics-based database construction is detailed, as well the validity is illustrated. Through harnessing the power of ML, SExFC offers the capability to deliver rapid and precise predictions, facilitating real-time applications and enhancing plasma control. The proposed model integrates the recurrent neural network (RNN) algorithm, specifically leveraging the Gated Recurrent Unit (GRU) for iterative prediction of flux evolutions based on radial profiles. Therefore, the SExFC model has the potential to enable rapid and physics-based predictions that can be seamlessly integrated into future real-time plasma control systems.

Implementation of a non-axisymmetric magnetic configuration in SOLEDGE3X to simulate 3D toroidal magnetic ripple effects: Application to WEST

The fluid-drift code SOLEDGE3X, developed by CEA/IRFM in collaboration with Aix-Marseille University, is a powerful tool for simulating transport and turbulence in tokamak edge plasmas with axisymmetric magnetic configurations. In tokamaks such as WEST, the pronounced toroidal magnetic ripple significantly affects plasma confinement and power exhaust, modulating both the poloidal and toroidal components of the equilibrium field. Using a discrete Biot–Savart law, the ripple field is calculated as a magnetic perturbation on the SOLEDGE3X mesh. The transport model and parallel gradient solvers have been enhanced to incorporate the new radial magnetic field component. Preliminary simulations of a WEST scenario reveal a heat deposition pattern in the divertor region consistent with observations from infrared camera experiments.