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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and fusion pilot plant may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1986

Plasma Source for Charge Control

Plasma source neutralizes electrical charge on spacecraft. When triggered by command from spacecraft potential monitor or from control system, plasma apparatus responds within about 1 s, generating charged plasma of required polarity. Discharging system to be tested on Air Force Geophysics Laboratory BERT-1 (Beam Emission Rocket Test) sounding rocket.

Aston, G.↗
DOE OSTI2021

DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)

Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas

A theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X.

neoclassical modelling↗
DOE OSTI2022

Design Considerations for Controlling Silicon Nanoparticle Nucleation and Growth in a Nonthermal Plasma

Controlling the nucleation and growth of nanoparticles in low temperature plasma systems is imperative for controlling nanoparticle size distributions; and for some applications such as deposition and etching in microelectronic processing, preventing particle contamination. In this work, silicon nanoparticle (NP) production from silane is used as a model system to investigate the nucleation process. Although the mechanisms responsible for silicon NP nucleation and growth have been studied, it is unclear how controllable system parameters (e.g., pressure, system geometry, and gas composition) can be used to inhibit or promote NP formation. For example, the transport of reactive silane species is expected to significantly affect the feed fraction of silane required to nucleate silicon NP (the nucleation onset fraction) due to losses at the reactor walls. In this work, NP mass density was determined as a function of system pressure, gas composition, and reactor diameter for a tubular flow-through radiofrequency (RF) plasma using Ar/H2/He/SiH4 gas mixtures. A quartz crystal microbalance (QCM) impactor was developed to measure the total aerosol mass density downstream of the plasma and thereby identify the nucleation onset and its dependence on process parameters. Finally, a reaction mechanism was developed and incorporated into a global plasma chemistry model to better understand the nucleation onset and NP growth.

36 MATERIALS SCIENCE↗
NASA NTRS1988

ARC length control for plasma welding

A control system to be used with a plasma arc welding apparatus is disclosed. The plasma arc welding apparatus includes a plasma arc power supply, a contactor, and an electrode assembly for moving the electrode relative to a work piece. The electrode assembly is raised or lowered by a drive motor. The present apparatus includes a plasma arc adapter connected across the power supply to measure the voltage across the plasma arc. The plasma arc adapter forms a dc output signal input to a differential amplifier. A second input is defined by an adjustable resistor connected to a dc voltage supply to permit operator control. The differential amplifier forms an output difference signal provided to an adder circuit. The adder circuit then connects with a power amplifier which forms the driving signal for the motor. In addition, the motor connects to a tachometor which forms a feedback signal delivered to the adder to provide damping, therby avoiding servo loop overshoot.

William F Iceland↗
DOE OSTI2025

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗
DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗
DOE OSTI2022

A method for automated modeling of plasma shape control response in tokamaks

Here, a simple method commonly used in modeling of tokamak conductor and plasma response for plasma control has been extended to allow more general modeling of tokamak PF conductor circuits. This extension combines a previously existing method for integrating plasma response and tokamak circuits with a more capable circuit modeling technique derived from the theory that underlies present-day automatic circuit simulation codes. This combined method can incorporate any combination of inductors (e.g., coils), resistors, capacitors, voltage sources, and current sources, while retaining the same model structure and ease of interpretation as the simple method. For many tokamaks, use of this extended method would not be the preferred approach, but for certain devices or for specialized models of a device, it is useful and occasionally essential. For example, the method has enabled fast and automated modeling of the complicated and daily-changing circuit topology used in the DIII-D tokamak. This automated modeling is essential to the support of controller design for the frequently changing requirements for DIII-D plasmas. It is likely to also find application in the workflows for new device designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Feedback Control of Plasma Instabilities with Charged Particle Beams and Study of Plasma Turbulence

A new non-perturbing technique for feedback control of plasma instabilities has been developed in the Columbia Linear Machine (CLM). The feedback control scheme involves the injection of a feedback modulated ion beam as a remote suppressor. The ion beam was obtained from a compact ion beam source which was developed for this purpose. A Langmuir probe was used as the feedback sensor. The feedback controller consisted of a phase-shifter and amplifiers. This technique was demonstrated by stabilizing various plasma instabilities to the background noise level, like the trapped particle instability, the ExB instability and the ion-temperature-gradient (ITG) driven instability. An important feature of this scheme is that the injected ion beam is non-perturbing to the plasma equilibrium parameters. The robustness of this feedback stabilization scheme was also investigated. The principal result is that the scheme is fairly robust, tolerating about 100% variation about the nominal parameter values. Next, this scheme is extended to the unsolved general problem of controlling multimode plasma instabilities simultaneously with a single sensor-suppressor pair. A single sensor-suppressor pair of feedback probes is desirable to reduce the perturbation caused by the probes. Two plasma instabilities the ExB and the ITG modes, were simultaneously stabilized. A simple 'state' feedback type method was used where more state information was generated from the single sensor Langmuir probe by appropriate signal processing, in this case, by differentiation. This proof-of-principle experiment demonstrated for the first time that by designing a more sophisticated electronic feedback controller, many plasma instabilities may be simultaneously controlled. Simple theoretical models showed generally good agreement with the feedback experimental results. On a parallel research front, a better understanding of the saturated state of a plasma instability was sought partly with the help of feedback. A plasma instability is usually observed in its saturated state and appears as a single feature in the frequency spectrum with a single azimuthal and parallel wavenumbers. The physics of the non-zero spectral width was investigated in detail because the finite spectral width can cause "turbulent" transport. One aspect of the "turbulence" was investigated by obtaining the scaling of the linear growth rate of the instabilities with the fluctuation levels. The linear growth rates were measured with the established gated feedback technique. The research showed that the ExB instability evolves into a quasi-coherent state when the fluctuation level is high. The coherent aspects were studied with a bispectral analysis. Moreover, the single spectral feature was discovered to be actually composed of a few radial harmonics. The radial harmonics play a role in the nonlinear saturation of the instability via three-wave coupling.

Tham, Philip Kin-Wah↗
DOE OSTI2024

Manufacturing porous U-10Zr metallic fuels with controllable microstructure by volume control spark plasma sintering

In this paper, the volume control spark plasma sintering tool has been designed and applied to sinter porous U-10Zr metallic fuels, by which the sintered sample volume can be precisely controlled. Ethanol and NH 4 HCO 3 are used to control the powder compact or as pore formers to control the pore size and pore structure. Without pore formers, the fuel pellet displays an inhomogeneous microstructure consisting of highly porous and highly densified areas. Uneven powder stacking in the green body results in a non-uniform microstructure, and in the closed-packed area, Joule heating accelerates the neck formation and densification. The addition of ethanol reduces the friction between the powders, resulting in isolated pores formed by the stacking of powders during the sintering. By adding NH 4 HCO 3 , the pore size, and structure can be well controlled, and an interconnected pore structure can be obtained upon the decomposition of the NH 4 HCO 3 . Further, a uniform microstructure and pore distributions can be achieved through the U-10Zr fuel pellets by controlling current flow during the volume control SPS sintering. The microstructure and phase characterization of the sintered porous U-10Zr pellets show major phases of α-U and α-Zr for the sample with short dwelling. For the sample with long dwelling (30 min), the ω UZr 2 in the Zr-enriched area has been observed. The strategy of volume control SPS sintering with the assistance of pore formers could be used to fabricate porous U-10Zr metallic fuels to mimic the microstructure evolution of irradiated metallic fuels (including porosity) and could enable a possible solution for the design of new sodium-free metallic fuels for high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Latent space mapping: Revolutionizing predictive models for divertor plasma detachment control

The inherent complexity of boundary plasma, characterized by multi-scale and multi-physics challenges, has historically restricted high-fidelity simulations to scientific research due to their intensive computational demands. Consequently, routine applications such as discharge control and scenario development have relied on faster but less accurate empirical methods. This work introduces DivControlNN, a novel machine-learning-based surrogate model designed to address these limitations by enabling quasi-real-time predictions (i.e., ~ 0.2 ms) of boundary and divertor plasma behavior. Trained on over 70,000 2D UEDGE simulations from KSTAR tokamak equilibria, DivControlNN employs latent space mapping to efficiently represent complex divertor plasma states, achieving a computational speed-up of over 10 8 compared to traditional simulations while maintaining a relative error below 20% for key plasma property predictions. During the 2024 KSTAR experimental campaign, a prototype detachment control system powered by DivControlNN successfully demonstrated detachment control on its first attempt, even for a new tungsten divertor configuration and without any fine-tuning. These results highlight the transformative potential of DivControlNN in overcoming diagnostic challenges in future fusion reactors by providing fast, robust, and reliable predictions for advanced integrated control systems.

Artificial neural networks↗
DOE OSTI2026

Final Technical Report for DoE award DE‐SC0023367 “Energetic Electron Transport in Magnetized Plasma with Magnetic Islands”

This project investigated how plasmas interact with energetic particles and solid materials under extreme conditions relevant to fusion energy, space plasmas, and planetary environments. Using experiments on the DIII-D National Fusion Facility, the research first examined how high-energy electrons move, become trapped, and are released in plasmas containing magnetic islands—structures commonly found in fusion reactors and Earth’s magnetosphere—providing new insight into particle transport and acceleration processes. The project also explored plasma-driven chemical reactions that can occur during meteoroid entry into planetary atmospheres, demonstrating that simple molecules such as ammonia can be produced and survive in high-temperature plasma conditions. Together, these results improve understanding of plasma behavior across laboratory, space, and planetary systems while informing fusion plasma control and plasma–material interaction studies. The project additionally contributed to workforce development by training graduate students, undergraduates, and early-career researchers and by disseminating results through peer-reviewed publications and international scientific conferences.

Orlov, Dmitri Mikhailovich [UC San Diego] (ORCID:0↗
DOE OSTI2022

Plasma-Catalyst Reactivity Control of Surface Nitrogen Species through Plasma-Temperature-Programmed Hydrogenation to Ammonia

Nonthermal plasma activation of N 2 can facilitate nitrogen adsorption on metal catalysts at low bulk temperatures and atmospheric pressure. Here, we apply a plasma-assisted temperature-programmed reaction (plasma-TPRxn) for ammonia (NH 3 ) synthesis using sequential exposure of a silica-supported metal catalyst to N 2 plasma followed by thermal hydrogen treatment while ramping the temperature to decouple the plasma activation of N 2 from surface catalyzed hydrogenation steps. This approach eliminates the effects from bulk plasma phase reactions, thereby allowing for direct interrogation of plasma activated nitrogen on the active metal surfaces. We confirm previously reported spectroscopic observations that show plasma-generated surface nitrogen can be converted to NH 3 through surface catalyzed pathways. Further, we demonstrate that the ammonia desorption peak temperature is sensitive to metal, with Pt desorbing NH 3 at the lowest temperature. Unsteady state microkinetic models of desorption kinetics as a function of initial N coverage and metal recover observed trends in NH 3 desorption temperatures and confirm that observed results reflect hydrogenation of plasma-induced N accommodation at each surface. In total, we show that the hydrogenation ability of the catalyst after plasma activation of N 2 is responsible for the reactivity trends observed in plasma-assisted NH 3 synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Data-driven model for divertor plasma detachment prediction

We present a fast and accurate data-driven surrogate model for divertor plasma detachment prediction leveraging the latent feature space concept in machine learning research. Our approach involves constructing and training two neural networks: an autoencoder that finds a proper latent space representation (LSR) of plasma state by compressing the multi-modal diagnostic measurements and a forward model using multi-layer perception (MLP) that projects a set of plasma control parameters to its corresponding LSR. By combining the forward model and the decoder network from autoencoder, this new data-driven surrogate model is able to predict a consistent set of diagnostic measurements based on a few plasma control parameters. In order to ensure that the crucial detachment physics is correctly captured, highly efficient 1D UEDGE model is used to generate training and validation data in this study. The benchmark between the data-driven surrogate model and UEDGE simulations shows that our surrogate model is capable of providing accurate detachment prediction (usually within a few per cent relative error margin) but with at least four orders of magnitude speed-up, indicating that performance-wise, it has the potential to facilitate integrated tokamak design and plasma control. Comparing with the widely used two-point model and/or two-point model formatting, the new data-driven model features additional detachment front prediction and can be easily extended to incorporate richer physics. This study demonstrates that the complicated divertor and scrape-off-layer plasma state has a low-dimensional representation in latent space. Understanding plasma dynamics in latent space and utilising this knowledge could open a new path for plasma control in magnetic fusion energy research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1981

Parameters and controlling of plasma chemistry

The parameters involved in plasma polymerization reactions are examined and the use of these parameters in the control of plasma reactions is dicussed. The variables associated with the reaction chamber, electrical discharge form, frequency and electrical source for the development of plasma, and monitoring techniques are addressed.

Tsuji, O.↗
DOE OSTI2025

Framework for assessment of magnetic equilibrium controller performance on the MAST upgrade spherical tokamak

Here, in this work we present the assessment framework for magnetic equilibrium controllers on MAST Upgrade spherical tokamak (MAST-U) spherical tokamak. Such controllers are essential for the MAST-U since exhaust physics and core-edge integration studies require advanced divertor plasma configurations. The developed framework is based on the TokSys suite of plasma control codes, which was adapted and upgraded for MAST-U. However, extra capabilities were added on top of TokSys to support the development of new control algorithms, deployment of controllers to the plasma control system (PCS) and evaluation of their performance. The controller assessment was realized via closed-loop integrated control simulations with the actual MAST-U PCS and different physics-based plasma models. Since all components of the assessment chain were experimentally validated, these simulations provide qualified controllers applicable for direct use in the experiment. This resulted in the successful experimental demonstration of advanced plasma shape control on MAST-U with minimal on-machine development time. A similar methodology would be beneficial to other tokamaks, both existing and future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗