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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Automated ICRF heating surrogate modeling via machine learning

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 R 2 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.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗
DOE OSTI2024

Effects of Plume Targeted Cooling on Residual Stress in Controlled Atmosphere Plasma Sprayed Coatings

Thermal spray processes can benefit from cooling to maintain substrate temper, reduce processing times, and manage thermally induced residual stresses. “Plume quenching” is a plume-targeted cooling technique which has been shown to reduce substrate temperatures by redirection of hot plume gases using a lateral argon curtain injected into the plume, while limiting interaction with the substrate or affecting coating properties. Here, this study explores the use of this technique for residual stress management by reducing the thermally driven component in nickel and tantalum coatings on titanium and aluminum substrates. The in-situ residual stress profiles were measured for all substrate and coating pairings during spraying and cooling, and the deposition and thermal stresses recorded. For substrate and coating pairings where the predominant component of residual stress was thermal (driven by a large difference in coefficient of thermal expansion, Δα, between coating and substrate), plume quenching reduced both the thermal stress and the final stress state of the coating. This was seen primarily in tantalum on aluminum coatings where the Δα was -17 × 10 -6 /°C, and thermal stress was reduced by 7.5% and 22.4% for the plume quenching rates of 50 and 100 slpm, respectively.

42 ENGINEERING↗
NASA NTRS1989

Method and apparatus for maintaining thermal control in plasma conditions

An apparatus and method are disclosed for determining the effects of exposure of oxygen plasma on a thin film polymer whose bulk is maintained at a predetermined temperature. The apparatus includes a chamber having a specimen therein. A plasma environment is provided in the chamber. A closure member is provided for sealing the chamber after the specimen is introduced into the chamber. The closure member also serves as a support for the test apparatus which includes a cooling coil. A platform having the test specimen thereon is supported on the cooling coil to be cooled by coolant flowing through the cooling coils. A thermoelectric module is supported on the platform to assist in maintaining a low test temperature for the test samples. The temperature of the sample is monitored by a thermocouple probe which is in contact with the sample. Any change in bulk sample temperature caused by the thermocouple probe is quickly adjusted to maintain the initial bulk temperature by the thermoelectric module.

Whitaker, Ann F.↗
NASA NTRS2001

The Importance of Optical Pathlength Control for Plasma Absorption Measurements

An inductively coupled GEC Cell with modified viewing ports has been used to measure in-situ absorption in CF4 plasmas via Fourier Transform Infrared Spectroscopy, and the results compared to those obtained in a standard viewport configuration. The viewing ports were modified so that the window boundary is inside, rather than outside, of the GEC cell. Because the absorption obtained is a spatially integrated absorption, measurements made represent an averaging of absorbing species inside and outside of the plasma. This modification is made to reduce this spatial averaging and thus allow a more accurate estimation of neutral species concentrations and temperatures within the plasmas. By reducing this pathlength, we find that the apparent CF4 consumption increases from 65% to 95% and the apparent vibrational temperature of CF4 rises by 50-75 K. The apparent fraction of etch product SiF4 decreases from 4% to 2%. The data suggests that these density changes may be due to significant temperature gradients between the plasma and chamber viewports.

Cruden, Brett A.↗
NASA NTRS2005

Numerical Simulations of Plasma Based Flow Control Applications

A mathematical model was developed to simulate flow control applications using plasma actuators. The effects of the plasma actuators on the external flow are incorporated into Navier Stokes computations as a body force vector. In order to compute this body force vector, the model solves two additional equations: one for the electric field due to the applied AC voltage at the electrodes and the other for the charge density representing the ionized air. The model is calibrated against an experiment having plasma-driven flow in a quiescent environment and is then applied to simulate a low pressure turbine flow with large flow separation. The effects of the plasma actuator on control of flow separation are demonstrated numerically.

Suzen, Y. B.↗
NASA NTRS2017

The Mars Crustal Magnetic Field Control of Plasma Boundary Locations and Atmospheric Loss: MHD Prediction and Comparison with MAVEN

We present results from a global Mars time-dependent MHD simulation under constant solar wind and solar radiation impact considering inherent magnetic field variations due to continuous planetary rotation. We calculate the 3-D shapes and locations of the bow shock (BS) and the induced magnetospheric boundary (IMB) and then examine their dynamic changes with time. We develop a physics-based, empirical algorithm to effectively summarize the multidimensional crustal field distribution. It is found that by organizing the model results using this new approach, the Mars crustal field shows a clear, significant influence on both the IMB and the BS. Specifically, quantitative relationships have been established between the field distribution and the mean boundary distances and the cross-section areas in the terminator plane for both of the boundaries. The model-predicted relationships are further verified by the observations from the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. Our analysis shows that the boundaries are collectively affected by the global crustal field distribution, which, however, cannot be simply parameterized by a local parameter like the widely used subsolar longitude. Our calculations show that the variability of the intrinsic crustal field distribution in Mars-centered Solar Orbital itself may account for approx.60% of the variation in total atmospheric loss, when external drivers are static. It is found that the crustal field has not only a shielding effect for atmospheric loss but also an escape-fostering effect by positively affecting the transterminator ion flow cross-section area.

Global↗
DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2001

Design of the EO-1 Pulsed Plasma Thruster Attitude Control Experiment

The Pulsed Plasma Thruster (PPT) Experiment on the Earth Observing 1 (EO-1) spacecraft has been designed to demonstrate the capability of a new generation PPT to perform spacecraft attitude control. The PPT is a small, self-contained pulsed electromagnetic Propulsion system capable of delivering high specific impulse (900-1200 s), very small impulse bits (10-1000 micro N-s) at low average power (less than 1 to 100 W). EO-1 has a single PPT that can produce torque in either the positive or negative pitch direction. For the PPT in-flight experiment, the pitch reaction wheel will be replaced by the PPT during nominal EO-1 nadir pointing. A PPT specific proportional-integral-derivative (PID) control algorithm was developed for the experiment. High fidelity simulations of the spacecraft attitude control capability using the PPT were conducted. The simulations, which showed PPT control performance within acceptable mission limits, will be used as the benchmark for on-orbit performance. The flight validation will demonstrate the ability of the PPT to provide precision pointing resolution. response and stability as an attitude control actuator.

Zakrzwski, Charles↗
NASA NTRS1996

Pulsed plasma thrusters for small spacecraft attitude control

Pulsed Plasma Thrusters (PPTS) are a new option for attitude control of a small spacecraft and may result in reduced attitude control system (ACS) mass and cost. The primary purpose of an ACS is to orient the spacecraft to the desired accuracy in inertial space. The ACS functions for which the PPT system will be analyzed include disturbance torque compensation, and slewing maneuvers such as sun acquisition for which the small impulse bit and high specific impulse of the PPT offers unique advantages. The NASA Lewis Research Center (LERC) currently has a contracted flight PPT system development program in place with Olin Aerospace with a delivery date of October 1997. The PPT systems in this study are based upon the work being done under the NASA LERC program. Analysis of the use of PPTs for ACS showed that the replacement of the standard momentum wheels and torque rods with a PPT system to perform the attitude control maneuvers on a small low Earth orbiting spacecraft reduced the ACS mass by 50 to 75% with no increase in required power level over comparable wheel-based systems, though rapid slewing power requirements may present an issue.

McGuire, Melissa L.↗
NASA NTRS1996

Pulsed Plasma Thrusters for Small Spacecraft Attitude Control

Pulsed plasma thrusters (PPT's) are a new option for attitude control of a small spacecraft and may result in reduced attitude control system (ACS) mass and cost. The primary purpose of an ACS is to orient the spacecraft configuration to the desired accuracy in inertial space. The ACS functions for which the PPT system will be analyzed include disturbance torque compensation and slewing maneuvers such as sun acquisition for which the small impulse bit and high specific impulse of the PPT offers unique advantages. The NASA Lewis Reserach Center (LeRC) currently has a contracted flight PPT system development program in place with Olin Aerospace and a delivery date of October 1997. The PPT system in this study are based upon the work being done under the NASA LeRC program. Analysis of the use of PPT's for ACS showed that the replacement of the standard momentum wheels and torque rods systems with a PTT system to perform the altitude control maneuvers on a small low Earth orbiting spacecraft reduced the ACS mass by 50 to 75 percent with no increase in required power level over comparable wheel-based systems.

McGuire, Melissa L.↗
DOE OSTI2025

Prediction of electric and magnetic fields from spectral data using machine learning algorithms for Doppler-free saturation spectroscopy diagnostics

The prediction of electric and magnetic field amplitudes from atomic spectral data is critical for plasma control in fusion devices such as tokamaks. Conventional approaches that rely on physics-based models are computationally expensive and unsuitable for real-time applications. In this work, we develop and benchmark three machine learning algorithms—simulation-based inference (SBI), fully connected neural networks (FCNN), and histogram-based gradient boosting regression (GBR-Hist)—to infer field intensities directly from Doppler-free saturation spectroscopy (DFSS) spectra. Synthetic datasets of spectra were generated using the EZSSS code and evaluated both with and without added Poisson noise to mimic experimental conditions. We find that SBI achieves the highest accuracy and robustness, FCNN provides a strong balance of accuracy and computational efficiency for real-time applications, and GBR-Hist offers the fastest inference but is more sensitive to noise. Furthermore, these results demonstrate the potential of machine learning to accelerate DFSS analysis and enhance its utility for plasma diagnostics and control.

Doppler-free saturation spectroscopy↗
DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1971

Postulation of the arc restrike mechanisms for exploding wires and tubes.

The many facets of exploding wire restrikes are studied. They are related to the cylindrical shock wave which pumps down the density of the center region of a line energy source or around the surface of the heated wire continuously to a lower density. When the density of any region is pumped down to lower than Paschen's electric breakdown criteria, restrike occurs. The cylindrical shocks occurring in exploding wires are, in general, divided into two types. In the first type the shock is generated by the wire explosion and in the second type the shock is generated by the heat conduction of the wire to the surrounding gas. Application of this mechanism to exploding tubes will enable us to create arc channels in arbitrary gaseous atmospheres with controllable plasma density with the contamination excluded. Neutral density shielded plasma experiments, therefore, can be conducted in a controllable environment.

Cheng, D. Y.↗