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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 721 records · Page 40

System Modeling of a Lunar Molten Regolith Electrolysis Plant

In-Situ Resource Utilization (ISRU) is the process of extracting local resources to produce commodities for propulsion, life support systems, and off-planet construction rather than transporting consumables from Earth. Molten Regolith Electrolysis (MRE) is a novel ISRU method of extracting oxygen gas and metal alloy from lunar regolith. The MRE process involves placing lunar regolith between two electrodes, through which current is passed, to melt the regolith and reduce the metal oxide constituents by direct electrolysis (e.g. FeO, SiO 2 , MgO, Al 2 O 3 ) into oxygen gas and metal alloys. The oxygen is liquefied and used as propellant for landers, while the metals (e.g. Ferro-alloys) are further processed and used in structural building materials and parts manufacturing. A system model was developed that accounted for the major processes of an MRE plant (from excavation of raw materials to storage of products) to assess the feasibility of a lunar MRE plant. The S ystem Engineering and Integration ( S E&I) I SRU M odeling and A nalysis (SIMA) team utilized its previously documented system sizing model, the Mission Analysis and Integration Tool (MAIT) as framework of the system model. MAIT uses MATLAB/Simulink to integrate subsystem models into a complete system model of the MRE plant. Total mass, volume, and power requirements were computed for numerous iterations of a MRE plant.

In-Situ Resource Utilization↗

Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems

This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗

Protection System Validation Using Post-Event Anomaly Classification with Machine Learning

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Protection System Validation with Machine Learning Anomaly Classification

A poster for the Early Career Poster Session. Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Dynamic modeling of brushless dc motor-power conditioner unit for electromechanical actuator application

A comprehensive digital model for the analysis of the dynamic-instantaneous performance of a power conditioner fed samarium-cobalt permanent magnet brushless DC motor is presented. The particular power conditioner-machine system at hand, for which this model was developed, is a component of an actual prototype electromechanical actuator built for NASA-JSC as a possible alternative to hydraulic actuators as part of feasibility studies for the shuttle orbiter applications. Excellent correlation between digital simulated and experimentally obtained performance data was achieved for this specific prototype. This is reported on in this paper. Details of one component of the model, its applications and the corresponding results are given in this paper.

Demerdash, N. A.↗

Post-Event Fault Identification with Machine Learning for Protection System Validation

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by accidental improper relay settings or deliberate malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that their performance falls within expectations. Relays that fail to isolate a fault or trip when there is no system disturbance can be flagged for settings review in situations where this behavior may not have been noticed due to manual restoration or backup protection operations. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by identifying fault events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

ASEAN Technical Exchange Workshop for System Operators, Regulators, and Policymakers

This presentation provides an in-depth exploration of power system planning, cross-border electricity trading, and battery energy storage systems (BESS), offering actionable insights for system operators, regulators, and policymakers. The first section delves into power system planning and analysis, focusing on capacity expansion models and resource adequacy studies, including their role in optimizing system efficiency, managing emissions, and addressing system reliability risks. Key considerations, such as integration of transmission into generation planning and the forecasting versus optimization of customer distributed energy resources (DER) technologies, are explored. The session highlights critical trade-offs in spatial granularity and model runtimes, as well as the feasibility of aligning distribution investments with capacity expansion efforts. The second section examines cross-border electricity trading, with an emphasis on resource adequacy concepts such as reliability targets, loss of load expectation (LOLE), and planning reserve margins (PRM). Case studies on reserve market design and coordination across US regions provide insights into improving reserve deliverability and managing interregional power balance and congestion. This section also addresses market-to-market congestion management, including advanced strategies for high-voltage direct current (HVDC) optimization and ancillary service delivery. Finally, the presentation covers the rapid evolution of Battery Energy Storage Systems (BESS), highlighting their operational growth, regulatory frameworks, and use cases in grid flexibility, energy storage, and reliability. The discussion focuses on the benefits of BESS for system stability, resilience, and integration of renewable energy, offering insights into its role as a vital component in the transition toward a more sustainable and flexible grid. Key performance parameters, such as throughput, round-trip efficiency, and state of charge, are also examined.

25 ENERGY STORAGE↗

The Dripping Handrail Model: Transient Chaos in Accretion Systems

We define and study a simple dynamical model for accretion systems, the "dripping handrail" (DHR). The time evolution of this spatially extended system is a mixture of periodic and apparently random (but actually deterministic) behavior. The nature of this mixture depends on the values of its physical parameters - the accretion rate, diffusion coefficient, and density threshold. The aperiodic component is a special kind of deterministic chaos called transient chaos. The model can simultaneously exhibit both the quasiperiodic oscillations (QPO) and very low frequency noise (VLFN) that characterize the power spectra of fluctuations of several classes of accretion systems in astronomy. For this reason, our model may be relevant to many such astrophysical systems, including binary stars with accretion onto a compact object - white dwarf, neutron star, or black hole - as well as active galactic nuclei. We describe the systematics of the DHR's temporal behavior, by exploring its physical parameter space using several diagnostics: power spectra, wavelet "scalegrams," and Lyapunov exponents. In addition, we note that for large accretion rates the DHR has periodic modes; the effective pulse shapes for these modes - evaluated by folding the time series at the known period - bear a resemblance to the similarly- determined shapes for some x-ray pulsars. The pulsing observed in some of these systems may be such periodic-mode accretion, and not due to pure rotation as in the standard pulsar model.

Young, Karl↗

Application of digital computer APU modeling techniques to control system design.

Study of the required controls for a H2-O2 auxiliary power unit (APU) technology program for the Space Shuttle. A steady-state system digital computer program was prepared and used to optimize initial system design. Analytical models of each system component were included. The program was used to solve a nineteen-dimensional problem, and then time-dependent differential equations were added to the computer program to simulate transient APU system and control. Some system parameters were considered quasi-steady-state, and others were treated as differential variables. The dynamic control analysis proceeded from initial ideal control modeling (which considered one control function and assumed the others to be ideal), stepwise through the system (adding control functions), until all of the control functions and their interactions were considered. In this way, the adequacy of the final control design over the required wide range of APU operating conditions was established.

Bailey, D. A.↗

Speed Variation Based Power Regulation Concept for Dynamic Wireless Charging

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. Here, this paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by 20% and increased by 30% respectively. An 85kHz power electronics model is developed based on designs and prototypes for an 11kW, 190m airgap static system and a 200kW dynamic wireless track. The simulation is validated in the 11kW experimental prototype and modified for 200kW operation to compare with simulated performance. Sensitivity studies are performed in MATLAB/Simulink to evaluate how parameters influence system performance and confirm the capability to reduce output power and maintain efficiency at 11 and 200kW. The static 11kW experimental system operates at 93.6% efficiency and multiple options exist to reduce power while maintaining efficiency greater than 90%. The capability to dynamically modify power output from WPT coils, in an experimentally validated simulation, enables techniques to significantly mitigate load variability due to reductions in vehicle speed.

42 ENGINEERING↗

Radiation induced non-linear oscillations in ITER baseline scenario plasmas in DIII-D

Abstract This work shows how the radiation brought about by metals or metal-equivalent radiators such as Kr and Xe produces non-linear dynamics on otherwise stationary β N flattops of DIII-D ITER Baseline Scenario demonstration discharges. The Kr and Xe gases are used to reproduce the radiative loss rates of W in present machines that operate at core temperatures much lower than the expected ITER temperature. Experiments on DIII-D with injection of Kr and Xe, as well as with sources of intrinsic metals reach the range of radiated fraction values expected in the ITER core and experience slow oscillations in temperature and radiated power. In many cases of high radiated fraction, the core temperature decreases enough for the safety factor profile to rise above the 1/1 rational surface, naturally eliminating sawteeth and occasionally producing a persistent helical core. The oscillations can be reproduced by a modified Lotka–Volterra system for temperature and radiated fraction if diffusion and noise are included, which indicates that the interplay between temperature and radiation can be the main cause of the cyclic nature of the system. A new physics based model which includes equations for temperature, density and input power can also reproduce the oscillations observed in the experiments. The present results suggest that the non-linearity of the system can be increased by the inclusion of the inherently non-linear alpha heating term, which is proportional to ∼ n e 2 T i 2 , and obtains oscillations in the model when added to an otherwise more stationary system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A computer model of solar panel-plasma interactions

High power solar arrays for satellite power systems are presently being planned with dimensions of kilometers, and with tens of kilovolts distributed over their surface. Such systems face many plasma interaction problems, such as power leakage to the plasma, particle focusing, and anomalous arcing. These effects cannot be adequately modeled without detailed knowledge of the plasma sheath structure and space charge effects. Laboratory studies of 1 by 10 meter solar array in a simulated low Earth orbit plasma are discussed. The plasma screening process is discussed, program theory is outlined, and a series of calibration models is presented. These models are designed to demonstrate that PANEL is capable of accurate self consistant space charge calculations. Such models include PANEL predictions for the Child-Langmuir diode problem.

Cooke, D. L.↗

Biconjugate Impedance Matching Control of the HERO WEC: Preprint

Effective control strategies are essential for maximizing the power output of wave energy converters (WECs). In this study, we explore the methodology of port-based modelling which can be used for bi-conjugate impedance matching, a type of reactive control that involves maximizing power transfer by setting the load (PTO) impedance to be the complex conjugate of the source impedance (WEC). Despite its foundational role in electrical engineering, this method has seen limited application in wave energy and has not yet been demonstrated in wave-powered desalination systems. We represent our complex multidisciplinary system as an equivalent circuit to explore frequency-based relations. The HERO WEC, a small-scale, modular point absorber (PA) designed for reverse osmosis desalination is used as a case study to demonstrate port-based modelling for control applications. Improving the performance of wave-powered water desalination systems could play a critical role in addressing freshwater scarcity for coastal communities, especially those in remote or disaster-prone regions.

16 TIDAL AND WAVE POWER↗

Camera Setup for Unsteady Pressure Sensitive Paint at NASA Ames Research Center

The unsteady Pressure-Sensitive Paint Development Team at NASA Ames Research Center is conducting a Launch Vehicle Demo Test in the Unitary Plan Wind Tunnel’s 11-ft Transonic Wind Tunnel in the first half of 2024 to showcase improvements made to unsteady Pressure-Sensitive Paint technology. The unsteady Pressure-Sensitive Paint setup has upgraded from a four-camera system to an eight-camera system, prompting analysis to maximize the system performance and overall data quality. Additional analysis was performed to maximize the system resolving power when subject to test constraints such as model size and model tunnel positions. These analyses have uncovered new opportunities to improve the unsteady Pressure-Sensitive Paint technology and will allow the system to collect higher quality data with simple changes to the setup procedure.

Camera Calibration↗

Evaluating advanced nuclear fission technologies for future decarbonized power grids

Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors would be compared to other technologies, or about which aspects of their designs offer the most value to a decarbonized power grid. We employ an electricity system optimization model and a case study of a decarbonized U.S. Eastern Interconnection circa 2050 to generate initial indicators of future economic value for advanced reactors and the sensitivity of future value to various design parameters, the availability of competing technologies, and the underlying policy environment. These results can inform long-term cost targets and guide near-term innovation priorities, investments, and reactor design decisions. We find that advanced reactors should cost $\$5.7$–$\$7.3$/W to gain an initial market share (assuming 30 year asset life and 3.5 %–6.5 % real weighted average cost of capital), while those that include thermal storage in their designs can cost up to $\$6.0$/W–$\$7.7$/W (not including cost of storage). Since the marginal value of advanced fission reactors declines as market penetration increases, break-even costs fall ~32 % at 100 GW of cumulative capacity and ~51 % at 300 GW. Additionally, policies that provide investment tax credits for nuclear energy create the most favorable environment for advanced nuclear fission. In conclusion, these findings can inform near-term resource allocation decisions by stakeholders, innovators and investors working in the energy technology sector.

Capacity expansion↗

POWER DATA PIPELINE

SF-25-081 Utility software for creating high-performance data pipelines to extract, load, and transform raw electric power systems measurements. For use with anomaly detection models training workflows. The software supports the project: Adaptive Cybersecurity for DER: A Game-Theoretic and Machine Learning approach for Real-Time Threat Detection and Mitigation

Plathottam, Silby Jose [Argonne National Laborator↗

Electrode Erosion and Prefire Studies Towards Fusion Scale Pulsed Power

This study presents a comprehensive investigation of electrode erosion and discharge behavior in spark gap switches over long switching cycle lifetimes. Brass, copper–tungsten (CuW), and stainless steel electrodes are tested under controlled conditions to quantify material degradation, debris accumulation, and changes in breakdown voltage. High-resolution imaging and statistical analysis of spark channel locations and gap breakdown voltages reveal how surface evolution influences long-term performance and reliability. These results provide essential data for lifetime modeling and inform design strategies for pulsed power systems in emerging applications such as private sector fusion energy and large-scale facilities like Sandia’s Z Machine and proposed ZX upgrades, where high repetition reliability and predictable behavior are critical.

electrical breakdown↗