The CQL3D-m continuum bounce-average Fokker-Planck code is adapted for magnetic mirror plasmas [1] and is now routinely used in no-free-parameter classical integrated modeling of mirror devices [2, 3]. In the present effort, we report on two RF methods of plasma heating in mirror machine. The fast ions (FI) are heated by Fast waves at 2nd-4th harmonic, where FIs originate from neutral beam injection at 45 degrees to the magnetic field. The scenario shows an efficient ion heating near the FI bouncing point. The electrons are heated by X-mode launched from the high magnetic field side towards the resonance. Different from the tokamak applications, CQL3D-m provides an evolving self-consistent ambipolar parallel electric field, which determines the shape of the loss cone and hence an accurate confinement time of both ions and electrons. Also, it includes a description of ion and electron sources and sinks (related to charge exchange and impact ionization) which are updated at every time step. CQL3D-m utilizes a fully nonlinear Coulomb collision operator that is important for the significantly non-Maxwellian ion distributions typically established in mirror plasmas.

Ion Cyclotron Range of Frequencies (ICRF) heating is a critical system for the SPARC mission of demonstrating net positive fusion gain. In the first campaign, 20 MW of installed power at 120 MHz will be supplied to 10 four-strap antennas, arranged in poloidal pairs. The matching network is designed to accommodate for a range of loading conditions and a fast controller adjusts the matching during a pulse with frequency modulation of ±1 MHz. For the main L-mode scenario of the first experimental campaign, the power coupling and absorption is analysed in this work. Several feeding schemes are compared and limits on the amount of the total coupled power are evaluated. Coupling of the full 20 MW power is possible well within the limit of the peak electric field in the transmission line of 15 kV/cm. The 3He minority and 2nd harmonic T heating scheme is validated in full-wave modelling to be efficient for heating plasma in the SPARC L-mode Q>1 scenario, with dominant ion heating and efficient single-pass absorption. A range of ICRF wave parameters and minority concentration would be suitable for operation and allow tailoring the heating properties for plasma conditions and experimental objectives.

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

OpenStar Technologies is pursuing the levitated dipole (LD) as a highly modular, loosely-coupled system that leverages their expertise in high temperature superconductor (HTS) technology. The next generation experiment at OpenStar, Tahi (Ma¯ori for “first”), will demonstrate the generation and confinement of fast ions in a levitated dipole for the first time. Ion cyclotron range of frequency (ICRF) heating is a leading candidate for energetic ion formation in Tahi. A frequency in the 10 MHz range will be used for H minority heating or D majority heating with waves launched from an antenna located above the floating coil. Unlike a tokamak, where the targeted cyclotron resonance is typically a vertical path through the center of the plasma, in a dipole the resonance location follows a C-shaped path from the separatrix to the center of the plasma. The value of B also varies significantly within the confined plasma resulting in a large number of cyclotron harmonics present in the low field region. Furthermore, levitated dipoles contain a “first closed flux surface” surrounding the floating coil, in addition to the traditional separatrix /last closed flux surface. Simulation e fforts using full-wave ICRF codes show that ICRF heating of a levitated dipole reactor is feasible using a pair of toroidal current straps phased to launch the appropriate parallel ( i.e. poloidal) refractive index.

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

A real-time capable core Ion Cyclotron Range of Frequencies (ICRF) heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.

Reproducing fast-ion enhanced fusion rates from ion-cyclotron resonance heating (ICRH) in tokamaks requires the self-consistent coupling of a full-wave solver and a Fokker–Planck solver, which evolves multiple simultaneously resonant ion species. We introduce a new self-consistent model that iterates the TORIC full-wave solver with the CQL3D Fokker–Planck solver using the integrated plasma simulator (IPS). This model evolves the bounce-averaged ion distribution functions in both parallel and perpendicular velocity-space with a quasilinear radio frequency (RF) diffusion operator valid in the ion finite Larmor radius (FLR) limit and the RF electric fields with the resultant non-Maxwellian FLR dielectric tensor. This produces non-Maxwellian ICRH simulations that are fully self-consistent, fast, and interoperable with integrated modeling frameworks, such as TRANSP/GACODE/IPS-FASTRAN. We demonstrate our model's capabilities by validating it against experimental data in Alcator C-Mod. We then perform the first RF heating simulations of SPARC using self-consistent non-Maxwellian ion distributions to investigate the potential to enhance fusion rates using ion cyclotron resonance heating generated fast ions.

As the Ion Cyclotron Radio Frequency range (ICRF) heating becomes more favorable in fusion devices, the urgency of predicting and mitigating impurity generation that arises from it becomes more pressing. In the ICRF regime, rectified Radio Frequency (RF) sheaths are known to form at antenna and material edges that influence negative effects like sputtering and a decrease in heating efficiency. Methods to mitigate the formation of these RF sheaths through RF image currents cancellation have been experimentally studied. A power-phasing scan done on Alcator C-Mod in which the amount of power on the two inner straps ( P in ) versus the total 4 straps ( P tot ) was varied showed a minimization of enhanced potentials between P in / P tot ∼ 0.7–0.9 while impurities were minimized for P in / P tot ∼ 0.5–0.8. New capabilities in the realm of representing the RF sheath numerically now allow for these experiments to be simulated. Given the size of the sheath relative to the scale of the device, it can be approximated as a Boundary Condition (BC). A new parallelized cold-plasma wave equation solver called Stix implements a non-linear sheath impedance model BC formulated by Myra et al (2015 Phys. Plasmas 22 062507) through the method of finite elements using the MFEM library [ http://mfem.org ]. It is seen that Stix shows qualitative agreement with the measured C-Mod enhanced potentials.

Treatments of plasma waves usually assume homogeneity, but the parallel gradients ubiquitous in plasmas can modify wave propagation and absorption. We derive a quasilocal inhomogeneous correction to the plasma dielectric for arbitrary distributions by expanding the phase correlation integral and develop a novel integration technique that allows our correction to be applied in many situations and has greater accuracy than other inhomogeneous dielectric formulas found in the literature. We apply this dielectric tensor to the lower-hybrid current drive problem and demonstrate that inhomogeneous wave damping does not affect the lower-hybrid wave's linear damping condition, and in the non-Maxwellian problem damping and propagation should remain unchanged except in the case of waves with very large phase velocities.

Ion cyclotron radio frequency range (ICRF) power plays an important role in heating and current drive in fusion devices. However, experiments show that in the ICRF regime there is a formation of a radio frequency (RF) sheath at the material and antenna boundaries that influences sputtering and power dissipation. Given the size of the sheath relative to the scale of the device, it can be approximated as a boundary condition (BC). Electromagnetic field solvers in the ICRF regime typically treat material boundaries as perfectly conducting, thus ignoring the effect of the RF sheath. Here we describe progress on implementing a model for the RF sheath based on a finite impedance sheath BC formulated by J. Myra and D. A. D'Ippolito, Physics of Plasmas 22 (2015) which provides a representation of the RF rectified sheath including capacitive and resistive effects. This research will discuss the results from the development of a parallelized cold-plasma wave equation solver Stix that implements this non-linear sheath impedance BC through the method of finite elements in pseudo-1D and pseudo-2D using the MFEM library. The verification and comparison of the sheath BC from Stix with results from H. Kohno and J. Myra, Computer Physics Communications 220 129-142 (2017) will also be discussed.

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations.A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications.More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing.The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing.Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n || , Z e f f ,V loop , P LHCD ) with sufficient density in all regions of parameter space.The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space.Data-driven surrogate models also allow for solving inverse and "lateral" problems.A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile.The πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

A mathematical model for the charging simulation of non-insulated superconducting pancake solenoids is presented. Numerical solutions are obtained by the simulation model using a variety of solvers. A scalability analysis is performed for both direct and preconditioned iterative solvers for four different pancakes solenoids with varying number of turns and mesh elements. It is found that even with two extremely different time scales in the system an iterative solver combination (FGMRES-GMRES) in conjunction with the parallel Auxiliary Space Maxwell Solver (AMS) preconditioner outperforms a parallelized direct solver (MUMPS). In general, the computational time of the iterative solver is found to increase with the number of turns in the solenoids and/or the conductivity assumed for the superconducting material.

We estimate the amount of $^{37}$Ar produced in natural xenon via cosmic ray-induced spallation, an inevitable consequence of the transportation and storage of xenon on the Earth's surface. We then calculate the resulting $^{37}$Ar concentration in a 10-tonne payload~(similar to that of the LUX-ZEPLIN experiment) assuming a representative schedule of xenon purification, storage and delivery to the underground facility. Using the spallation model by Silberberg and Tsao, the sea level production rate of $^{37}$Ar in natural xenon is estimated to be 0.024~atoms/kg/day. Assuming the xenon is successively purified to remove radioactive contaminants in 1-tonne batches at a rate of 1~tonne/month, the average $^{37}$Ar activity after 10~tonnes are purified and transported underground is 0.058--0.090~$\mu$Bq/kg, depending on the degree of argon removal during above-ground purification. Such cosmogenic $^{37}$Ar will appear as a noticeable background in the early science data, while decaying with a 35~day half-life. This newly-noticed production mechanism of $^{37}$Ar should be considered when planning for future liquid xenon-based experiments.

Raytracing/Fokker–Planck (FP) simulations used to model lower-hybrid current drive (LHCD) often fail to reproduce experimental results, particularly when LHCD is weakly damped. A proposed reason for this discrepancy is the lack of ‘full-wave’ effects, such as diffraction and interference, in raytracing simulations and the breakdown of the raytracing approximation. Previous studies of LHCD using non-Maxwellian full-wave/FP simulations have been performed, but these simulations were not self-consistent and enforced power conservation between the FP and full-wave code using a numerical rescaling factor. Here, we have created a fully self-consistent full-wave/FP model for LHCD that is automatically power conserving. This was accomplished by coupling an overhauled version of the non-Maxwellian TORLH full-wave solver and the CQL3D FP code using the Integrated Plasma Simulator. We performed converged full-wave/FP simulations of Alcator C-Mod discharges and compared them with raytracing. We found that excellent agreement in the power deposition profiles from raytracing and TORLH could be obtained, however, TORLH had somewhat lower current drive efficiency and broader power deposition profiles in some cases. This discrepancy appears to be a result of numerical limitations present in the TORLH model and a small amount of diffractional broadening of the TORLH wave spectrum. Our results suggest full-wave simulation of LHCD is likely not necessary as diffraction and interference represented only a small correction that could not account for the differences between simulations and experiment.

Three machine learning techniques (multilayer perceptron, random forest and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modelling and real-time control applications. The machine learning models use a database of more than 16 000 GENRAY/CQL3D simulations for training, validation and testing. Latin hypercube sampling methods ensure that the database covers the range of nine input parameters ( $n_{e0}$ , $T_{e0}$ , $I_p$ , $B_t$ , $R_0$ , $n_{\|}$ , $Z_{{\rm eff}}$ , $V_{{\rm loop}}$ and $P_{{\rm LHCD}}$ ) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to $\sim$ ms with high accuracy across the input parameter space.

The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019-2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (alpha) physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER.

Lower-hybrid current drive (LHCD) actuators are important components of modern day fusion experiments as well as proposed fusion reactors. However, simulations of LHCD often differ substantially from experimental results, and from each other, especially in the inferred power deposition profile shape. Here we investigate some possible causes of this discrepancy; ‘full-wave’ effects such as interference and diffraction, which are omitted from standard raytracing simulations and the breakdown of the raytracing near reflections and caustics. We compare raytracing simulations to state-of-the-art full-wave simulations using matched hot-plasma dielectric tensors in realistic tokamak scenarios for the first time. We show that differences between full-wave simulations and raytracing in previous work were primarily due to numerical and physical inconsistencies in the simulations, and we demonstrate that quantitative agreement between raytracing and converged full-wave simulations can be obtained in reactor relevant-scenarios and qualitative agreement can be obtained in situations with weak damping.

This paper summarizes recent progress in modeling the interaction between ion cyclotron range of frequency (ICRF) waves and edge plasma with application to ASDEX Upgrade. The basic theories, the development of ICRF and edge plasma codes, the integrated modeling methods and some key results are reviewed. In particular, the following physical aspects are discussed: (1) ICRF power coupling; (2) slow wave propagation; (3) ICRF-rectified sheath; (4) ICRF-induced convection; (5) ICRF-edge turbulence interaction. Moreover, comprehensive integrated modeling strategies by including all necessary codes in one package and solving multiple physical issues self-consistently are discussed.

The SPARC tokamak project, currently in engineering design, aims to achieve breakeven and burning plasma conditions in a compact device, thanks to new developments in high-temperature superconductor technology. With a magnetic field of 12.2 T on axis and 8.7 MA of plasma current, SPARC is predicted to produce 140 MW of fusion power with a plasma gain of Q ≈ 11, providing ample margin with respect to its mission of Q > 2. All tokamak systems are being designed to produce this landmark plasma discharge, thus enabling the study of burning plasma physics and tokamak operations in reactor relevant conditions to pave the way for the design and construction of a compact, high-field fusion power plant. Construction of SPARC is planned to begin by mid-2021.

This paper summarizes the physical principles behind the novel three-ion scenarios using radio frequency waves in the ion cyclotron range of frequencies (ICRF). We discuss how to transform mode conversion electron heating into a new flexible ICRF technique for ion cyclotron heating and fast-ion generation in multi-ion species plasmas. The theoretical section provides practical recipes for selecting the plasma composition to realize three-ion ICRF scenarios, including two equivalent possibilities for the choice of resonant absorbers that have been identified. The theoretical findings have been convincingly confirmed by the proof-of-principle experiments in mixed H–D plasmas on the Alcator C-Mod and JET tokamaks, using thermal 3He and fast D ions from neutral beam injection as resonant absorbers. Since 2018, significant progress has been made on the ASDEX Upgrade and JET tokamaks in H–4He and H–D plasmas, guided by the ITER needs. Furthermore, the scenario was also successfully applied in JET D–3He plasmas as a technique to generate fusion-born alpha particles and study effects of fast ions on plasma confinement under ITER-relevant plasma heating conditions. Tuned for the central deposition of ICRF power in a small region in the plasma core of large devices such as JET, three-ion ICRF scenarios are efficient in generating large populations of passing fast ions and modifying the q-profile. Recent experimental and modeling developments have expanded the use of three-ion scenarios from dedicated ICRF studies to a flexible tool with a broad range of different applications in fusion research.