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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Localization Using Visual Odometry and a Single Downward-Pointing Camera

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

Swank, Aaron J.↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Recent Advancements in spoken language processing technologies have enabled the development of reliable automation tools to assist air traffic control (ATC) operations. These advancements present a unique opportunity to strategically implement digital taxi instructions for aircraft movement on the ground. Digital taxi instructions issue taxiing procedures to pilots as textual or graphical instructions. There are several benefits of digital instructions, including a reduction in radio congestion, elimination of communication errors, and improved aircraft monitoring capabilities. Natural language understanding (NLU) models can extract digital taxi instructions from verbal instructions issued by air traffic controllers. This capability enables the implementation of a digital taxi communication framework with minimal changes to the existing air traffic controller operational environment. We explore a novel application for NLU: automatically generating digital taxi instructions from air traffic controller speech. We describe the development of an annotation scheme to represent (aircraft) ground traffic communications in the US National Airspace System (NAS).Our annotation scheme uses intent classification and slot filling to extract taxi instructions, enabling NLU models to leverage syntactic information. Several neural network models were trained to categorize the controller’s intent and label information relevant to his or her intent.Our research demonstrates that it is feasible to use NLU to automatically generate digitaltaxi instructions, suggesting that it is a powerful tool for the implementation of digital taxi communications.

Hillel Steinmetz↗
DOE OSTI2024

Double-Side Cooled 1.2kV, 300A SiC MOSFET Phase-leg Modules for 200 kW, > 100 kW/L Traction Inverters

The packaging of a double-side cooled 1.2 kV, 149 A SiC phase-leg modules has been reported in recent years for making 100 kW, 100 kW/L traction inverters. Each phase-leg module consists of two SiC MOSFETs, one per switch position. Six of the phase-leg modules are assembled into a segmented inverter configuration to meet the power and power density requirement. In this work, the layout of the phase-leg module was redesigned to include four of the SiC MOSFETs, two per switch position, with the aim of doubling the power to 200 kW and increasing the power density beyond 100 kW/L, but with only a 10.25% footprint increase. Key features of the packaging technology developed in the previous work were implemented in the current work, which include silver sintering for chip bonding and porous silver inter-posts for bonding device source pads to substrate. Parasitic extraction simulation showed that the four-chip module has a low parasitic inductance of 4.7 nH, like the two-chip module. Static characterization of the four-chip prototypes showed a low average on-resistance of 9 mΩ and a low average leakage current of 5 nA at Vds of 1.2 kV.

Zhang, Zichen↗
DOE OSTI2022

Characterizing particle-based thermal storage performance using optical methods for use in next generation concentrating solar power plants

Concentrating Solar Power (CSP) generation is an attractive option for low-emission power generation; however, the high costs of thermal storage associated with concentrating solar create a large barrier for their use and adaptation into modern life. Lowering their operation costs, while maintaining high thermal storage and transfer performance is essential. Solid particle-based heat exchange systems can reduce CSP cost but are often less efficient. Efforts to increase their performance have led to use of binary size particle mixes. Presented is an optical-based thermal analysis technique used to measure near-wall thermal conductivity of particle beds essential in determining their heat exchanger efficiency. Modulated Photothermal Radiometry is used to make dynamic temperature measurements, allowing for the extraction of the most relevant thermal properties like thermal conductivity, specific heat, and effusivity. The system uses a modulated laser source causing a damped periodic heat flux, resulting in a frequency and thermal property dependent surface temperature, of which is measured using radiometry. Lock-In techniques are used to extrapolate the amplitude of the signal. Plotting the amplitude against the root angular frequency allows for effusivity measurement by ratio to a known sample. Using specific heat measurements from literature and density measurements, the thermal conductivity of the particle mixes can be calculated. The simplicity of MPTR to probe through the depth of the bed is ideal for use in CSP for dynamic thermal performance monitoring.

Corona, Javier↗
DOE OSTI2025

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bridging Power System Protection Gaps with Data-driven Approaches

Protection is a critical function in power systems to avoid equipment damage, maintain personnel safety, and support system reliability. However, current protective relay technology cannot adequately protect equipment and personnel from effects of some events; these deficiencies are termed protection gaps. In this research, a data-driven approach is proposed to complement traditional protection technology and distinguish fault conditions from transients caused by normal operations. A convolutional neural network (CNN) based fault detection approach is implemented to achieve data translation invariance of the time-series input data. As a result, the data-driven method can accurately detect system faults despite variation and noise in the input data. In addition, using the CNN–based method avoids the complicated manual feature extraction procedure required by many traditional data-driven methods. The effectiveness of the proposed approach is tested on four kinds of protection gaps: high impedance faults, transformer/generator inter-turn faults, distribution system PV circuit faults, and the mis-operation situations of Zone 3 line protection relays operating under system stress. Finally, a transfer learning method is also proposed to address the common issue of data-driven methods for which real-world training data are scarce. Extensive study results demonstrate that the proposed approach can accurately bridge power system protection gaps.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Femtoscopic study of the proton-proton and proton-deuteron systems in heavy-ion collisions at the LHC

This work reports femtoscopic correlations of p – – p ($\overline{p}$ – – $\overline{p}$) and p – – d ($\overline{p}$ – – $\overline{d}$) pairs measured in Pb–Pb collisions at center-of-mass energy per nucleon $\sqrt{s_{NN}}$ = 5.02 TeV in the ALICE Collaboration. A fit to the measured proton-proton correlation functions allows one to extract the dependence of the nucleon femtoscopic radius of the particle-emitting source on the pair transverse mass (m T ) and on the average charge particle multiplicity $\langle$dN ch /dη$\rangle$ 1/3 for three centrality intervals (0–10%, 10 – – 30 %, 30 – – 50 %). In both cases, the expected power-law and linear scalings are observed, respectively. The measured p–d correlations can be described by both two- and three-body calculations, indicating that the femtoscopy observable is not sensitive to the short-distance features of the dynamics of the p-(p-n) system, due to the large inter-particle distances in Pb–Pb collisions at the LHC. Indeed, in this study, the minimum measured femtoscopic source sizes for protons and deuterons have a minimum value at 2.73$^{+0.05}_{–0.05}$ and 3.10$^{+1.04}_{–0.86}$ fm, respectively, for the 30–50% centrality collisions. Moreover, the m T -scaling obtained for the p–p and p–d systems is compatible within 1σ of the uncertainties. These findings provide new input for fundamental studies on the production of light (anti)nuclei under extreme conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Startup regime of high-efficiency tapering-enhanced FEL oscillator

In this paper, we present a design of a high-efficiency high-gain free-electron laser oscillator based on the use of a strongly tapered undulator for extracting energy from high-brightness electron beams. We provide an analytical model of the setup followed by numerical simulations for lasing at the wavelength of 13.5 nm. We discuss the optimization of the system in steady state and the conditions necessary for the pass-per-pass buildup of the power from shot noise level. We propose the use of fast phase shifters as a way to accelerate the buildup. Finally, we present time-dependent simulations of the oscillator and discuss the role of spectral filtering. The optimized working point yields a total energy conversion efficiency from the electron beam to output radiation above 1% at the wavelength of 13.5 nm.

Beam dynamics↗
DOE OSTI2024

Inertia Estimation and Trend Analysis of the United States Power Grid Interconnections

The transition from conventional to modern power systems is causing an increase in integration of inverter-based resources (IBRs). This generally leads to a decrease in total system inertia, which in-turn increases the system’s rate-of-change-of-frequency (RoCoF) during disturbances. This poses a threat to the frequency stability of the system and may falsely trigger protective devices. To monitor system status and plan for integrating renewable energy sources like photovoltaic, wind, and energy storage systems, a realistic study of inertia estimation and analysis in the United States (US) over the past decade is needed. This paper uses field-measured phasor measurement unit (PMU) data collected throughout the US from 2013 to 2023 via the Frequency Monitoring Network (FNET/GridEye) operated by the University of Tennessee, Knoxville (UTK) and Oak Ridge National Laboratory (ORNL). The collected PMU frequency data is utilized to estimate the system inertia of the three US interconnections: Eastern, Western, and Texas. Various RoCoF time windows are investigated for estimating the inertia of each interconnection by maximizing the correlation coefficient between the measured RoCoF and power mismatch. The resulting inertia trends over the past decade show approximately a 6% decline in inertia in the Eastern interconnection, a 15% decline in inertia in the Western interconnection, and a 16% increase in inertia in Texas. Key insights into how inertia is changing amidst the complex energy landscape are extracted using the fuel mix trend data. This provides valuable information for future energy strategies and planning.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

DQ Admittance Model Extraction for IBRs via Gaussian Pulse Excitation

While $dq$ admittance models have shown to be very useful for stability analysis, extracting admittance models of inverter-based resources (IBRs) from the electromagnetic transient (EMT) simulation environment using frequency scans takes time. In this letter, a new perturbation method based on Gaussian pulses in combination with the system identification algorithms shows great promise for parametric $dq$ admittance model extraction. We present the $dq$ admittance model extracting method for a type-4 wind turbine. Challenges in implementing Gaussian pulse excitation are also pointed out. In conclusion, the extracted $dq$ admittance model via the new method shows to have a high matching degree with the measurements obtained from frequency scans.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1995

Ion propulsion

An ion engine is a plasma thruster which produces thrust by extracting ions from the plasma and accelerating them to high velocity with an electrostatic field. The ions are then neutralized and leave the engine as high velocity neutral particles. The advantages of ion engines are high specific impulse and efficiency and their ability to operate over a wide range of input powers. In comparison with other electric thrusters, the ion engine has higher efficiency and specific impulse than thermal electric devices such as the arcjet, microwave, radiofrequency and laser heated thrusters and can operate at much lower current levels than the MPD thruster. However, the thrust level for an ion engine may be lower than a thermal electric thruster of the same operating power, consistent with its higher specific impulse, and therefore ion engines are best suited for missions which can tolerate longer duration propulsive phases. The critical issue for the ion engine is lifetime, since the prospective missions may require operation for several thousands of hours. The critical components of the ion engine, with respect to engine lifetime, are the screen and accelerating grid structures. Typically, these are large metal screens that must support a large voltage difference and maintain a small gap between them. Metallic whisker growth, distortion and vibration can lead to arcing, and over a long period of time ion sputtering will erode the grid structures and change their geometry. In order to study the effects of long time operation of the grid structure, we are developing computer codes based on the Particle-In-Cell (PIC) technique and Laser Induced Fluorescence (LIF) diagnostic techniques to study the physical processes which control the performance and lifetime of the grid structures.

Meserole, J. S.↗
NASA NTRS1989

Ion propulsion

An ion engine is a plasma thruster which produces thrust by extracting ions from the plasma and accelerating them to high velocity with an electrostatic field. The ions are then neutralized and leave the engine as high velocity neutral particles. The advantages of ion engines are high specific impulse and efficiency and their ability to operate over a wide range of input powers. In comparison with other electric thrusters, the ion engine has higher efficiency and specific impulse than thermal electric devices such as the arcjet, microwave, radio frequency, and laser heated thrusters and can operate at much lower current levels than the MPD thruster. However, the thrust level for an ion engine may be lower than a thermal electric thruster of the same operating power, consistent with its higher specific impulse, and therefore ion engines are best suited for missions which can tolerate longer duration propulsive phases. The critical issue for the ion engine is lifetime, since the prospective missions may require operation for several thousands of hours. The critical components of the ion engine, with respect to engine lifetime, are the screen and accelerating grid structures. Typically, these are large metal screens that must support a large voltage difference and maintain a small gap between them. Metallic whisker growth, distortion, and vibration can lead to arcing, and over a long period of time ion sputtering will erode the grid structures and change their geometry. In order to study the effects of long time operation of the grid structure, we are developing computer codes based on the particle-in-cell (PIC) technique and laser induced fluorescence (LIF) diagnostic techniques to study the physical processes which control the performance and lifetime of the grid structures.

Meserole, J. S.↗
NASA NTRS2006

Discharge Chamber Plasma Structure of a 30-cm NSTAR-Type Ion Engine

Single Langmuir probe measurements are presented over a two-dimensional array of locations in the near Discharge Cathode Assembly (DCA) region of a 30-cm diameter ring cusp ion thruster over a range of thruster operating conditions encompassing the high-power half of the NASA throttling table. The Langmuir probe data were analyzed with two separate methods. All data were analyzed initially assuming an electron population consisting of Maxwellian electrons only. The on-axis data were then analyzed assuming both Maxwellian and primary electrons. Discharge plasma data taken with beam extraction exhibit a broadening of the higher electron temperature plume boundary compared to similar discharge conditions without beam extraction. The opposite effect is evident with the electron/ion number density as the data without began, extraction appears to be more collimated than the corresponding data with beam extraction. Primary electron energy and number densities are presented for one operating condition giving an order of magnitude of their value and the error associated with this calculation.

Herman, Daniel A.↗
NASA NTRS2006

Short Haul Civil Tiltrotor Contingency Power System Preliminary Design

Single Langmuir probe measurements are presented over a two-dimensional array of locations in the near Discharge Cathode Assembly (DCA) region of a 30-cm diameter ring cusp ion thruster over a range of thruster operating conditions encompassing the high-power half of the NASA throttling table. The Langmuir probe data were analyzed with two separate methods. All data were analyzed initially assuming an electron population consisting of Maxwellian electrons only. The on-axis data were then analyzed assuming both Maxwellian and primary electrons. Discharge plasma data taken with beam extraction exhibit a broadening of the higher electron temperature plume boundary compared to similar discharge conditions without beam extraction. The opposite effect is evident with the electron/ion number density as the data without began, extraction appears to be more collimated than the corresponding data with beam extraction. Primary electron energy and number densities are presented for one operating condition giving an order of magnitude of their value and the error associated with this calculation.

Eames, David J. H.↗
NASA NTRS2007

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Hunter, Gary W.↗
NASA NTRS2020

Increasing anthropogenic methane emissions arise equally from agricultural and fossil fuel sources

Climate stabilization remains elusive, with increased greenhouse gas concentrations already increasing global average surface temperatures 1.1°C above pre-industrial levels (World Meteorological Organization 2019). Carbon dioxide (CO2) emissions from fossil fuel use, deforestation, and other anthropogenic sources reached ~ 43 billion metric tonnes in 2019 (Friedlingstein et al 2019, Jackson et al 2019). Storms, floods, and other extreme weather events displaced a record 7 million people in the first half of 2019 (IDMC 2019). When global mean surface temperature four million years ago was 2°C–3°C warmer than today (a likely temperature increase before the end of the century), ice sheets in Greenland and West Antarctica melted and parts of East Antarctica’s ice retreated, causing sea levels to rise 10–20 m (World Meteorological Organization 2019). Methane (CH4) emissions have contributed almost one quarter of the cumulative radiative forcings for CO2, CH4, and N2O (nitrous oxide) combined since 1750 (Etminan et al 2016). Although methane is far less abundant in the atmosphere than CO2, it absorbs thermal infrared radiation much more efficiently and, in consequence, has a global warming potential (GWP) ~86 times stronger per unit mass than CO2 on a 20-year timescale and 28- times more powerful on a 100-year time scale (IPCC 2014). Global average methane concentrations in the atmosphere reached ~1875 parts per billion (ppb) at the end of 2019, more than two-and-a-half times preindustrial levels (Dlugokencky 2020). The largest methane sources include anthropogenic emissions from agriculture, waste, and the extraction and use of fossil fuels as well as natural emissions from wetlands, freshwater systems, and geological sources (Kirschke et al 2013, Saunois et al 2016a, Ganesan et al 2019). Here, we summarize new estimates of the global methane budget based on the analysis of Saunois et al (2020) for the year 2017, the last year of the new Global Methane Budget and the most recent year data are fully available. We compare these estimates to mean values for the reference ‘stabilization’ period of 2000–2006 when atmospheric CH4 concentrations were relatively stable. We present data for sources and sinks and provide insights for the geographical regions and economic sectors where emissions have changed the most over recent decades.

fossil fuel sources↗
DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗