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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D

We introduce EFIT-Prime, a novel machine learning surrogate model for EFIT (Equilibrium FIT) that integrates probabilistic and physics-informed methodologies to overcome typical limitations associated with deterministic and ad hoc neural network architectures. EFIT-Prime utilizes a neural architecture search-based deep ensemble for robust uncertainty quantification, providing scalable and efficient neural architectures that comprehensively quantify both data and model uncertainties. Physically informed by the Grad–Shafranov equation, EFIT-Prime applies a constraint on the current density J tor and a smoothness constraint on the first derivative of the poloidal flux, ensuring physically plausible solutions. Furthermore, the spatial location of the diagnostics is explicitly incorporated in the inputs to account for their spatial correlation. Extensive evaluations demonstrate EFIT-Prime's accuracy and robustness across diverse scenarios, most notably showing good generalization on negative-triangularity discharges that were excluded from training. Timing studies indicate an ensemble inference time of 15 ms for predicting a new equilibrium, offering the possibility of plasma control in real-time, if the model is optimized for speed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Augmenting machine learning of Grad–Shafranov equilibrium reconstruction with Green's functions

This work presents a method for predicting plasma equilibria in tokamak fusion experiments and reactors. The approach involves representing the plasma current as a linear combination of basis functions using principal component analysis of plasma toroidal current densities (J t ) from the EFIT-AI equilibrium database. Then utilizing EFIT's Green's function tables, basis functions are created for the poloidal flux (ψ) and diagnostics generated from the toroidal current (J t ). Similar to the idea of a physics-informed neural network (NN), this physically enforces consistency between ψ, J t , and the synthetic diagnostics. First, the predictive capability of a least squares technique to minimize the error on the synthetic diagnostics is employed. The results show that the method achieves high accuracy in predicting ψ and moderate accuracy in predicting J t with median R 2 = 0.9993 and R 2 = 0.978, respectively. A comprehensive NN using a network architecture search is also employed to predict the coefficients of the basis functions. The NN demonstrates significantly better performance compared to the least squares method with median R 2 = 0.9997 and 0.9916 for J t and ψ, respectively. The robustness of the method is evaluated by handling missing or incorrect data through the least squares filling of missing data, which shows that the NN prediction remains strong even with a reduced number of diagnostics. Additionally, the method is tested on plasmas outside of the training range showing reasonable results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Application of machine learning and artificial intelligence to extend EFIT equilibrium reconstruction

Recent progress in the application of machine learning (ML)/artificial intelligence (AI) algorithms to improve the Equilibrium Fitting (EFIT) code equilibrium reconstruction for fusion data analysis applications is presented. A device-independent portable core equilibrium solver capable of computing or reconstructing equilibrium for different tokamaks has been created to facilitate adaptation of ML/AI algorithms. A large EFIT database comprising of DIII-D magnetic, motional Stark effect, and kinetic reconstruction data has been generated for developments of EFIT model-order-reduction (MOR) surrogate models to reconstruct approximate equilibrium solutions. Furthermore, a neural-network MOR surrogate model has been successfully trained and tested using the magnetically reconstructed datasets with encouraging results. Other progress includes developments of a Gaussian process Bayesian framework that can adapt its many hyperparameters to improve processing of experimental input data and a 3D perturbed equilibrium database from toroidal full magnetohydrodynamic linear response modeling using the Magnetohydrodynamic Resistive Spectrum - Feedback (MARS-F) code for developments of 3D-MOR surrogate models.

Gaussian process↗
DOE OSTI2024

Examining transport and integrated modeling predictive capabilities for negative-triangularity scenarios

This paper investigates the predictive capabilities of TGYRO and TGLF models in assessing the performance of negative triangularity (NT) plasmas compared to positive triangularity (PT) plasmas in fusion devices. TGYRO predicts kinetic profiles, while TGLF analyzes turbulent transport. The study reveals that TGYRO reasonably predicts NT profiles similar to PT, although it overpredicts the high-power scenarios where there is increased experimental MHD activity. TGLF analysis finds reduced linear growth rates in NT and altered flux spectra relative to PT. Additionally, the TGLF SAT0 saturation model is observed to predict high-k transport and a reduction of particle transport with the electron temperature gradient. These findings are further corroborated by core-pedestal modeling using the Stability Transport Equilibrium Pedestal workflow, showing stronger confinement improvements in NT, particularly at higher power densities for the SAT0 saturation model. Furthermore, the study underscores the importance of accurately capturing turbulence saturation mechanisms for NT in order to project its performance accurately in fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A 3D helical filament surrogate model for 3D tokamak equilibria

A novel approach for efficient representation of three-dimensional (3D) tokamak equilibria is investigated, where a set of helical current filaments occupying the plasma region are employed to resolve deviations from the two-dimensional (2D) axi-symmetric state. A discrete set of 3D filaments, located at rational surfaces for a given toroidal mode number n and following the 2D equilibrium field lines (thus forming closed current loops), are found to provide a surrogate model of 3D equilibria with reasonable accuracy. Specifically, application of the filament model to 3D perturbed equilibria, due to the resonant magnetic perturbation (RMP) in DIII-D and MAST-U discharges, reveals that (1) a single helical filament per rational surface is sufficient; (2) 21 such helical filaments are capable of representing the n = 2 3D response field in MAST-U with less than 10% relative error as compared to that computed by a full magnetohydrodynamic code; (3) optimizing currents (both amplitude and phase) flowing in 3D filaments with fixed geometry, the highest accuracy fitting is found to depend on the characteristics of the 3D equilibria such as the coil current phasing of the RMP coils in our case studies. Here, whis filament approach is also applicable for generating surrogate models of other type of 3D tokamak equilibria, including those during the initial phase of the plasma disruption.

MARS-F↗
DOE OSTI2020

Progress in extending high poloidal beta scenarios on DIII-D towards a steady-state fusion reactor and impact of energetic particles

To prepare for steady-state operation of future fusion reactors (e.g. the International Thermonuclear Experimental Reactor and China Fusion Engineering Test Reactor (CFETR)), experiments on DIII-D have extended the high poloidal beta ( β P ) scenario to reactor-relevant edge safety factor q 95 ~ 6.0, while maintaining a large-radius internal transport barrier (ITB) using negative magnetic shear. Excellent energy confinement quality ( H 98y2 > 1.5) is sustained at high normalized beta ( β N ~ 3.5). This high-performance ITB state with Greenwald density fraction near 100% and q min ≥ 3 is achieved with toroidal plasma rotation V tor ~ 0 at ρ ≥ 0.6. This is a key result for reactors expected to have low V tor . At high β P (≥1.9), large Shafranov shift can stabilize turbulence leading to a high confinement state with a low pedestal and an ITB. At lower β P (<1.9), negative magnetic shear in the plasma core contributes to turbulence suppression and can compensate for reduced Shafranov shift to continue to access a large-radius ITB and excellent confinement with low V tor , consistent with the results of gyrofluid transport simulations. These high- β P cases are characterized by weak/no Alfvén eigenmodes (a.e.) and classical fast-ion transport. At high density, the fast-ion deceleration time decreases and Δ β fast is lower; these reduce a.e. drive. The reverse-shear Alfvén eigenmodes are weaker or stable because the negative magnetic shear region is located at higher radius, away from the peaked fast-ion profile. Resistive wall modes can be a limitation at simultaneous high β N , low internal inductance, and low rotation. Analysis suggests that additional off-axis external current drive could provide a more stable path at reduced q 95 . Based on a DIII-D high- β P plasma with large-radius ITB, two scenarios are proposed for CFETR Q = 5 steady-state operation with ~1 GW fusion power: a lower-$l_i$($l_i$ ~ 0.66) and a higher-$l_i$($l_i$ ~ 0.75) case. Using a Landau closure model, multiple energetic particle (EP) effects on the a.e. stability are analyzed modifying the growth rate of the a.e.s triggered by the neutral-beam-injection EPs and alpha particles, although the stabilizing/destabilizing effect is weak for the cases analyzed. The stabilizing effects of the combined EP species β , energy, and density profile in CFETR need further investigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Neural-network accelerated coupled core-pedestal simulations with self-consistent transport of impurities and compatible with ITER IMAS

pedestal structure, current profile, and plasma equilibrium physics has been developed and tested against a DIII-D discharge. Here, key features of the achieved core-pedestal coupled workflow are its ability to account for the transport of impurities in the plasma self-consistently, as well as its use of machine learning accelerated models for the pedestal structure and for the turbulent transport physics. Notably, the coupled workflow is implemented within the OMFIT framework, and makes use of the ITER integrated modeling and analysis suite (IMAS) data structure for exchanging data among the physics codes that are involved in the simulations. Such technical advance has been facilitated by the development of a new numerical library named OMAS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Toroidal modeling of runaway avalanche in DIII-D discharges

Abstract A toroidal modeling tool is developed to study the runaway electron (RE) avalanche production process in tokamak plasmas, by coupling the Rosenbluth–Putvinski avalanche model (Rosenbluth and Putvinski 1997 Nucl. Fusion 37 1355) with an n = 0 magneto-hydrodynamic (MHD) solver. Initial value numerical simulations are carried out for two DIII-D discharges with different plasma shapes (one near circular, and the other with high elongation). It is found that, assuming the same level of about 1% seed current level, the Rosenbluth–Putvinski model somewhat underestimates the RE plateau current for the circular-shaped plasma, as compared with that measured in DIII-D experiments. For an elongated, higher current plasma, simulations find strong runaway current avalanche production despite the lack of measured plateau RE current in experiments. A possible reason for this discrepancy is a lack of additional RE dissipation physics in the present two-dimensional model. Systematic scans of the plasma boundary shape, at fixed pre-disruption plasma current, find that the plasma elongation helps to reduce the RE avalanche production, confirming recent results obtained with an analytic model (Fülöp et al 2020 J. Plasma Phys. 86 474860101). The effect of the plasma triangularity (either positive or negative), on the other hand, has a minor effect. On the physics side, the avalanche process involves two competing mechanisms associated with the electric field. On the one hand, a stronger electric field produces a higher instantaneous avalanche growth rate. On the other hand, a fast growing RE current quickly reduces the fraction of the conduction current together with the electric field, and hence a faster dissipation of the poloidal flux. As a final result of these two dynamic processes, the runaway plateau current is not always the largest with the strongest initial electric field. These results lay the foundation for future self-consistent inclusion of the MHD dynamics and the RE amplification process.

Physics↗
DOE OSTI2022

Linear simulation of magnetohydrodynamic plasma response to three-dimensional magnetic perturbations in high-β P plasmas

In this work, we report the numerical analyses of linear magnetohydrodynamics (MHD) plasma response to applied three-dimensional magnetic perturbations (MPs) in a joint DIII-D/EAST collaboration on high-β P (poloidal beta) plasmas, utilizing the extended-MHD code M3D-C1, with the purpose of realizing a better understanding of the existing experiment in which the n=3 MPs were applied to such high-β P plasmas attempting to control large amplitude type-I ELMs. Such high-β P plasmas obtained at the DIII-D tokamak feature an upper-biased double null configuration, a high edge safety factor q 95 ~6.4, and a stable internal transport barrier (ITB) leading to relatively high core pressures. Single-fluid simulations show that the plasma response to n=3 MPs, including both non-resonant/kinking and resonant components, is significantly weaker than that to n=1 or 2 MPs. To survey the impact of q 95 on plasma response to applied MPs, the SEGWAY (Self-consistent Equilibrium Generating Workflow for AnalYsis) module, developed in the OMFIT integrated modelling framework, is employed to generate a series of equilibria with a wide range of q 95 while other key parameters including the normalized beta, electron density at pedestal top, and plasma shape are kept fixed. Compared to the vacuum response, single-fluid M3D-C1 simulations predict a much more significant decrease of resonant plasma response to the applied n=3 MPs at the maximum penetration radii as q 95 increases. In contrast to single-fluid simulation results showing resonant penetration occurs only near the pedestal top where the E×B toroidal rotation frequency is zero, two-fluid simulations show two comparable resonant penetrations locating near the pedestal top and the ITB foot, where the perpendicular electron rotation frequency is zero. Such resonant field penetration near the ITB foot may be responsible for the observed formation of a staircase structure in both electron density and temperature profiles and thereby a considerable deterioration of global plasma performance when MPs are applied in high-β P plasmas. Motivated by this numerical work, we provide some ideas for the future research, with the purpose of realizing effective ELM control in such high-β P plasmas on the DIII-D and EAST devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Non-linear MHD modelling of edge localized modes suppression by resonant magnetic perturbations in ITER

Edge localized modes (ELMs) suppression by resonant magnetic perturbations (RMPs) was studied with the non-linear magneto-hydro-dynamic (MHD) code JOREK for the ITER H-mode scenarios at 15 MA, 12.5 MA, 10 MA/5.3 T. In this study, the main aim was to demonstrate that ELMs can be suppressed by RMPs while the divertor 3D footprints of heat and particle fluxes remain within divertor material limits. The unstable peeling–ballooning modes responsible for ELMs without RMPs were modelled first for each scenario using numerically accessible parameters for ITER. Then the stabilization of ELMs by RMPs was modelled with the same parameters. RMP spectra, optimized by the linear MHD MARS-F code, with main toroidal harmonics N = 2, N = 3, N = 4 have been used as boundary conditions of the computational domain of JOREK, including realistic RMP coils, main plasma, scrape off layer (SOL) divertor and realistic first wall. The model includes all relevant plasma flows: toroidal rotation, two fluid diamagnetic effects and neoclassical poloidal friction. With RMPs, the main toroidal harmonic and the non-linearly coupled harmonics remain dominant at the plasma edge, producing saturated modes and a continuous MHD turbulent transport thereby avoiding ELM crashes in all scenarios considered here. The threshold for ELM suppression was found at a maximum RMP coils current of 45 kAt–60 kAt compared to the coils maximum capability of 90 kAt. In the high beta poloidal steady-state 10 MA/5.3 T scenario, a rotating QH-mode without ELMs was observed even without RMPs. In this scenario with RMPs N = 3, N = 4 at 20 kAt maximum current in RMP coils, similar QH-mode behaviour was observed however with dominant edge harmonic corresponding to the main toroidal number of RMPs. The present MHD modelling was limited in time by few tens of ms after RMPs were switched on until the magnetic energy of the modes saturates. As a consequence the thermal energy was still evolving on this time scale, far from the ITER confinement time scale and hence only the form of 3D footprints on the divertor targets can be indicated within this set-up. Also note, that the divertor physics was missing in this model, so realistic values of fluxes are out of reach in this modelling. However the stationary 3D divertor and particle fluxes could be simply extrapolated from these results to the stationary situation considering that a large power fraction should be radiated in the core and SOL and only about 50 MW power is going to the divertor, which is an arbitrary, but reasonable number used here. The 3D footprints with RMPs show the characteristic splitting with the main RMP toroidal symmetry. The maximum radial extension of the footprints typically was ~20 cm in inner divertor and ~40 cm in outer divertor with stationary heat fluxes decreasing further out from the initial strike point from ~5 MW m ₋2 to ~1 MW m ₋2 assuming a total power in the divertor and walls is 50 MW. The heat fluxes remain within the divertor target and baffle areas, however with rather small margin in the outer divertor which could be an issue for the first wall especially in transient regimes when part of the plasma thermal energy is released due to switching on the RMP coils. This fact should be considered when RMPs are applied with a more favorable application before or soon after the L–H transition, although optimization is required to avoid increasing the L–H power threshold with RMPs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Doubling off-axis electron cyclotron current drive efficiency via velocity space engineering

For the first time, experiments on the DIII-D tokamak have demonstrated electron cyclotron current drive with more than double the conventional efficiency by tailoring the wave–particle interactions in velocity space using a novel ‘top launch’ geometry. Steering the EC waves to propagate nearly parallel to the resonance drives current more efficiently by (1) selective damping on electrons with higher parallel velocity v ||, and (2) longer absorption path to compensate for inherently weaker absorption at higher v ||. Experiments using a fixed-injection top launch system find an optimal velocity space interaction for maximum current drive efficiency at ρ ~ 0.5 where the ease of drawing out a high v || electron tail is balanced by sufficient absorption.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Simulation of runaway electron production with CQL3D coupled to NIMROD

Abstract A coupling between two distinctly different codes—one magnetohydrodynamic (MHD) and another kinetic—is achieved and applied for simulation of runaway electron (RE) production. The 3D initial value MHD code NIMROD simulates a DIII-D pure neon shattered pellet injection plasma quench including the propagation and ablation of the fragments, ionization and recombination of the impurities, and the radiated and transported energies. The field data from NIMROD is then used by the bounce-averaged Fokker–Planck Collisional QuasiLinear 3D (CQL3D) kinetic code to simulate the production of REs and their radial transport. The coupling procedure involves mapping of data between different grids and adjustment of the NIMROD toroidal electric field when REs appear. It is shown that without the radial transport, a large RE current is generated, up to 30% of the pre-pellet ohmic current. However, when the radial transport is included in CQL3D, the RE current is reduced to undetectable level, consistent with experiment. Various forms of the radial diffusion are surveyed to determine conditions when the fast electrons would not have time to be accelerated to relativistic energies before they are lost to chamber wall.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Surrogate models for plasma displacement and current in 3D perturbed magnetohydrodynamic equilibria in tokamaks

Abstract A numerical database of over one thousand perturbed three-dimensional (3D) equilibria has been generated, constructed based on the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) computed plasma response to the externally applied 3D field sources in multiple tokamak devices. Perturbed 3D equilibria with the n = 1–4 ( n is the toroidal mode number) toroidal periodicity are computed. Surrogate models are created for the computed perturbed 3D equilibrium utilizing model order reduction (MOR) techniques. In particular, retaining the first few eigenstates from the singular value decomposition (SVD) of the data is found to produce reasonably accurate MOR-representations for the key perturbed quantities, such as the perturbed parallel plasma current density and the plasma radial displacement. SVD also helps to reveal the core versus edge plasma response to the applied 3D field. For the database covering the conventional aspect ratio devices, about 95% of data can be represented by the truncated SVD-series with inclusion of only the first five eigenstates, achieving a relative error (RE) below 20%. The MOR-data is further utilized to train neural networks (NNs) to enable fast reconstruction of perturbed 3D equilibria, based on the two-dimensional equilibrium input and the 3D source field. The best NN-training is achieved for the MOR-data obtained with a global SVD approach, where the full set of samples used for NN training and testing are stretched and form a large matrix which is then subject to SVD. The fully connected multi-layer perceptron, with one or two hidden layers, can be trained to predict the MOR-data with less than 10% RE. As a key insight, a better strategy is to train separate NNs for the plasma response fields with different toroidal mode numbers. It is also better to apply MOR and to subsequently train NNs separately for conventional and low aspect ratio devices, due to enhanced toroidal coupling of Fourier spectra in the plasma response in the latter case.

3D equilibrium↗
DOE OSTI2023

Self-consistent investigation of density fueling needs on ITER and CFETR utilizing the new Pellet Ablation Module

Abstract Self-consistent modeling using the stability, transport, equilibrium, and pedestal (STEP) workflow in the OMFIT integrated modeling framework (predicting pedestal with EPED, core profiles with TGYRO, current profile with ONETWO, and EFIT for equilibrium) suggests ITER and future devices such as China Fusion Engineering Test Reactor (CFETR) Zhuang et al (2019 Nucl. Fusion 59 112010) will benefit from high-density operation (Greenwald limit fraction f g w ≈ 0.7−1.3). Regimes with an operational density near the Greenwald limit will likely need peaked density profiles so that the pedestal density remains below the Greenwald limit. Peaked density profiles can be achieved with the help of pellet injection. A flexible Pellet Ablation Module (PAM), which predicts the density source based on a comprehensive analytical pellet ablation model, has been developed for predicting pellet fueling for transport studies, and has been incorporated into the STEP workflow for predictive modeling. This workflow is applied to DIII-D and finds good agreement with experiments. On ITER the effect of pellet fueling is examined in an advanced inductive scenario, where a fusion gain of up to Q = 9 is predicted with strong central pellet fueling. On CFETR, with a mid-radius density source, an average of 1.5 × 10 22 electrons s −1 are required to achieve the density and temperature profiles necessary for the 1000 MW advanced scenario with a tritium burn-up fraction of ∼ 3 % .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

MHD modeling of shattered pellet injection in JET

Abstract Nonlinear 3D MHD simulations of shattered-pellet injection (SPI) in JET show prototypical SPI-driven disruptions using the M3D-C1 and NIMROD extended-MHD codes. Initially, radiation-driven thermal quenches are accelerated by MHD activity as the pellet crosses rational surfaces, leading to a radiation spike, global stochasticization of the magnetic field, and a complete thermal quench. Eventually, current quenches, preceded by a current spike are seen as the Ohmic heating becomes equal to the radiative cooling. The results are qualitatively similar for both a single monolithic pellet, pencil-beam model, and a realistic shatter to represent the SPI plume. A scan in viscosity from 500 to 2000 m 2 s −1 for MHD simulations finds that reducing viscosity increases MHD activity and decreases thermal quench time slightly. A realistic cloud of fragments modeling shows that mixed-D–Ne pellet travels deeper into the plasma core before the thermal quench. At the slow pellet speeds, the pellet is found to be moving slowly enough inward that even the 5% neon in the mixed pellet is enough to effectively radiate the thermal energy available. Radiation toroidal peaking is predicted to be at levels consistent with experimental observations and reduced as the pellet travels deeper into the plasma. These simulations lay the ground work for more-sophisticated validative and predictive modeling of SPI in JET using both M3D-C1 and NIMROD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗