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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 613 records · Page 34

Propulsion Control Technology Development Needs to Address NASA Aeronautics Research Mission Goals for Thrusts 3a and 4

The Commercial Aero-Propulsion Control Working Group (CAPCWG), consisting of propulsion control technology leads from The Boeing Company, GE Aviation, Honeywell, Pratt & Whitney, Rolls-Royce, and NASA (National Aeronautics and Space Administration) Glenn Research Center, has been working together over the past year to identify propulsion control technology areas of common interest that we believe are critical to achieving the challenging NASA Aeronautics Research goals for Thrust 3a: Ultra-Efficient Commercial Vehicles - Subsonic Transports, and Thrust 4: Transition to Alternative Propulsion and Energy. This paper describes the various propulsion control technology development areas identified by CAPCWG as most critical for NASA to invest in. For Thrust 3a these are: i) Integrated On-Board Model Based Engine Control and Health Management; ii) Flexible and Modular Networked Control Hardware and Software Architecture; iii) Intelligent Air/Fuel Control for Low Emissions Combustion; and iv) Active Clearance Control. For Thrust 4a, the focus is on Hybrid Electric Propulsion (HEP) for single aisle commercial aircraft. The specific technology development areas include: i) Integrated Power and Propulsion System Dynamic Modeling for Control; ii) Control Architectures for HEP; iii) HEP Control Verification and Validation; and iv) Engine/Airplane Control Integration. For each of the technology areas, the discussion includes: problem to be solved and how it relates to NASA goals, and the challenges to be addressed in reducing risk.

Propulsion Control↗

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Thunderstorm and Fair-weather Quasi-Static Electric Fields Over Land and Ocean

Natural lightning and the associated clouds are known to behave differently over land and ocean, but many questions remain. We expand the related observational datasets by obtaining simultaneous quasi-static electric field observations over coastal land, near-shore water, and deep ocean regions during both fair-weather and thunderstorm periods. Oceanic observations were obtained using two 3-m NOAA buoys that were instrumented with Campbell Scientific electric field mills to measure the quasi-static electric fields. These data were compared to selected electric field records from the existing on-shore electric field mill suite of 31 sensors at Kennedy Space Center (KSC). Lightning occurrence times, locations and peak current estimates for both onshore and ocean were provided by the U.S. National Lightning Detection Network. The buoy instruments were first evaluated on-shore at the Florida coast, and the first system was calibrated for field enhancements and to confirm proper behavior of the system in elevated-field environments. The buoys were then moored 20 mi and 120 mi off the coast of KSC in February (20 mi) and August (120 mi) 2014. Diurnal fair-weather fields at both ocean sites matched will with each other and with those found during the Carnegie cruise, but mean values were 33% smaller, due at least in-part to constraints on the calibration procedure. Diurnal fair-weather fields variations at coastal and inland sites were a poorer match than offshore, likely because the offshore environment is “cleaner” with limited variations in local space charge, lower surface aerosol densities, little surface heating to disturb the surface charge layer during fair weather, and fewer local radioactive sources to modulate the near-surface electrical conductivity. Storm-related static fields were 4-5× larger at both oceanic sites than over land, likely due to decreased screening by near-surface space charge produced by corona current. The time-evolution of the electric field and field changes during storm approach are sufficiently different over land and ocean to warrant further study. This work shows the quality, accuracy, and reliability of these data, and has demonstrated the practicality of off-shore electric field measurements for safety- and launch-related decision making at KSC.

Lightning↗

Structural Health Monitoring and Impact Detection Using Neural Networks for Damage Characterization

Detection of damage due to foreign object impact is an important factor in the development of new aerospace vehicles. Acoustic waves generated on impact can be detected using a set of piezoelectric transducers, and the location of impact can be determined by triangulation based on the differences in the arrival time of the waves at each of the sensors. These sensors generate electrical signals in response to mechanical motion resulting from the impact as well as from natural vibrations. Due to electrical noise and mechanical vibration, accurately determining these time differentials can be challenging, and even small measurement inaccuracies can lead to significant errors in the computed damage location. Wavelet transforms are used to analyze the signals at multiple levels of detail, allowing the signals resulting from the impact to be isolated from ambient electromechanical noise. Data extracted from these transformed signals are input to an artificial neural network to aid in identifying the moment of impact from the transformed signals. By distinguishing which of the signal components are resultant from the impact and which are characteristic of noise and normal aerodynamic loads, the time differentials as well as the location of damage can be accurately assessed. The combination of wavelet transformations and neural network processing results in an efficient and accurate approach for passive in-flight detection of foreign object damage.

Ross, Richard W.↗

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Foundation Models for the Electric Power Grid

Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich representations of complex systems and dynamics can be applied to many downstream applications. Therefore, advances in FMs can find uses in electric power grids, challenged by the energy transition and climate change. This paper calls for the development of FMs for electric grids. We highlight their strengths and weaknesses amidst the challenges of a changing grid. It is argued that FMs learning from diverse grid data and topologies, which we call grid foundation models (GridFMs), could unlock transformative capabilities, pioneering a new approach to leveraging AI to redefine how we manage complexity and uncertainty in the electric grid. Finally, we discuss a practical implementation pathway and road map of a GridFM-v0, a first GridFM for power flow applications based on graph neural networks, and explore how various downstream use cases will benefit from this model and future GridFMs.

AI-based power flow simulation↗

Material Characterization Study of Magnetite Nanocrystals for RF Sensing

Magnetite nanocrystals show promise for electrically small gigahertz frequency applications, which could lead to miniaturizing transformer cores and new sensing technologies. This work presents a rigorous radiofrequency characterization of these nanocrystals using vector network analyzer (VNA) ferromagnetic resonance (FMR) measurements. For the first time, two different average diameters of Fe 3 O 4 nanocrystals are investigated (7.3 and 20.2 nm). When the VNA–FMR results were compared to micromagnetic simulations, the magnetic anisotropy (K 1 ) deviated from the ideal mean orientation value of K 1 /2 to K 1 /80 for the 7.3 nm nanocrystal. In contrast, the obtained magnetic anisotropy in 20.2 nm nanocrystals slightly deviated to K 1 /11 due to less structural deformations. These findings resulted in a newly proposed methodology for an approximate simulation based on VNA–FMR measurements. In addition, this work estimates the approximate amount of nanocrystals needed to measure a useful VNA–FMR spectrum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Atmosphere explorer missions C, D, and E. Spacecraft experiment interface definition study

The Atmosphere Explorer Missions C, D, & E Spacecraft/Experiment Interface Definition Study is discussed. The objectives of the study included an analysis of the accommodation requirements of the experiments for the three missions, an assessment of the overall effect of these requirements on the spacecraft system design and performance, and the detailed definition of all experiment/spacecraft electrical, mechanical, and environmental interfaces. In addition, the study included the identification and definition of system characteristics required to ensure compatibility with the consolidated STADAN and MSFN communications networks.

Source record↗

The linear polarization of 3C 345 at milliarcsecond resolution

A polarization-sensitive 6 cm map of the superluminal quasar 3C 345 with angular resolution 2.5 x 4.7 mas was made using four stations of the US VLBI network. The optically thick core is essentially unpolarized, while both of the knots in the jet are highly polarized. The inner knot C3 has m = 11 percent at electric vector position angle chi = 22 deg, and the outer knot C2 has m = 6 percent at chi = 83 deg. Thus the magnetic field appears to be parallel to the jet near its base and to change direction down the jet.

Wardle, J. F. C.↗

Lunar Reconnaissance Orbiter (LRO) Command and Data Handling Flight Electronics Subsystem

A document describes a high-performance, modular, and state-of-the-art Command and Data Handling (C&DH) system developed for use on the Lunar Reconnaissance Orbiter (LRO) mission. This system implements a complete hardware C&DH subsystem in a single chassis enclosure that includes a processor card, 48 Gbytes of solid-state recorder memory, data buses including MIL-STD-1553B, custom RS-422, SpaceWire, analog collection, switched power services, and interfaces to the Ka-Band and S-Band RF communications systems. The C&DH team capitalized on extensive experience with hardware and software with PCI bus design, SpaceWire networking, Actel FPGA design, digital flight design techniques, and the use of VxWorks for the real-time operating system. The resulting hardware architecture was implemented to meet the LRO mission requirements. The C&DH comprises an enclosure, a backplane, a low-voltage power converter, a single-board computer, a communications interface board, four data storage boards, a housekeeping and digital input/output board, and an analog data acquisition board. The interfaces between the C&DH and the instruments and avionics are connected through a SpaceWire network, a MIL-STD-1553 bus, and a combination of synchronous and asynchronous serial data transfers over RS-422 and LVDS (low-voltage differential-signaling) electrical interfaces. The C&DH acts as the spacecraft data system with an instrument data manager providing all software and internal bus scheduling, ingestion of science data, distribution of commands, and performing science operations in real time.

Nguyen, Quang↗

Phased Antenna Array for Global Navigation Satellite System Signals

Systems and methods for phased array antennas are described. Supports for phased array antennas can be constructed by 3D printing. The array elements and combiner network can be constructed by conducting wire. Different parameters of the antenna, like the gain and directivity, can be controlled by selection of the appropriate design, and by electrical steering. Phased array antennas may be used for radio occultation measurements.

Turbiner, Dmitry↗

Calculating the High-Latitude Ionospheric Electrodynamics Using A Machine Learning-Based Field-Aligned Current Model

We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML-AIM). ML-AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC-derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML-AIM inputs are 60-min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML-AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML-AIM produces physically accurate ionospheric potential patterns such as the two-cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML-AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data-assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML-AIM than others. ML-AIM is unique and innovative because it predicts ionospheric responses to the time-varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi-static ionospheric condition under quasi-steady solar wind/IMF conditions. Plans are underway to improve ML-AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

auroral electrodynamics↗

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

The ultimate goal is to create an extraterrestrial unmanned system for subsurface mapping and exploration. Neural networks are to be used to recognize anomalies in the profiles that correspond to potentially exploitable subsurface features. The ground penetrating radar (GPR) techniques are likewise identical. Hence, the preliminary research focus on GPR systems will be directly applicable to seismic systems once such systems can be designed for continuous operation. The original GPR profile may be very complex due to electrical behavior of the background, targets, and antennas, much as the seismic record is made complex by multiple reflections, ghosting, and ringing. Because the format of the GPR data is similar to the format of seismic data, seismic processing software may be applied to GPR data to help enhance the data. A neural network may then be trained to more accurately identify anomalies from the processed record than from the original record.

Mcgill, J. W.↗

Smoke generator

A smoke generator is disclosed which is particularly suitable for mounting on the wing tips of an aircraft and for conducting airflow studies. The device includes a network of thermally insulated tubes for carrying a fluid which is used to produce smoke. The fluid, which need not be combustible, is heated above its vaporization temperature by electric current which is passed through the fluid conduit tubes, so that the tubes serve both as fluid conduits and resistance heating elements. Fluid supply and monitoring systems and electrical control systems are also disclosed.

Rogers, J. R.↗

Design study of wind turbines 50 kW to 3000 kW for electric utility applications. Volume 1: Summary report

Wind turbine configurations that would lead to generation of electrical power in a cost effective manner were considered. All possible overall system configurationss, operating modes, and sybsystem concepts were evaluated for both technical feasibility and compatibility with utility networks, as well as for economic attractiveness. A design optimization computer code was developed to determine the cost sensitivity of the various design features, and thus establish the configuration and design conditions that would minimize the generated energy costs. The preliminary designs of both a 500 kW unit and a 1500 kW unit operating in a 12 mph and 18 mph median wind speed respectively, were developed. The rationale employed and the key findings are summarized.

Source record↗

Modeling of the Orbital Debris Population of RORSAT Sodium-Potassium Droplets

A large population resident in the orbital debris environment is composed of eutectic sodium-potassium (NaK) droplets, released during the reactor core ejection of 16 nuclear-powered Radar Ocean Reconnaissance Satellites (RORSATs) launched in the 1980s by the former Soviet Union. These electrically conducting RORSAT debris objects are spherical in shape, generating highly polarized radar returns. Their diameters are mostly in the centimeter and millimeter size regimes. Since the Space Surveillance Network catalog is limited to objects greater than 5 cm in low Earth orbit, our current knowledge about this special class of orbital debris relies largely on the analysis of Haystack radar data. This paper elaborates the simulation of the RORSAT debris populations in the new NASA Orbital Debris Engineering Model ORDEM2010, which replaces ORDEM2000. The estimation of the NaK populations uses the NASA NaK-module as a benchmark. It follows the general statistical approach to developing all other ORDEM2010-required LEO populations (for various types of debris and across a wide range of object sizes). This paper describes, in detail, each major step in the NaK-population derivation, including a specific discussion on the conversion between Haystack-measured radar-cross-sections and object-size distribution for the NaK droplets. Modeling results show that the RORSAT debris population is stable for the time period under study and that Haystack data sets are fairly consistent over the observations of multiple years.

Xu, Y.-L.↗

Meteorological Aspects of Two Modes of Lightning Triggered Upward Lightning (LTUL) Events in Sprite-Producing MCSs

During the 2013 convective storm season, a high resolution 3-D Lightning Mapping Array was deployed to north central Kansas (Cummins et al, this conference.) In conjunction with fixed and mobile camera systems and electric field mills, this allowed for detailed investigations of lightning induced upward lighting (LTUL) discharges from tall objects in the region, including wind turbines. Also, concurrent observations using a network of low-light cameras deployed over the central U.S. as part of the PhOCAL program detected transient luminous events (TLEs) above the Kansas LMA (KSLMA). During the night of 29-30 May 2013, waves of precipitation associated with several large MCSs traversing Kansas moved through the KSLMA domain. We focus on two LTUL events that exemplify two modes of upward lightning production from tall structures. At 0859Z, 30 May 2013, a nearby + 92 kA CG, with extensive in-cloud branching passing overhead a wind farm, was followed by complex LTUL discharges from four turbines. In addition, a sprite was confirmed by the Bennett, CO SpriteNet camera. The parent flash covered a very large area. It initiated near the MCS convective leading line ~150 km to the south, and traveled into a stratiform precipitation maximum over the KSLMA. Typically when a +CG precedes an LTUL, the triggering component is either 1) the return stroke that traverses the leader network which initially forms near the towers or 2) new negative leader activity that develops once the return stroke reaches the end of the initial leader network that may not have initially been near the tower. In the latter case, the new leader development passes near the towers and triggers upward positive leaders similar to those associated with only an intracloud flash. The +CG return stroke may hit >10 km from the towers and the new leader development may travel extensive distances before getting close enough to the towers to trigger upward lightning. In this case, there was the typical long delay between the +CG return stroke and LTUL initiation (10s to 100s of ms). The parent lightning discharges for both sprites and LTULs have many common aspects and tend to occur in similar meteorological regimes, with the two phenomena often occurring together. An earlier LUTL, at 2320Z, 29 May 2013 was captured at 9900 fps by a Phantom camera in the PhOCAL mobile Lightning Investigation Vehicle (LIV). This discharge, exhibiting numerous recoil leaders, also occurred in a stratiform region some ~50-100 km north of an MCS convective core. While there was no preceding +CG, there was an extensive network of IC channels, one of which passed overhead close to the turbine. These observations are consistent with the ongoing UPLIGHTS studies of LTULs from tall towers in Rapid City. While a +CG is usually involved (~85% of the time), the LTUL occurs because of the associated extensive in cloud components passing over towers. The earlier case without a +CG typifies this second mode where the triggering component is a negative leader associated with the IC activity passing near the towers initiates the upward positive leaders. We will discuss the parent discharges, shown in their meteorological (radar and satellite) context, and attempt to better understand the charge structures present in both the convective and stratiform regions of the MCS. The sprite and its relationship to the parent discharge will similarly be discussed

Lyons, W. A.↗