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105 records · Page 6

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↗

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↗

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↗

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)↗

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.

machine learning↗

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↗

Fast Particle-Wave Interactions and Alfvén Eigenmodes in JET Tokamak Plasmas

This document serves as the closeout report of DOE Grant Award No. DE-FG02-99ER54563 with project period 1 April 2015 through 31 March 2020. The project comprised the international collaboration between MIT and EU scientists on the JET facility to improve our understanding of the physics of energetic particle-wave interactions by measuring the damping rates of stable Alfvén Eigenmodes (AEs) and unstable energetic particle driven modes. More specifically, this project involved the continued participation of MIT, the Culham Centre for Fusion Energy, the Swiss Plasma Center, and theorists from various European laboratories and from UC Irvine. Past contributions from the University of São Paulo are gratefully acknowledged. The Alfvén Eigenmode Active Diagnostic (AEAD) on JET discharges was successfully upgraded in this period and has extracted physically useful information, in primarily deuterium plasma discharges. It is expected that such experiments would be continued during the DT campaign in CY 2021 to assess the damping rates of similar modes in the presence of alpha particles, a product of fusing burning plasma. Only JET would carry out such experiments in the near term in the world. It is important to note that this collaboration was continued under DOE Grant Award No. DE-SC0014264 from 1 April 2020 through the present. In this grant period, the AEAD was upgraded with a set of individual amplifiers for each of a set of six antennas in two toroidally opposite locations. These new amplifiers allowed targeted selection of the antennas’ toroidal spectrum for AEs of interest with toroidal mode number | n | ≤ 20. The resonant detection and measurement of the damping rates of AEs was obtained from magnetic probes that could be compared with theory and simulations. This is a key topic of investigation for ITER and all other next-step fusion experiments, where such modes will interact with energetic particles produced by fusion reactions (alpha particles), Neutral Beam Injection (NBI) and Ion Cyclotron Resonance Heating (ICRH). The majority of the observations during this period were of Toroidal Alfvén Eigenmodes (TAEs) as these are most commonly observed on JET; a number of measurements were made during dedicated TAE experiments. However, a new set of lower frequency band filters were procured with the goal of studying Geodesic Acoustic Modes (GAMs), Beta (Acoustic) AEs (BAE/BAAEs), and Reverse Shear AEs (RSAEs), also predicted by theory. Commissioning and optimizations were successfully completed in this period, and the diagnostic has been in operation during the more recent JET campaigns. Initial results have been obtained in dedicated TAE experiments and successfully compared to drift-kinetic theory. A wide range of theoretical studies have been undertaken in support of the upcoming JET campaigns experiments. To supplement the ongoing use of ideal MHD codes, such as MISHKA during the studies of TAEs, gyrokinetic simulations of low frequency AEs were performed in collaboration with UC Irvine. The Gyrokinetic Toroidal Code (GTC) was used to determine the structure, frequencies and stability of AEs in JET plasmas. Thus, a solid scientific foundation has been laid for future DT campaigns in JET in the 2021 operation period when the damping rates of relevant modes in the presence of alpha particles could be assessed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗

Creating the Distributed Energy Resources Education Center (DEREC)

The built environment in the United States consumes 40% of the energy generated and emits roughly the same percentage of total carbon footprint. Distributed energy resources (DER), small or modular energy generation and storage technologies, present the nation with an opportunity to substantially improve those metrics while securing the nation’s energy independence. As opportunities increase for implementing such technologies, they also continue to evolve and often outpace the nation’s traditional building practices. In an effort to effectively and proactively incorporate distributed energy resources into the nation’s energy supply, Southface Energy Institute convened with national and regional partners to create the Distributed Energy Resources Education Center (DEREC). Using national model codes and their regionally amended versions as a collective starting point, the DEREC team collaborated with industry experts and identified impediments to effective implementation of DERs, developing discipline-specific curriculum to eliminate those impediments. The center, developed in collaboration with Interstate Renewable Energy Committee (IREC) and National Buildings Institute (NBI), leverages existing DER education content as well as new and dynamic training materials and online courses that collectively engage the many roles necessary for DER implementations, including designers, code officials, builders and skilled trades, and building owners who specify, inspect, build, operate, and maintain buildings with DERs.

14 SOLAR ENERGY↗

Quantitative comparisons of electron-scale turbulence measurements in NSTX via synthetic diagnostics for high-k scattering.

Two synthetic diagnostics are implemented for the high-k scattering system in NSTX [D. R. Smith, E. Mazzucato, W. Lee, H. K. Park, C. W. Domier, and N. C. Luhmann Jr., Rev. Sci. Instrum., 79, 123501 (2008)] allowing direct comparisons between synthetic and experimentally detected frequency and wavenumber spectra of electron-scale turbulence fluctuations. Synthetic diagnostics were formulated in real-space and in wavenumber space, and were deployed to realistic electron-scale simulations carried out with the GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186 (2003) 545]. A highly unstable ETG regime (electron temperature gradient mode) in a modest beta NSTX NBI-heated H-mode discharge was chosen for the analysis. Mapping the measured wavenumbers to field aligned coordinates showed that the high-k system is sensitive to fluctuations that are closer to the spectral peak in the density fluctuation wavenumber spectrum (streamers) than originally predicted. Analysis of synthetic spectra show that the frequency response of the detected fluctuations is dominated by Doppler shift and insensitive to the turbulence drive. The shape of the high-k density fluctuation wavenumber spectrum is sensitive to the ETG turbulence drive conditions, and can be reproduced in a sensitivity scan of the most pertinent turbulent drive terms in the simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A novel measurement of marginal Alfven Eigenmode stability during high power auxiliary heating in JET

The interaction of Alfven Eigenmodes (AEs) and energetic particles is one of many important factors determining the success of future tokamaks. In JET, eight in-vessel antennas were installed to actively probe stable AEs with frequencies ranging 25-250 kHz and toroidal mode numbers |n| < 20. During the 2019-2020 deuterium campaign, almost 7500 resonances and their frequencies f0, net damping rates \gamma < 0, and toroidal mode numbers were measured in almost 800 plasma discharges. From a statistical analysis of this database, continuum and radiative damping are inferred to increase with edge safety factor, edge magnetic shear, and when including non-ideal effects. Both stable AE observations and their associated damping rates are found to decrease with |n|. Active antenna excitation is also found to be ineffective in H-mode as opposed to L-mode; this is likely due to the increased edge density gradient's effect on accessibility and ELM-related noise's impact on mode identification. A novel measurement is reported of a marginally stable, edge-localized Ellipticity-induced AE probed by the antennas during high-power auxiliary heating (ICRH and NBI) up to 25 MW. NOVA-K kinetic-MHD simulations show good agreement with experimental measurements of f0, \gamma, and n, indicating the dominance of continuum and electron Landau damping in this case. Similar experimental and computational studies are planned for the recent hydrogen and ongoing tritium campaigns, in preparation for the upcoming DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of the TCV tokamak program: Scientific progress and facility upgrades

The TCV tokamak is augmenting its unique historical capabilities (strong shaping, strong electron heating) with ion heating, additional electron heating compatible with high densities, and variable divertor geometry, in a multifaceted upgrade program designed to broaden its operational range without sacrificing its fundamental flexibility. The TCV program is rooted in a three-pronged approach aimed at ITER support, explorations towards DEMO, and fundamental research. A 1 MW, tangential neutral beam injector (NBI) was recently installed and promptly extended the TCV parameter range, with record ion temperatures and toroidal rotation velocities and measurable neutral-beam current drive. ITER-relevant scenario development has received particular attention, with strategies aimed at maximizing performance through optimized discharge trajectories to avoid MHD instabilities, such as peeling-ballooning and neoclassical tearing modes. Experiments on exhaust physics have focused particularly on detachment, a necessary step to a DEMO reactor, in a comprehensive set of conventional and advanced divertor concepts. The specific theoretical prediction of an enhanced radiation region between the two X-points in the low-field-side snowflake-minus configuration was experimentally confirmed. Fundamental investigations of the power decay length in the scrape-off layer (SOL) are progressing rapidly, again in widely varying configurations and in both D and He plasmas; in particular, the double decay length in L-mode limited plasmas was found to be replaced by a single length at high SOL resistivity. Experiments on disruption mitigation by massive gas injection and electron-cyclotron resonance heating (ECRH) have begun in earnest, in parallel with studies of runaway electron generation and control, in both stable and disruptive conditions; a quiescent runaway beam carrying the entire electrical current appears to develop in some cases. Developments in plasma control have benefited from progress in individual controller design and have evolved steadily towards controller integration, mostly within an environment supervised by a tokamak profile control simulator. TCV has demonstrated effective wall conditioning with ECRH in He in support of the preparations for JT-60SA operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

3D full wave fast wave modeling with realistic antenna geometry and SOL plasma

This paper reports the significant advancement of our ability to model and to understand how RF waves interact with the SOL plasma, by simulating the full torus 3D SOL plasma together with the antenna and core plasma. We introduce and use a recently developed and open source code, Petra-M, which was constructed on the scalable MFEM C++ finite element library, and performed 3D full wave simulations in the HHFW regime for both NSTX-U and LAPD plasmas. A first full wave simulation for a full 3D torus including a realistic antenna geometry and SOL plasma region for NSTX-U is presented. A scan of the antenna phasing shows a strong interaction between FWs and the SOL plasma for lower antenna phasing, which is consistent with previous NSTX HHFW observations. The effect of the 3D wave field on the fast ion population from NBI beams in NSTX-U is also discussed by using the 3D field obtained from the Petra-M simulations in the full-orbit following particle SPIRAL code. On LAPD, 3D full wave simulations of a new HHFW 4-strap antenna recently installed by TAE Technologies on LAPD are performed showing a qualitative agreement with experimental data.

Bertelli, Nicola↗

Fast ion confinement in the presence of core magnetic islands in Wendelstein 7-X

The effect of magnetic islands in the core region of Wendelstein 7-X (W7-X) on fast ion confinement is explored through simulations with the BEAMS3D code. A magnetic configuration where the n/m = 5/5 island chain is shifted to r/a ~ 0.7 allows the exploration of core island physics in W7-X. The control coil system on W7-X allows the tuning of the island size either increasing the island width or decreasing it. A coupling of the BEAMS3D code to the FIELDLINES code provides a versatile mechanism for incorporating magnetic islands and stochastic regions into the BEAMS3D code. Collisionless simulations suggest that the presence of core islands degrade the confinement of passing particles in the region of the island chain. Full neutral beam simulations of W7-X show a similar behavior with confinement decreasing as the island width is increased. Comparisons between a vacuum magnetic field and low beta HINT2 simulation are made showing similar fast ion behavior. Measurements of lost fast ions in W7-X confirm this trend with the control coil suppressed island configuration showing lower losses than that with no control coils applied. Simulations of fast ion wall loads are performed suggesting no drastic change in loss pattern and a slight reduction in losses with minimized islands.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reversed Field Pinch Research in MST (Final Technical Report)

This is the Final Technical Report for the cooperative agreement DE-FC02-05ER54814 titled “Reversed Field Pinch Research in MST” spanning the funding period 4/1/2005 to 12/14/2019. It summarizes key results from MST research, major publications and presentations, and the mentoring of graduate students and postdocs. The Madison Symmetric Torus (MST) is unique within the U.S. and world fusion plasma program. As one of just five operating reversed field pinch (RFP) experiments, and the only one in the U.S., MST has had an important role in advancing the fundamental understanding of the RFP plasma configuration. The MST research program targets topics that intersect with all three goals. While MST provides a unique opportunity to advance the science and fusion potential of the RFP, as a cousin to the tokamak and stellarator plasma configurations the RFP is a valuable partner in establishing validated predictive capability for fusion science more generally. Specific combinations of the major variables in toroidal confinement, like magnetic field strength, plasma current, and shaping, define the different configurations. By exploring adjacent regions in this major variable parameter space, the RFP exposes dependencies not otherwise accessible in the tokamak and stellarator. This diversity enlarges the arena for scientific discovery, both for fusion and plasma physics. The basic science emphasis for MST research has been the self-organizing behavior of RFP plasmas. This inspired MST’s participation in the NSF Physics Frontier Center for Magnetic Self-Organization in Laboratory and Astrophysical Plasmas (CMSO), which ran from 2004-2016 and motivated a substantial fraction of MST’s research goals and capabilities. By all measures the MST Program has been remarkably successful in publications, community engagement, and mentoring of young scientists. While the DOE-FES’s proof-of-principle program for the RFP now languishes through the cessation of this cooperative agreement, operation of MST continues as one of two devices included in the new Wisconsin Plasma Physics Laboratory (WiPPL) basic science user facility. The scope of present research for MST in WiPPL is narrowed to the basic science associated with the RFP magnetic configuration and the advancement of specific fusion topics, which now includes studies of disruptions in tokamak plasmas. The world’s effort in RFP fusion research continues, despite a lack of U.S. federal support to investigate the RFP configuration for fusion application, most notably through a major upgrade to the RFX-mod2 facility in Italy [1] and the recent construction of the KTX facility at USTC in China. First plasmas for RFX-mod2 are anticipated in 2021.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗