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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nano-Engineered Interfaces in Dual-Layer Electrodes for Protonic Ceramic Cells with Enhanced Stability and Kinetics

Enhancing interfacial stability and charge transfer in protonic ceramic cells (PCCs) remains a critical challenge, as structural degradation and interfacial resistance often compromise durability and efficiency. Here, we report a nanoengineered dual-layer oxygen electrode architecture designed to address these limitations by introducing a fine-grained nanoparticle interfacial contact layer beneath a porous catalytic backbone. The nanoscale powders, through enhanced sintering activity, densify into a robust interfacial layer that promotes strong chemical bonding, uniform adhesion, and continuous ionic/electronic pathways with the BCZYYb electrolyte. This hierarchical architecture mitigates delamination, redistributes mechanical stress, and establishes efficient charge and mass transport channels without relying on corrosive surface treatments. Electrochemical evaluation demonstrates that the dual-layer design markedly reduces interfacial polarization resistance and accelerates electrode kinetics. Compared to the single-layer counterpart, the architecture achieves a peel strength of 44.53 N/cm 2 , a 40% improvement in peak power density (0.96 W cm –2 at 600 °C), and a 130% enhancement in electrolysis current density (4.78 A cm –2 at 1.57 V). Faradaic efficiency remains as high as 88% under high steam concentrations, underscoring minimal charge loss during practical operation. Notably, the electrode retains stability across 450–600 °C and under transient voltage cycling, with impedance spectra confirming suppressed interfacial resistance growth over prolonged use. These results highlight nanoscale interface engineering as a powerful route to enhance both mechanical robustness and electrochemical kinetics in PCCs. The demonstrated scalability and durability of this architecture provide a versatile platform for advancing solid-state electrochemical systems, including reversible fuel cells and high-efficiency hydrogen production technologies.

Faradaic efficiency↗
DOE OSTI2022

A Lyapunov-Based Generalized Dc-Side Controller Design for PV-Connected Systems

The objective of this paper is to realize a universal dc-side controller for photovoltaic (PV) systems where the control is agnostic to the downstream converter configuration. To achieve this, the downstream power converter and its controls are manipulated into an effective power control loop that is then cast into a generalized multi-loop design framework. On the dc side, a nonlinear small-signal model of the PV input is realized exclusively in terms of PV datasheet parameters (i.e., open-circuit voltage, short-circuit current, and maximum power point). Finally, a linear controller is used to modulate the dc-side PV system with the generic downstream power controller. A Lyapunov candidate is proposed to analyze the stability of the interconnected system and provide a streamlined approach for the controller design. The proposed design is validated on a 1k VA experimental setup that interfaces a PV module to the grid.

generalized PV controller↗
NASA NTRS2009

Thermal Design and Analysis of a Multi-Stage 30K Radiative Cooling System for EPIC

The Experimental Probe of Inflationary Cosmology (EPIC) is an implementation of the NASA Einstein Inflation Probe mission, to answer questions about the physics of Inflation in the early Universe by measuring the polarization of the Cosmic Microwave Background (CMB). The mission relies on a passive cooling system to cool the enclosure of a telescope to 30 K; a cryocooler then cools this enclosure to 18 K and the telescope to 4 K. Subsequently, an adiabatic demagnetization refrigerator further cools a large focal plane to approx.100 mK. For this mission, the telescope has an aperture of 1.4 m, and the spacecraft's symmetry axis is oriented approx. 45 degrees relative to the direction of the sun. The spacecraft will be spun at approx. 0.5 rpm around this axis, which then precesses on the sky at 1 rph. The passive system must both supply the necessary cooling power for the cryocooler and meet demanding temperature stability requirements. We describe the thermal design of a passive cooling system consisting of four V-groove radiators for shielding of solar radiation and cooling the telescope to 30 K. The design realizes loads of 20 and 68 mW at the 4 K and 18 K stages on the cooler, respectively. A lower cost option for reaching 40 K with three V-groove radiators is also described. The analysis includes radiation coupling between stages of the radiators and sunshields, and parasitic conduction in the bipod support, harnesses, and ADR leads. Dynamic effects are also estimated, including the very small variations in temperature due to the scan motion of the spacecraft.

Space↗
NASA NTRS1973

V/STOL tilt rotor aircraft study: Wind tunnel tests of a full scale hingeless prop/rotor designed for the Boeing Model 222 tilt rotor aircraft

The rotor system designed for the Boeing Model 222 tilt rotor aircraft is a soft-in-plane hingeless rotor design, 26 feet in diameter. This rotor has completed two test programs in the NASA Ames 40' X 80' wind tunnel. The first test was a windmilling rotor test on two dynamic wing test stands. The rotor was tested up to an advance ratio equivalence of 400 knots. The second test used the NASA powered propeller test rig and data were obtained in hover, transition and low speed cruise flight. Test data were obtained in the areas of wing-rotor dynamics, rotor loads, stability and control, feedback controls, and performance to meet the test objectives. These data are presented.

Magee, J. P.↗
DOE OSTI2025

Advanced Computational Modeling of High-Level Waste Vitrification at the Hanford Site

The U.S. Department of Energy (DOE) has selected vitrification for stabilizing legacy tank waste at the Hanford site, where radioactive waste from plutonium production was historically stored in underground tanks. This waste will be separated into low-activity waste (LAW) and high-level waste (HLW) fractions and processed at the Waste Treatment and Immobilization Plant (WTP). At WTP, glass melters are used for the vitrification of radioactive tank waste, transforming it into a stable borosilicate glass form for safe long-term storage. The melter vessel is constructed from highly durable and heat-resistant materials, where the vitrification process occurs. The main regions that are modeled are the melt pool, plenum, cold cap, riser/discharge chamber, and surrounding structure with insulation layers. Forced convection induced by air bubblers at the base of the melter ensure uniform temperature distribution and provide heat to the cold cap layer. The cold cap is a region of reacting batch feed that floats on top of the molten glass and is where the batch-to-glass reactions occur. Joule heating provided by electrodes mounted along the vertical walls of the melter and immersed directly in the glass, generates the necessary heat for the net endothermic conversion processes that occur in the cold cap. The high temperatures, radioactivity, and opaque nature of the glass prevent direct observation inside the melters. Therefore, computational models are essential for providing insight into factors that affect melter throughput. Thermocouples in the plenum provide operators with plenum temperature measurements. Operational adjustments include bubbling rate, voltage supplied to the electrodes, feed adjustments, and glass removal rate. Different computational fluid dynamics (CFD) models have been developed, each serving a specific purpose. There are CFD models of different scale melters, as well as models that capture the two-phase flow interfaces of rising bubbles in the molten glass or models with a simplified molten glass region so that the surrounding structure and plenum can be feasibly incorporated. Pilot-scale melter models have been developed to serve as validation of the methods employed in the simulation of the full-scale WTP melters. Models incorporating resolved bubbling are used to develop momentum source terms to implement into a single phase, multi-region, steady-state flow model that is being validated by measured process parameters such as glass production rate, voltage, input power, plenum temperatures, etc. The resolved bubbling model uses the multiphase volume of fluid approach to model the system with a high-resolution interface capturing scheme to maintain sharp interfaces between the molten glass and the air phase. The suite of CFD models is continually being improved to incorporate more realistic physics and achieve faster turnaround time. For example, an incremental controller is implemented to automatically adjust electrode voltage within the simulation to a molten glass set point temperature of 1150°C. Newer models feature improved meshes to ensure conformal meshes between regions and eliminate unnecessary mesh refinement in areas that are not of interest (such as boundary layers in offgas ports). Instead of explicitly modeling the structural, refractory, and insulation layers of the melter, a thermal resistance approach is used with published correlations used for boundary conditions. The development of robust and efficient CFD models will be instrumental in enabling the WTP to successfully fulfill its mission of safely stabilizing legacy nuclear waste.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2023

Characterizing different motility-induced regimes in active matter with machine learning and noise

Here we examine motility-induced phase separation (MIPS) in two-dimensional run-and-tumble disk systems using both machine learning and noise fluctuation analysis. Our measures suggest that within the MIPS state there are several distinct regimes as a function of density and run time, so that systems with MIPS transitions exhibit an active fluid, an active crystal, and a critical regime. The different regimes can be detected by combining an order parameter extracted from principal component analysis with a cluster stability measurement. The principal component-derived order parameter is maximized in the critical regime, remains low in the active fluid, and has an intermediate value in the active crystal regime. We demonstrate that machine learning can better capture dynamical properties of the MIPS regimes compared to more standard structural measures such as the maximum cluster size. The different regimes can also be characterized via changes in the noise power of the fluctuations in the average speed. In the critical regime, the noise power passes through a maximum and has a broad spectrum with a 1/f 1.6 signature, similar to the noise observed near depinning transitions or for solids undergoing plastic deformation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗
DOE OSTI2024

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2024

Performance Evaluation of Multi-Vendor Grid-Forming Inverters for Grid-Connected Operation Through Hardware Experimentation: Preprint

Existing real-world projects of GFM inverters that operate in parallel to power grids typically are sized between dozens and a few hundreds Megawatt (MW) scale according to a recent NERC GFM inverter white paper. These large systems are often difficult to evaluate prior to deployments because of their large size. The performance of smaller GFM inverters (dozens to a few hundreds MW) that operate parallel with power grids (distribution systems) is even less understood. There is an opportunity to better understand these systems through hardware testing under controlled laboratory conditions. Therefore, this paper presents the functional performance evaluation tests of multiple (three) commercial GFM inverters when they operate in parallel with the grid through hardware experiments. The goal of these tests is to explore the GFM inverters' functionalities and dynamic response when in parallel with power grids to eventually develop universal specifications for GFM inverters. Both steady state (changing the inverter's frequency and voltage droop) and transient (adding step change in grid's frequency/voltage) tests are performed for each GFM inverter with the same testing circuit and testing protocol. The experimental results indicate the bench-marked performance that: 1) the GFM inverters can be dispatched through frequency and voltage droop intercepts to output the target power when paralleled to the grid; 2) the GFM inverters automatically respond to system frequency and voltage events to output the needed power, however, the GFM inverters all show stability issues when absorbing reactive power from the grid.

grid-forming inverters↗
DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗
NASA NTRSDate not supplied

Recent Results from Dragonfly Testing/Analysis as we head to PDR

Dragonfly is a relocatable lander mission to Saturn's moon Titan4, which as well as being a target of out-standing astrobiological interest as an organic-rich Ocean World, has the combination of low gravity (1/7 that of Earth) and a thick atmosphere (4x the density of Earth), making it an environment uniquely suitable for flight. Thus, the Dragonfly lander (similar in size to the Curiosity Mars rover) can take off using lift from a set of eight rotors and fly to a new landing site several kilometers away. The ability to perform such flights, lasting approximately 30 minutes, every month or so on Titan brings unprecedented mobility to planetary exploration, on a world known to have a diverse land-scape of dunes, craters and other features. Dragonfly is planned to launch in 2027, and following a nearly seven year interplanetary cruise would arrive at Titan by 2034. Due to the large scale height of the Titan atmosphere, Entry, Descent, and Landing (EDL) will be prolonged affair, taking nearly two hours to reach the surface. The ballistic entry environments that Dragonfly will be subjected to are fairly similar to that experienced by recent Mars missions; peak heating on the aeroshell will be about 300 W/sq.cm and peak deceleration is about 10g’s. Following the five minute entry segment, much of the remaining time is spent descending on the drogue and main para-chutes, which carry the dual role of decelerating the spacecraft and stabilizing the system during the long descent. While on one hand, this leisurely EDL sequence affords a relaxed timeline and plenty of time for event staging, it also provides ample opportunity for small disturbances to grow into potential flight safety risks, adding emphasis to the need for careful modeling, simulation and testing of key dynamic events. About two hours after entering the atmosphere, the nearly one metric ton rotocraft will be lowered approximately one meter out of the backshell (the ‘pose’ maneuver) to expose all eight rotors. The rotors will then be used to arrest any residual spin rate and prepare the system for transition to powered flight. Once despin is complete and the lander reaches a target altitude of 1.2 km above the surface (as verified by on-board lidar), the lander will be released and free fall for approximately one second before beginning controlled free flight. This entire “preparation for powered flight” process takes place over several minutes while the system is subject to the dynamic environment produced by so-called “wrist-mode” oscillations as the lander and backshell swing on the main parachute. Once in free flight, the lander will engage on-board terrain relative navigation to locate and navigate to a safe landing zone in the Shangri-La dune field south of Selk crater. Communication during this sequence will be limited to a series of direct-to-Earth X-band tones signalling key events and providing forensic information. Once on the ground, the lander will begin to send additional information, including data collected during this EDL sequence by the on-board Dragonfly Entry Aerosciences Measurements (DrEAM) instrumentation suite. This presentation will walk through the entry to first landing timeline in more detail, with a focus on recent analysis and testing results that inform system performance, margins and residual risk estimation.

Dragonfly↗
DOE OSTI2023

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Explaining System-Level Prognostics with Established Machine Learning Methods

System-level prognostics is crucial for ensuring reliability and enabling predictive maintenance in complex systems with interconnected components. This study presents a framework that integrates data-driven methods to predict the remaining useful life (RUL) of a subsystem under multiple and concurrent faults within a nuclear power plant system with explainable artificial intelligence (XAI). A nuclear power plant (NPP) operation was simulated to model the degradation behavior of NPP components, and four machine learning models—Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory (LSTM)—were evaluated for prognostics with a novel system RUL parameter. The LSTM model demonstrated potential superior repeatability, while SHAP (SHapley Additive exPlanations) for explainability provided consistent and trustworthy global explanations. In contrast, LIME (Local Interpretable Model-agnostic Explanations) offered localized interpretability but showed reduced stability for sequential data. Key findings include the interplay between component-level degradation and system-wide performance, with LSTM effectively capturing these dynamics through sequence-level predictions. The XAI techniques enhanced transparency by identifying critical features influencing model predictions and aligning with domain knowledge. Furthermore, this framework has significant implications for improving trust and understanding in predictive maintenance, particularly in safety-critical industries like nuclear energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Machine Learning Solutions for a Stable Grid Recovery

Grid operating security studies are typically employed to establish operating boundaries, ensuring secure and stable operation for a range of operation under NERC guidelines. However, if these boundaries are severely violated, existing system security margins will be largely unknown, as would be a secure incremental dispatch path to higher security margins while continuing to serve load. As an alternative to the use of complex optimizations over dynamic conditions, this work employs the use of machine learning to identify a sequence of secure state transitions which place the grid in a higher degree of operating security with greater static and dynamic stability margins. Several reinforcement learning solution methods were developed using deep learning neural networks, including Deep Q-learning, Mu-Zero, and the continuous algorithms Proximal Reinforcement Learning, and Advantage Actor Critic Learning. The work is demonstrated on a power grid with three control dimensions but can be scaled in size and dimensionality, which is the subject of ongoing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1998

A Spaceflight Magnetic Bearing Equipped Optical Chopper with Six-Axis Active Control

This paper describes the development of an ETU (Engineering Test Unit) rotary optical chopper with magnetic bearings. An ETU is required to be both flight-like, nearly identical to a flight unit without the need for material certifications, and demonstrate structural and performance integrity. A prototype breadboard design previously demonstrated the feasibility of meeting flight performance requirements using magnetic bearings. The chopper mechanism is a critical component of the High Resolution Dynamics Limb Sounder (HIRDLS) which will be flown on EOS-CHEM (Earth Observing System-Chemistry). Particularly noteworthy are the science requirements which demand high precision positioning and minimal power consumption along with full redundancy of coils and sensors in a miniature, lightweight package. The magnetic bearings are unique in their pole design to minimize parasitic losses and utilize collocated optical sensing. The motor is of an unusual disk-type ironless stator design. The ETU design has evolved from the breadboard design. A number of improvements have been incorporated into the ETU design. Active thrust control has been added along with changes to improve sensor stability, motor efficiency, and touchdown and launch survivability. It was necessary to do all this while simultaneously reducing the mechanism volume. Flight-like electronics utilize a DSP (Digital Signal Processor) and contain all sensor electronics and drivers on a single five inch by nine inch circuit board. Performance test results are reported including magnetic bearing and motor rotational losses.

Blumenstock, Kenneth A.↗
NASA NTRS1998

A Spaceflight Magnetic Bearing Equipped Optical Chopper with Six-Axis Active Control

This paper describes the development of an ETU (Engineering Test Unit) rotary optical chopper with magnetic bearings. An ETU is required to be both flight-like, nearly identical to a flight unit without the need for material certifications, and demonstrate structural and performance integrity. A prototype breadboard design previously demonstrated the feasibility of meeting flight performance requirements using magnetic bearings. The chopper mechanism is a critical component of the High Resolution Dynamics Limb Sounder (HIRDLS) which will be flown on EOS-CHEM (Earth Observing System-Chemistry). Particularly noteworthy are the science requirements which demand high precision positioning and minimal power consumption along with full redundancy of coils and sensors in a miniature, lightweight package. The magnetic bearings are unique in their pole design to minimize parasitic losses and utilize collocated optical sensing. The motor is of an unusual disk-type ironless stator design. The ETU design has evolved from the breadboard design. A number of improvements have been incorporated into the ETU design. Active thrust control has been added along with changes to improve sensor stability, motor efficiency, and touchdown and launch survivability. It was necessary to do all this while simultaneously reducing the mechanism volume. Flight-like electronics utilize a DSP (Digital Signal Processor) and contain all sensor electronics and drivers on a single five inch by nine inch circuit board. Performance test results are reported including magnetic bearing and motor rotational losses.

Blumenstock, K. A.↗
NASA NTRS1998

A Spaceflight Magnetic Bearing Equipped Optical Chopper with Six-Axis Active Control

This paper describes the development of an ETU (Engineering Test Unit) rotary optical chopper with magnetic bearings. An ETU is required to be both flight-like, nearly identical to a flight unit without the need for material certifications, and demonstrate structural and performance integrity. A prototype breadboard design previously demonstrated the feasibility of meeting flight performance requirements using magnetic bearings. The chopper mechanism is a critical component of the High Resolution Dynamics Limb Sounder (HIRDLS) which will be flown on EOS-CHEM (Earth Observing System-Chemistry). Particularly noteworthy are the science requirements which demand high precision positioning and minimal power consumption along with full redundancy of coils and sensors in a miniature, lightweight package. The magnetic bearings are unique in their pole design to minimize parasitic losses and utilize collocated optical sensing. The motor is of an unusual disk-type ironless stator design. The ETU design has evolved from the breadboard design. A number of improvements have been incorporated into the ETU design. Active thrust control has been added along with changes to improve sensor stability, motor efficiency, and touchdown and launch survivability. It was necessary to do all this while simultaneously reducing the mechanism volume. Flight-like electronics utilize a DSP (Digital Signal Processor) and contain all sensor electronics and drivers on a single five inch by nine inch circuit board. Performance test results are reported including magnetic bearing and motor rotational losses.

Blumenstock, Kenneth A.↗