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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Improving Discovery, Sharing, and Use of Water Data: Initial Findings and Suggested Future Work

Collaborative management of water resources requires a broad suite of “water data” that extends beyond basic information about water quantity and quality to other related topics such as water infrastructure, aquatic ecosystem health, socioeconomic factors, and power generation. Water data are disparate in nature because they are collected and provided by many entities, and in some cases, remain challenging to access and use. The U.S. Department of Energy’s Water Power Technologies Office initiated a project to characterize relevant categories of water data; describe the current state of accessing, using, and visualizing water data; and outline investigatory pathways for future efforts aimed at improving the discovery, sharing, and use of water data. Input on these topics was solicited from a small but diverse cross section of members of the water resources community. Fourteen broad categories of water data were identified: dams; ecology; flood control; hydroclimatology; hydrography; hydrology; hydropower; management landscape; migratory barriers; recreation and aesthetic importance; socioeconomic; water quality; water availability and use; and weather. Stakeholder perspectives on the accessibility and usability of water data indicate these aspects are affected by a complex set of technical and social factors. However, stakeholders generally agreed that better access to water data can provide a range of benefits to water management, and they stressed the need to generate broad support from water data users and producers. Two investigatory pathways were outlined that, taken together, provide a logical progression toward the goals of the project. The first pathway emphasizes further investigation to better define target audiences and data needs, identify opportunities for collaboration between related efforts, and conduct value demonstration activities to generate further support for improving discovery and access of water data. The second pathway focuses on creating a comprehensive vision for potential solutions that improve the discovery of water data. Several activities that align with the first pathway are suggested for the next phase of the project.

13 HYDRO ENERGY↗
DOE OSTI2022

Pulsed power to control growth of silicon nanoparticles in low temperature flowing plasmas

Low-temperature plasmas have seen increasing use for synthesizing high-quality, mono-disperse nanoparticles (NPs). Recent work has highlighted that an important process in NP growth in plasmas is particle trapping—small, negatively charged nanoparticles become trapped by the positive electrostatic potential in the plasma, even if only momentarily charged. In this article, results are discussed from a computational investigation into how pulsing the power applied to an inductively coupled plasma (ICP) reactor may be used for controlling the size of NPs synthesized in the plasma. The model system is an ICP at 1 Torr to grow silicon NPs from an Ar/SiH 4 gas mixture. This system was simulated using a two-dimensional plasma hydrodynamics model coupled to a three-dimensional kinetic NP growth and trajectory tracking model. The effects of pulse frequency and pulse duty cycle are discussed. We identified separate regimes of pulsing where particles become trapped for one pulsed cycle, a few cycles, and many cycles—each having noticeable effects on particle size distributions. For the same average power, pulsing can produce a stronger trapping potential for particles when compared to continuous wave power, potentially increasing particle mono-dispersity. Pulsing may also offer a larger degree of control over particle size for the same average power. Experimental confirmation of predicted trends is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Deep learning model to detect various synchrophasor data anomalies

High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Additionally, four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.

42 ENGINEERING↗
DOE OSTI2020

High-power few-cycle Cr:ZnSe mid-infrared source for attosecond soft x-ray physics

The development of mid-infrared, high-energy pulses of extremely short pulse duration is of great importance to the strong-field physics community, as it enables extension of the high-harmonic cutoff towards the keV range of photon energies. Here we demonstrate a C r 2 + : Z n S e laser amplifier delivering 7 mJ, 100 fs pulses at 1 kHz repetition rate and 2.4 µm central wavelength with excellent energy stability and beam quality. These pulses are post-compressed to 39 fs, 6.2 mJ, and 115 GW peak power in a novel nonlinear compression scheme. The laser system was used to generate coherent soft x-ray radiation up to 0.6 keV covering the entire water window, which is of high importance for bio-relevant applications. The obtained results open a wide range of applications in nonlinear optics, attosecond and strong-field physics, and remote sensing.

Leshchenko, Vyacheslav E. (ORCID:0000000199708559)↗
DOE OSTI2021

Hierarchical Convolutional Neural Networks for Event Classification on PMU Measurements

Event classification is one of the central components of automated disturbance analysis based on PMU measurements. Obtaining high-quality event labels remains a challenge for supervised learning-based classification of local and system-wide events in power grids due to its labor-intensive requirement. We present a sensitivity study considering rapidly refined, partially and fully inspected event labels that leads to evidence that hierarchical convolutional neural networks (HCNNs) outperform traditional classification models regardless of the quality of the available event labels. Furthermore, it is demonstrated that performance similar to the one obtained using entirely domain-driven labeling can be achieved as long as the involved expert does not mislabel more than ~5% of the event data captured by PMU measurements.

47 OTHER INSTRUMENTATION↗
NASA NTRS1961

Effects of Gyroscopic Cross Coupling Between Pitch and Yaw on the Handling Qualities of VTOL Aircraft

Gyroscopic cross coupling between pitch and yaw was simulated with a variable-stability helicopter while hovering in a yawing maneuver to ascertain the effect of cross coupling on handling qualities. Pilot ratings of the controllability of cross coupling were obtained for various combinations of longitudinal control power, angular velocity about the yaw axis, and simulated engine angular momentum. A theoretical investigation, supplemented by simulator data, was undertaken to determine the effect of longitudinal damping on the coupling controllability. Also, a comparison was made between flight and simulator data. The results indicated that for an aircraft with otherwise satisfactory longitudinal handling qualities, the level of cross coupling is satisfactory when less than 30 percent of the available longitudinal control will trim out the largest gyroscopic coupling moment which might be encountered. Increased longitudinal damping resulted in a significant increase in the controllability of pitch-yaw gyroscopic cross coupling.

Garren, John F., Jr.↗
NASA NTRS2011

Progress in Materials and Component Development for Advanced Lithium-ion Cells for NASA's Exploration Missions

Vehicles and stand-alone power systems that enable the next generation of human missions to the Moon will require energy storage systems that are safer, lighter, and more compact than current state-of-the- art (SOA) aerospace quality lithium-ion (Li-ion) batteries. NASA is developing advanced Li-ion cells to enable or enhance the power systems for the Altair Lunar Lander, Extravehicular Activities spacesuit, and rovers and portable utility pallets for Lunar Surface Systems. Advanced, high-performing materials are required to provide component-level performance that can offer the required gains at the integrated cell level. Although there is still a significant amount of work yet to be done, the present state of development activities has resulted in the synthesis of promising materials that approach the ultimate performance goals. This report on interim progress of the development efforts will elaborate on the challenges of the development activities, proposed strategies to overcome technical issues, and present performance of materials and cell components.

Reid, Concha, M.↗
DOE OSTI2025

Transforming the Process Industries through Electrification: Challenges and Opportunities

For the more than 70 years, the process industries have provided essential fuels and materials for global growth. Increased manufacturing production comes with substantial environmental impact. Reducing environmental impact through process electrification, carbon capture, and other emerging technologies would require large changes throughout the process industries. We review opportunities and challenges related to electrification, focusing on technical, operational, and economic considerations. Here, we conclude that electrification could completely eliminate scope 1 CO 2 emissions, increase product quality, and reduce the equipment size and cost. On the other hand, it calls for a significant expansion of power generation capacity, as well as new paradigms for process design and operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Sensitivity and Detection Limit of Spectroscopic-Grade Perovskite CsPbBr 3 Crystal for Hard X-Ray Detection

We report spectroscopic-grade single crystal detectors can register the energies of individual X-ray interactions enabling photon-counting systems with superior resolution over traditional photoconductive X-ray detection systems. Current technical challenges have limited the preparation of perovskite semiconductors for energy-discrimination X-ray photon-counting detection. Here, this work reports the deployment of a spectroscopic-grade CsPbBr 3 Schottky detector under reverse bias for continuum hard X-ray detection in both the photocurrent and spectroscopic schemes. High surface barriers of approximate to ≈ 1 eV are formed by depositing solid bismuth and gold contacts. The spectroscopic response under a hard X-ray source is assessed in resolving the characteristic X-ray peak. The methodology in enhancing X-ray sensitivity by controlling the X-ray energies and flux, and voltage, is described. The X-ray sensitivity varies between a few tens to over 8000 μC Gy air -1 cm -2 . The detectable dose rate of the CsPbBr 3 detectors is as low as 0.02 nGy air s -1 in the energy discrimination configuration. Finally, the unbiased CsPbBr 3 device forms a spontaneous contact potential difference of about 0.7 V enabling high quality of the CsPbBr 3 single crystals to operate in "passive" self-powered X-ray detection mode and the X-ray sensitivity is estimated as 14 μC Gy air -1 cm -2 . The great potential of spectroscopic-grade CsPbBr 3 devices for X-ray photon-counting systems is anticipated in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Introduction: Neuromorphic Materials

The explosive growth in data collection and the need to process it efficiently, as well as the desire to automate increasingly complex tasks in transportation, medical care, manufacturing, security and many other fields have motivated a growing interest in neuromorphic computing. Unlike the binary, transistorbased ON/OFF logic gates and separate logic and memory functionalities employed in digital computing, neuromorphic computing is inspired by animal brains that use interconnected synapses and neurons to perform processing, storage and transmission of information at the same location, while only consuming ~20 W or less of power. Motivated by the brain’s efficiency, adaptability, self-learning and resiliency qualities, neuromorphic computing can be broadly defined as an approach to processing and storing information using hardware and algorithms inspired by models of biological neural systems. Present research in neuromorphic computing encompasses approaches that vary significantly in their degree of neuro-inspiration, from systems that only incorporate features such as asynchronous, event-driven operation or use crossbar arrays of non-volatile memory (NVM) elements to accelerate deep neural networks (DNNs), to designs that embrace the extreme parallelism, sparsity, reconfigurability, adaptability, complexity and stochasticity observed in nervous systems. The term ‘neuromorphic’ computing is often credited to Carver Mead, who in the 1980s investigated Si-based analog electronics to replicate functions of the animal retina. Earlier important advances in this field include the work of Frank Rosenblatt, who proposed the concept of the perceptron, Bernard Widrow, who used this concept to build one of the first analog neural networks, the Adaline and many other researchers (see ref. 6 for an historical perspective on neuromorphic computing). With the recent increase in the use of artificial intelligence and large language models, and rising concerns over the associated energy costs, interest in neuromorphic hardware has expanded rapidly. According to some estimates, driven largely by the drastic growth in the training use of artificial intelligence (AI) models using the current computing architectures, the energy cost of computing is projected to reach the energy supply worldwide by 2045. Furthermore, while this is not a realistic outcome, it means that, if more efficient computing technologies are not developed -- soon -- the world will soon become one where demand for energy and market constraints limit the continued increase of societal access to AI and cloud services from data centers. Data centers used for training and use of these models consume hundreds of terawatt hours of electricity, already past 4% of the US electricity demand.

Circuits↗
DOE OSTI2021

Bulk Production of Any Ratio 12 C: 13 C Turbostratic Flash Graphene and Its Unusual Spectroscopic Characteristics

As graphene enjoys worldwide research and deployment, the biological impact, geologic degradation, environmental retention, and even some physical phenomena remain less well studied. Bulk production of 13 C-graphene yields a powerful route to study all of these questions. Gram scale synthesis of high quality and high purity turbostratic flash graphene with varying amounts of 13 C-enrichment, from 5% to 99% is reported here. Here, the material is characterized by solid state nuclear magnetic resonance spectroscopy, Raman spectroscopy, infrared (IR) spectroscopy, X-ray photoelectron spectroscopy and inductively coupled plasma mass spectrometry. Notably, an unusual enhancement in the Raman spectroscopic D’ peak is observed, resulting from the modification in vibrational frequency through isotopic enrichment favoring intravalley phonon scattering modes. While the IR absorbance spectrum of graphene is for the most part silent, we prepare here 13 C-enhanced graphene samples that show a large aromatic 12 C= 13 C stretch that reveals this IR-active mode.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Thoroughly testing and integrating hundreds of Pull Requests per month: ROOT’s new Cost-efficient and Feature Rich GitHub-based CI

ROOT is an open source framework, freely available on GitHub, at the heart of data acquisition, processing and analysis of HE(N)P experiments, and beyond. It is developed collaboratively: contributions are not authored only by ROOT team members, but also by the user community at large: developers and scientists from universities, labs as well as the private sector. More than 1500 GitHub Pull Requests are merged on average per year. It is in this context that code integration acquires a primary role. The review of code contributions isn’t enough: not only they need to be thoroughly reviewed, they also need to be thoroughly tested through a powerful CI infrastructure on several different platforms to comply with the high code quality standards of the project. Since the end of 2023, ROOT moved its continuous integration system from Jenkins to GitHub Actions. In this contribution, we characterise the transition to the GitHub CI, focussing on our strategy, its implementation and the lessons learned, as well as the advantages the new system offers with respect to the previous one. Particular emphasis will be given to the evaluation of the cost-benefit ratio for Jenkins and GitHub Actions for the ROOT project. We also describe how we manage to run in less than one hour thousands of unit, integration, functional and end-to-end tests on different flavours of Windows, four versions of macOS, as well as about ten of the most used Linux distributions, taking advantage of the CERN computing infrastructure.

Piparo, Danilo [CERN]↗
DOE OSTI2024

Dark Matter and other BSM searches with SRF cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Dark Matter and other BSM searches with SRF cavities at SQMS

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Cavity Based Searches for New Particles and Gravitational Waves

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will focus mostly on Dark SRF and MAGO activities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Evaluation of Pozzolan-substituted Cast Stone for Pretreated Hanford Tank Waste

Portland cement. The future availability of quality Class F fly ash has come into question as coal-fired power plants are being converted to gas or taken offline. Consequently, alternative pozzolanic reagents are being evaluated for fly ash replacement in cementitious matrices for treating radioactive waste and debris. In 2023 and 2024, Savannah River National Laboratory (SRNL) was funded to evaluate natural pozzolans for the replacement of Class F fly in the Savannah River Site (SRS) Saltstone formulation. Based on the promising results and uncertain availability of Class F fly ash in the northwestern US, Hanford Tank Waste Operations & Closure, LLC (H2C) requested SRNL to evaluate the potential for substituting natural pozzolans in the Hanford West Area Pretreated Low Activity Tank Waste (PTW/LAW) Cast Stone formulation1 . Task 1 in this request was to determine the change in Cast Stone volume resulting from stabilization/solidification of 1 L of PTW/LAW tank waste. The densities of three (Hess Pumice, tephra pumice, and clinoptilolite zeolite) pozzolan-substituted Baseline Cast Stone mixes were determined, and volume changes relative to the fly ash-Baseline Mix with a water-to-dry mix = 0.40 were calculated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1974

Development and fabrication of S-band chip varactor parametric amplifier

A noncryogenic, S-band parametric amplifier operating in the 2.2 to 2.3 GHz band and having an average input noise temperature of less than 30 K was built and tested. The parametric amplifier module occupies a volume of less than 1-1/4 cubic feet and weighs less than 60 pounds. The module is designed for use in various NASA ground stations to replace larger, more complex cryogenic units which require considerably more maintenance because of the cryogenic refrigeration system employed. The amplifier can be located up to 15 feet from the power supply unit. Optimum performance was achieved through the use of high-quality unpackaged (chip) varactors in the amplifier design.

Kramer, E.↗
NASA NTRS1974

Applications Technology Satellite 6 - Upgrading the life style of millions of people

The primary objective of the ATS-6 is to demonstrate the feasibility of operating a high-powered geosynchronous communications satellite capable of relaying color TV and other high-quality signals on multiple frequencies to relatively simple and inexpensive ground receivers. Other capabilities include providing a link between ships, aircraft, or other earth satellites (e.g., low-orbit meteorological satellites) and the ground. The ATS-6 flight-objective accomplishments and subsystem performance for its first 30 days in orbit are summarized. Success is predicted for most of the experiments carried.

Thole, J. M.↗