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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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Areas covered include: • Accelerators for industrial applications: - Modest energy: few MeVs tens of MeV - Modest power: tens of kW hundreds of kW. • Specific requirements: – Simplicity – Low cost – Reliability – Work in industrial environment (harsh!) – Easy to operate – Small sizes – High efficiency
Work under this grant addressed a part of the challenge facing the closure of the nuclear fuel cycle; reducing the radiotoxicity of lived fission products (LLFP). It was based on the possibility that partitioning of isotopes and accelerator-based transmutation on particular LLFP combined with geological disposal may lead to an acceptable societal solution to the problem of management. The feasibility of using photonuclear processes based on the excitation of the giant dipole resonance (GDR) by bremsstrahlung radiation as a cost effective transmutation method was accessed. The nuclear reactions of interest: (γ,xn), (n,γ), (γ,p) can be induced by bremsstrahlung radiation produced by high power electron accelerators. The driver of these processes would be an accelerator that produces a high energy and high power electron beam of ~ 100 MeV. The major advantages of such accelerators for this purpose are that they are essentially available “off the shelf” and potentially would be of reasonable cost for this application. Methods were examined that used photo produced neutrons or the bremsstrahlung photons only, or use both photons and neutrons in combination for irradiations of selected LLFP. Extrapolating the results to plausible engineering scale transmuters it was found that the energy cost for 129 I and 99 Tc transmutation by these methods are about 2 and 4%, respectively, of the energy produced from 1000MWe.
A combination of an inelastic thermal spike model suitable for insulators and molecular dynamics simulations is used to study the effects of temperature and electronic energy loss on ion track formation, size and morphology in SrTiO 3 systems with pre-existing disorder. We find temperature dependence of the ion track size. In addition, we find a threshold in the electronic energy loss for a given pre-existing defect concentration, which indicates a threshold in the synergy between the inelastic and elastic energy loss.
From the inception of power systems, synchronous machines have acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, power electronics interfaces are playing a growing role as they are the primary interface for several types of renewable energy sources and storage technologies. As the role of power electronics in systems continues to grow, it is crucial to investigate the properties of bulk power systems in low inertia settings. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. Furthermore, the inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings and, hence, differing levels of inertia. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the interaction between the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.
Knowing the rate at which particle radiation releases energy in a material, the “stopping power,” is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well understood in the literature, the route for gathering data on the electronic contribution has for decades remained costly and reliant on many simplifying assumptions, including that materials are isotropic. We establish a method that combines time-dependent density functional theory (TDDFT) and machine learning to reduce the time to assess new materials to hours on a supercomputer and provide valuable data on how atomic details influence electronic stopping. Our approach uses TDDFT to compute the electronic stopping from first principles in several directions and then machine learning to interpolate to other directions at a cost of 10 million times fewer core-hours. We demonstrate the combined approach in a study of proton irradiation in aluminum and employ it to predict how the depth of maximum energy deposition, the “Bragg Peak,” varies depending on the incident angle—a quantity otherwise inaccessible to modelers and far outside the scales of quantum mechanical simulations. The lack of any experimental information requirement makes our method applicable to most materials, and its speed makes it a prime candidate for enabling quantum-to-continuum models of radiation damage. The prospect of reusing valuable TDDFT data for training the model makes our approach appealing for applications in the age of materials data science.
Despite the IEEE Power Electronics Society (PELS) establishing Technical Committee 10 on Design Methodologies with a focus on the cyber-physical security of power electronics systems, a holistic design methodology for addressing security vulnerabilities remains underdeveloped. This gap largely stems from the limited integration of computer science and power/control engineering studies in this interdisciplinary field. Addressing the inadequacy of unilateral cyber or control perspectives, this article presents a novel four-layer cyber-physical security model specifically designed for electric machine drives. Central to this model is the innovative control information flow (CIF) model, residing within the control layer, which serves as a pivotal link between the cyber layer's vulnerable resources and the physical layer's state-space models. By mapping vulnerable resources to control variable space and tracing attack propagation, the CIF model facilitates accurate impact predictions based on tainted control laws. The effectiveness and validity of this proposed model are demonstrated through hardware experiments involving two typical cyber-attack scenarios, underscoring its potential as a comprehensive framework for multidisciplinary security strategies.
Power spectrum analysis (PSA) is a fast, non-destructive, sensitive method for examining commercial off-the-shelf ( COTS ) electronic components. These features make PSA attractive for both component screening and surveillance in support of component reliability efforts. Current analysis methods limit the utility of PSA due to the need to manually examine the results of analysis to identify anomalous parts. This study demonstrates the development and application of a workflow to automate the screening of COTS electronic components. Further, this study demonstrates the use of multivariate algorithms to assess aging of Zener diodes. These workflows can be readily extended to other components, combining the benefits of PSA and multivariate analysis to screen and evaluate COTS electronic components.
ST5 mission requirements include validation of Lithium-ion battery in orbit. Accommodation in the power system for Li-ion battery can be reduced with smaller amp-hour size, highly matched cells when compared to the larger amp-hour size approach. Result can be lower system mass and increased reliability.
Electrical systems with high power and high power density are integral to many aerospace and energy applications. These systems, enabled by power electronics with wide bandgap semiconductor devices, require management of both efficiency/thermal aspects and electromagnetic interference that are problems specific to high power and high frequency applications, respectively. In addition to advanced active components, these applications also require passive components (inductors, capacitors, conductors) capable of operation under challenging conditions. This work surveys the state of the art of magnetic components and soft magnetic materials used as inductive cores. The wide variety of motor and converter topologies translates to a variety of requirements in the magnetics including mechanical properties, permeabilities, and frequency response. The scaling impact of material properties will be surveyed with respect to component performance and sizing, using both data from experiment and the published literature. Variations on simulations, both in lumped circuits and finite element models, will also be discussed as these are important aspects of the design phase of modern power electronics.
The high temperature of the surface of Venus poses many difficulties. Previous Venus landers have only operated for short durations before succumbing to the heat. NASA Glenn Research Center conducted a study on communications for long duration Venus surface missions. I report the findings in this presentation. Current technology allows production of communications transceivers that can operate on the surface of Venus, at temperatures above 450 C and pressures of over 90 atmospheres. While these transceivers would have to be relatively simple, without much of the advanced signal processing often used in modern transceivers, since current and near future integrated circuits cannot operate at such high temperatures, the transceivers will be able to meet the requirements of proposed Venus Surface mission. The communication bands of interest are High Frequency or Very High Frequency (HFNHF) for communication between Venus surface and airborne probes (including surface to surface and air to air), and Ultra High Frequency (UHF) to Microwave bands for communication to orbiters. For HFNHF, transceivers could use existing vacuum tube technology. The packaging of the vacuum tubes may need modification, but the internal operating structure already operates at high temperatures. Using metal vacuum structures instead of glass, allows operation at high pressure. Wide bandgap transistors and diodes may be able to replace some of the thermionic components. VHF communications would be useful for line-of- sight operations, while HF would be useful for short-wave type communications using the Venusian ionosphere. UHF and microwave communications use magnetically focused thermionic devices, such as traveling wave tubes (TWTs), magnetron (M-type) amplifiers, and klystrons for high power amplifiers, and backward wave oscillators (BWOs) and reflex klystrons for oscillators. Permanent magnets are already in use in industry that can operate at 500 C. These magnets could focus electron beam tubes on the surface of Venus. While microwave windows will need to be designed for the high pressure, diamond windows have already been demonstrated, so high-pressure microwave windows can be designed and built. Thus, all of these devices could be useful for Venus surface missions. Current electronic power conditioners to supply the high voltages used in these microwave devices cannot operate at high temperatures, but earlier electronic power conditioners that used vacuum tubes can be modified to work at high temperature. Evaluating the various devices in this study, the M-type traveling wave tube (where a traveling wave structure is used in a crossed-field device, similar to the Amplitron used on the Apollo missions) stood out for the high power amplifier since it requires a single high voltage, simplifying the power supply design. Since the receiver amplifier is a low power amplifier, the loss of efficiency in linear beam devices without a depressed collector (and thus needing a single high voltage) is not important; a low noise TWT is a possible solution. Before solid-state microwave amplifiers were available, such TWTs were built with a 1-2 dB noise figure. A microwave triode or transistor made from a wide bandgap material may be preferable, if available. Much of the development work needed for Venusian communication devices will need to focus on the packaging of the devices, and their connections, but the technology is available to build transceivers that can operate on the surface of Venus indefinitely.
In power electronics, prediction of states may be used for identification of faults, determination of aging of components, identification of bad data measurements, among others. Prediction of states in power electronics have broadly been based on: (a) physics-based models, (b) data-driven models, and (c) hybrid models. In this paper, data-driven approaches are presented for intelligent prediction of states in multi-port autonomous reconfigurable solar power plant (MARS) and compared. The data-set needed to train the data-driven models based on artificial intelligence (AI) algorithms has been identified and the trained models are evaluated under different extrapolated normal and abnormal operating conditions. The AI algorithms include nonlinear auto-regressive exogenous model (NARX), spiking neural networks (SNN), and decision tree. The models are compared and contrasted. The best model (NARX) is evaluated under different normal and abnormal operating conditions that have indicated accurate prediction.
The recent increase in infiltration of distributed resources has challenged the traditional operation of power systems. Simultaneously, devastating effects of recent natural disasters have questioned the resilience of power infrastructure for an electricity dependent community. In this study, a solution has been presented in the form of a resilient smart grid network which utilizes Distributed Energy Resources (DERs) and Machine Learning (ML) algorithms to improve the power availability during disastrous events. In addition to power electronics with load categorization features, the presented system utilizes ML tools to use the information from neighbouring units and external sources to make complicated logical decisions directed towards provide power to critical loads at all times. Furthermore, provided model encourages consideration of ML tools as a part of smart grid design process together with power electronics and controls, not as an additional feature.
The aeronautics industry has been challenged on many fronts to increase efficiency, reduce emissions, and decrease dependency on carbon-based fuels. With subsonic transports serving as the dominant contributor to the fuel consumption and carbon footprint of global aviation, the need for environmentally-responsible transportation has been met with a boom of research in the field of aircraft propulsion electrification across industry, government, and academic organizations. However, adoption of electrified propulsion systems for large commercial aircraft today is unattainable, due to the lack of motors and power electronics appropriately sized for these vehicles, high weight requirements of conventional electrical energy storage systems, and new principles required to design these classes of aircraft. The mission of the Center for High-Efficiency Electrical Technologies for Aircraft (CHEETA) program is to develop, mature, and design disruptive technologies for electric commercial aviation. The associated technologies being researched include distributed aero-propulsion system integration, high-efficiency electrochemical power conversion, flight-weight electric machines and power electronics, materials and systems for superconducting high-efficiency power transmission, and methods for complex system integration and optimization. Additionally, the current program is investigating the use of unconventional energy storage and power generation architectures, such as liquid hydrogen fuel and high-efficiency fuel cell systems. The research program provides a direct line-of-sight to not only achieving, but potentially even exceeding the aviation community goals for transition to alternative propulsion and energy through convergence of various novel technologies. The end result of maturation and integration of these technologies is an aircraft system with a quiet, efficient propulsion system that produces zero carbon dioxide, nitrogen oxides, and particulate matter emissions at the vehicle level.
The design and testing of a 400 watt, dual phase, dual rotor, field modulated inductor alternator is described. The system is designed for use as a flywheel to ac utility line or flywheel to dc bus (electric vehicle) power converter. The machine is unique in that it uses dual rotors and separately controlled fields to produce output current and voltage which are in phase with each other. Having the voltage and current in phase allows the power electronics to be made of simple low cost components. Based on analytical predictions and experimental results, development of a complete 22 kilowatt (30 Hp) power conversion system is recommended. This system would include power electronics and controls and would replace the inductor alternator with an improved electromagnetic conversion system.
Energy efficiency is a key performance indicator for battery storage systems. A detailed electro-thermal model of a stationary lithium-ion battery system is developed and an evaluation of its energy efficiency is conducted. The model offers a holistic approach to calculating conversion losses and auxiliary power consumption. Sub-models for battery rack, power electronics, thermal management as well as the control and monitoring components are developed and coupled to a comprehensive model. The simulation is parametrized based on a prototype 192 kWh system using lithium iron phosphate batteries connected to the low voltage grid. The key loss mechanisms are identified, thoroughly analyzed and modeled. Generic profiles featuring various system operation modes are evaluated to show the characteristics of stationary battery systems. Typically the losses in the power electronics outweigh the losses in the battery at low power operating points. The auxiliary power consumption dominates for low system utilization rates. For estimation of real-world performance, the grid applications Primary Control Reserve, Secondary Control Reserve and the storage of surplus photovoltaic power are evaluated. Conversion round-trip efficiency is in the range of 70-80%. Finally, overall system efficiency, which also considers system power consumption, is 8-13 percentage points lower for Primary Control Reserve and the photovoltaic-battery application. However, for Secondary Control Reserve, the total round-trip efficiency is found to be extremely low at 23% due to the low energy throughput of this application type.
In order to power or charge electronic devices wirelessly, a bi-directional wireless power transfer method has been proposed and experimentally investigated. In the proposed design, two receiving coils are used on both sides of a transmitting coil along its central axis to receive the power wirelessly from the generated magnetic fields through strongly coupled magnetic resonance. It has been observed experimentally that the maximum power transfer occurs at the operating resonant frequency for optimum electric load connected across the receiving coils on both side. The optimum wireless power transfer efficiency is 88% for the bi-directional power transfer technique compared 84% in the one side receiver system. By adopting the developed bi-directional power transfer method, two electronic devices can be powered up or charged simultaneously instead of a single device through usual one side receiver system without affecting the optimum power transfer efficiency.
This paper presents a networked hardware-in-the-loop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAr regulation technologies as an example to illustrate system setups, communication requirements among different HIL simulation systems, and system connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.
The dynamic operation of networked microgrids leads to varying topological configurations and generator commitments and dispatches. These variations correspond to systems with different electrical characteristics. The fixed control gains of high-speed power electronic devices may result in undesirable system performance when the electrical characteristics change significantly. As such, it is necessary to tune the control gains of power electronics devices to adapt to the changing system characteristics. This paper uses observer-based reinforcement learning to automatically tune the proportional-integral (PI) gains of phase lock loop (PLL) controller of grid-following (GFL) inverters to adapt to the changing system strengths, that would be seen in networked microgrid operations. Simulation results using an operational electric distribution system, modeled as networked microgrids, are presented to demonstrate the need and effectiveness of the proposed adaptive controls.