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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Analysis and Evaluation of Thermally Annealed Pyrolytic Graphite Heat Spreader for Power Modules

Next generation power modules demand increased heat extraction capability along with reduced weight and volume. In this paper, thermally annealed pyrolytic graphite (TPG) is analyzed and compared with conventional materials used in power modules for thermal management. Fundamental properties of TPG are explained and compared with commonly used materials in power module heat spreaders and substrates. The encapsulated TPG based heat spreader is manufactured and compared with bulk copper in simulation and experimental based analysis. The results show that encapsulated TPG based heat spreader achieves more than 50% reduction in thermal resistance along with 48% reduction in weight in the heat spreader layer.

Gurpinar, Emre↗
DOE OSTI2024

High-Temperature Wireless Sensor Platform Powered by Energy Scavenging

This paper reports on the development of key components required for a self-powered oscillator unit designed to wirelessly transmit its signal under full insertion in high-temperature (HT) harsh-environments (HE), such as those present in power plants and industrial settings (metallurgic, oil extraction, molding, and aerospace). The oscillator employed a silicon carbide (SiC) power transistor and HT passive components on a screen-printed alumina circuit board capable of operation beyond 300 °C. The HT oscillator circuit was powered solely by in-situ energy scavenging thermoelectric generator (TEG) modules using passive cooling, eliminating the need for an external power supply or active cooling. In addition, a silicon-based external booster circuit was used to achieve the required TEG voltage regulation to test the TEG-powered HT oscillator circuit. The TEG-powered oscillator circuit was tested inside a non-metallic furnace from room temperature to over 300 °C for transmission of a wireless signal, which was detected outside the furnace at 11 ft (3.4 m). Such a wireless transmitting system powered only by in-situ TEGs, with no requirement for external power or active cooling, is very attractive for flexible, mobile stand-alone control and sensor units targeted for operation in HT HE conditions found in power plants and industrial settings.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1978

An inverter/controller subsystem optimized for photovoltaic applications

Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. Optimization of the inverter/controller design is discussed as part of an overall photovoltaic power system designed for maximum energy extraction from the solar array. The special design requirements for the inverter/ controller include: a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy.

Pickrell, R. L.↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1995

Development of a 1 kW, 200 C Mapham Inventor

Electronic systems and components are often exposed to high temperature environment in space-based applications, nuclear power facilities, and geothermal energy extraction fields. A key requirement for these systems is, therefore, to withstand the high temperature exposure while maintaining efficient and reliable operation. Efforts were taken to design and develop a high temperature power inverter capable of 200 C operation. A 1 kW, 20 kHz Mapham inverter was designed and evaluated as a function of temperature at different load levels. The inverter system, excluding its input, control, and logic circuits, was characterized at temperatures from ambient to 200 C at 0%, 50%, and 100% resistive loading. With an applied input voltage of 75 VDC, the inverter produced an output of 250 VAC. The results obtained, which indicate good operational characteristics of the inverter up to 200 C, are presented and discussed.

Hammoud, Ahmad↗
DOE OSTI2021

Rotor blade imbalance fault detection for variable-speed marine current turbines via generator power signal analysis

Marine hydrokinetic (MHK) turbines extract renewable energy from oceanic environments. However, due to the harsh conditions that these turbines operate in, system performance naturally degrades over time. Thus, ensuring efficient condition-based maintenance is imperative towards guaranteeing reliable operation and reduced costs for marine hydrokinetic power. This work proposes a novel framework aimed at identifying and classifying the severity of rotor blade pitch imbalance faults experienced by marine current turbines (MCTs). In the framework, a Continuous Morlet Wavelet Transform (CMWT) is first utilized to acquire the wavelet coefficients encompassed within the 1P frequency range of the turbine's rotor shaft. From these coefficients, several statistical indices are tabulated into a six-dimensional feature space. Next, Principle Component Analysis (PCA) is employed on the resulting feature space for dimensionality reduction, and then the application of a K-Nearest Neighbor (KNN) machine learning algorithm is utilized for fault detection and severity classification. The effectiveness of the proposed framework is validated using a high-fidelity MCT numerical simulation platform, where results demonstrate that the presence of a pitch imbalance fault can be accurately detected 100% of the time and correctly classified based upon severity more than 97% of the time.

42 ENGINEERING↗
DOE OSTI2021

Rootkit detection system

A system and method (referred to as the system) detect infectious code. The system injects a repetitive software code that causes malware in a monitored device to render a detectable direct current power consumption profile. A guide wave generator generates a guide wave signal that establishes an observational window that is applied to data that represent a direct current source power consumption of the monitored device. An extraction device extracts a portion of the data that represent the direct current source power consumption of the monitored device. A deviation engine identifies the malware on the monitored device without processing data associated with a prior identification of the malware or identifying a source of the malware or identifying a location of the malware on the monitored device.

Dawson, Joel↗
DOE OSTI2023

DQ Admittance Extraction for Inverter-Based Resources

The power grid industry is pushing for electromagnetic transient (EMT)-based studies for generation interconnection and planning process due to high penetrations of inverter-based resource (IBRs). Vendor-specific and site-specific black-box IBR models are preferred in those simulation studies. For small-signal analysis, measurement-based admittance models are necessary. In this paper, we demonstrate the extraction of frequency-domain dq frame IBR models. These linear models are specific to operating conditions. We demonstrate two extraction methods: frequency scan and a step response-based method. The latter relies on converting time-domain responses to Laplace-domain expressions via eigensystem realization analysis (ERA). Both can lead to dq admittance representation and the latter is time saving.

admittance model↗
DOE OSTI2022

Power quality disturbances diagnosis: A 2D densely connected convolutional network framework

The fast and accurate diagnosis of power quality disturbances (PQD) aids in avoiding shutdowns and unnecessary procedures, concerning electric energy distribution systems. As such, a number of techniques have been tested and applied in order to reach this objective. Majority of the techniques applied are two-step based. On the first step, power quality disturbances features are extracted. Second step, considering features extracted, disturbance classification is implemented. Recently, relevant literature has presented data-driven signal processing-based approaches, as deep convolutional neural networks (DCNN), which can implement both processing steps while providing automated recognition of patterns and outliers in data. However, not considered by state-of-art, power quality disturbances are evolving in nature, while all possible regularities might not be represented in the dataset. In this work a 2 Dimension Densely Connected Convolutional Network (2D-DenseNet) framework is presented. Further, a case study with synthetic disturbance events are analyzed. Easy-to-implement formulation, built on the 2D-DenseNet, without hard-to-design parameters, highlight potential aspects for real-life implementation.

42 ENGINEERING↗
DOE OSTI2025

Low-Cost Identification and Monitoring of Diverse MELs in Residential and Commercial Buildings with PowerBlade (Final Technical Report)

This report describes our progress in developing a scalable wireless metering system that integrates plug-load energy meters that measure real, reactive, and apparent power along with load monitoring based on extracting high-fidelity electrical waveform features collected at every load to capture power profiles and automatically identify and categorize MELs, and make this technology available to the research, commercial, and government sectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Sustainable ammonia synthesis from nitrogen wet with sea water by single-step plasma catalysis

Ammonia synthesis at ambient conditions employing intermittent distributed green sources of energy and feedstocks is globally sought to replace the centralized Haber-Bosch (H-B) process operating at high temperature and pressure. We report herein for the first time an effective and sustainable ammonia synthesis pathway from N 2 wet with seawater vapor over spherical SiO 2 and M/SiO 2 (M: Ag, Cu, and Co) catalysts driven by non-thermal plasma (NTP). Experimental results indicate that the presence of a catalyst is required for ammonia production from seawater vapor and N 2 . The Co/SiO 2 catalyst delivered the highest ammonia synthesis rate (r NH 3 ) of 3.7 mmol g cat -1 h -1 and energy yield of 3.2 g NH 3 ∙kW -1 ∙h -1 at a relatively low input power of 2 W. The extraction of H atoms from H 2 O molecules plays an important role in the ammonia synthesis from seawater vapor. Finally, this work unfolds a novel platform for the subsequent optimization of sustainable ammonia production from endless resources such as seawater and N 2 through catalytic non-thermal plasma potentially powered by renewable sources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Benzocyclobutene polymer as an additive for a benzocyclobutene-fullerene: application in stable p–i–n perovskite solar cells

A poly(methacrylate) with benzocyclobutene side chains, CL, has been synthesized by radical polymerization for use as a crosslinking additive for a previously reported benzocyclobutene-functionalized fullerene, PCBCB, which can be thermally insolubilized following solution processing. Films of PCBCB incorporating CL and n-doped with (IrCp*Cp) 2 exhibit in-plane electrical conductivities around ten times higher than those of n-doped films without CL, while the use of CL also reduces leaching of dopant ions from the film upon washing. The performance and stability of perovskite solar cells using insolubilized PCBCB:CL, insolubilized PCBCB, or PCBM as top electron-extraction layers are compared; cells with undoped PCBCB:CL extraction layers exhibit higher average and maximum power conversion efficiencies (16 and 18.5%, respectively) than their PCBM and PCBCB counterparts. Devices with undoped PCBCB:CL extraction layers also showed excellent thermal stability, retaining 92% of their stabilized power output after aging for 3000 h at 85 °C in the dark in a nitrogen atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Argon metastable density and temperature of a 43 GHz microplasma

Argon (1s 5 ) metastable density and translational gas temperature are experimentally measured using laser diode absorption spectroscopy within a 43 GHz microplasma. The plasma is initiated and sustained within a photonic crystal constructed from a rectangular array of alumina rods, each 1 mm in diameter. This configuration generates stable microplasma from 10 to 600 Torr using millimeter wave power from 100 to 1200 mW. The metastable density is in the order of 10 18 m –3 at low pressure. However, Ar(1s 5 ) density decreases to undetectable levels with increasing pressure and wave power. The gas temperature is extracted from the Lorentzian line shape of the absorption profile at 811.53 nm. The gas temperature increases from approximately 400 K at low pressure to 2000 K at 320 Torr (427 mbar, 4.27 × 10 4 Pa). Furthermore, these data are compared with previous results and suggest that the microplasma has a dense core of electrons that depletes the metastable density at high gas pressure and wave power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Physics-Based Feature Extraction from Bulk Time-Series PMU Datasets for Event Detection

In this work, two physics-based feature extraction techniques are developed for bulk time-series phasor measurement unit (PMU) datasets collected from the field to train the machine learning model for anomaly detection. Two approaches have been developed to extract useful features for different types of events. An admittance-based feature extraction technique is developed to detect events that involve line outages and system topology variations. The developed algorithm extracts the system equivalent admittance variation. Additionally, Fielder’s Theory is utilized to further reduce the potential computation burden by sectionalizing large-scale grids and datasets into smaller areas. Second, an oscillation-based feature extraction technique is developed to detect low-frequency oscillations in power grids. The dominant oscillation modes in the grids are extracted using energy-sorted Prony analysis. The extracted dominant oscillation modes by the developed work exhibit a high fitting resolution. Finally, the developed techniques have been validated using large-scale and real-world datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2004

Deep-Sea Video Cameras Without Pressure Housings

Underwater video cameras of a proposed type (and, optionally, their light sources) would not be housed in pressure vessels. Conventional underwater cameras and their light sources are housed in pods that keep the contents dry and maintain interior pressures of about 1 atmosphere (.0.1 MPa). Pods strong enough to withstand the pressures at great ocean depths are bulky, heavy, and expensive. Elimination of the pods would make it possible to build camera/light-source units that would be significantly smaller, lighter, and less expensive. The depth ratings of the proposed camera/light source units would be essentially unlimited because the strengths of their housings would no longer be an issue. A camera according to the proposal would contain an active-pixel image sensor and readout circuits, all in the form of a single silicon-based complementary metal oxide/semiconductor (CMOS) integrated- circuit chip. As long as none of the circuitry and none of the electrical leads were exposed to seawater, which is electrically conductive, silicon integrated- circuit chips could withstand the hydrostatic pressure of even the deepest ocean. The pressure would change the semiconductor band gap by only a slight amount . not enough to degrade imaging performance significantly. Electrical contact with seawater would be prevented by potting the integrated-circuit chip in a transparent plastic case. The electrical leads for supplying power to the chip and extracting the video signal would also be potted, though not necessarily in the same transparent plastic. The hydrostatic pressure would tend to compress the plastic case and the chip equally on all sides; there would be no need for great strength because there would be no need to hold back high pressure on one side against low pressure on the other side. A light source suitable for use with the camera could consist of light-emitting diodes (LEDs). Like integrated- circuit chips, LEDs can withstand very large hydrostatic pressures. If power-supply regulators or filter capacitors were needed, these could be attached in chip form directly onto the back of, and potted with, the imager chip. Because CMOS imagers dissipate little power, the potting would not result in overheating. To minimize the cost of the camera, a fixed lens could be fabricated as part of the plastic case. For improved optical performance at greater cost, an adjustable glass achromatic lens would be mounted in a reservoir that would be filled with transparent oil and subject to the full hydrostatic pressure, and the reservoir would be mounted on the case to position the lens in front of the image sensor. The lens would by adjusted for focus by use of a motor inside the reservoir (oil-filled motors already exist).

Cunningham, Thomas↗
DOE OSTI2024

High-resolution ion mobility based on traveling wave structures for lossless ion manipulation resolves hidden lipid features

Abstract High-resolution ion mobility (resolving power > 200) coupled with mass spectrometry (MS) is a powerful analytical tool for resolving isobars and isomers in complex samples. High-resolution ion mobility is capable of discerning additional structurally distinct features, which are not observed with conventional resolving power ion mobility (IM, resolving power ~ 50) techniques such as traveling wave IM and drift tube ion mobility (DTIM). DTIM in particular is considered to be the “gold standard” IM technique since collision cross section (CCS) values are directly obtained through a first-principles relationship, whereas traveling wave IM techniques require an additional calibration strategy to determine accurate CCS values. In this study, we aim to evaluate the separation capabilities of a traveling wave ion mobility structures for lossless ion manipulation platform integrated with mass spectrometry analysis (SLIM IM-MS) for both lipid isomer standards and complex lipid samples. A cross-platform investigation of seven subclass-specific lipid extracts examined by both DTIM-MS and SLIM IM-MS showed additional features were observed for all lipid extracts when examined under high resolving power IM conditions, with the number of CCS-aligned features that resolve into additional peaks from DTIM-MS to SLIM IM-MS analysis varying between 5 and 50%, depending on the specific lipid sub-class investigated. Lipid CCS values are obtained from SLIM IM ( TW(SLIM) CCS) through a two-step calibration procedure to align these measurements to within 2% average bias to reference values obtained via DTIM ( DT CCS). A total of 225 lipid features from seven lipid extracts are subsequently identified in the high resolving power IM analysis by a combination of accurate mass-to-charge, CCS, retention time, and linear mobility-mass correlations to curate a high-resolution IM lipid structural atlas. These results emphasize the high isomeric complexity present in lipidomic samples and underscore the need for multiple analytical stages of separation operated at high resolution. Graphical abstract

Reardon, Allison R. (ORCID:0000000165830134)↗