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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Structural Analysis of the QCM Aboard the ER-2

As a result of recent supersonic transport (SST) studies on the effect they may have on the atmosphere, several experiments have been proposed to capture and evaluate samples of the stratosphere where SST's travel. One means to achieve this is to utilize the quartz crystal microbalance (QCM) installed aboard the ER-2, formerly the U-2 reconnaissance aircraft. The QCM is a cascade impactor designed to perform in-situ, real-time measurements of aerosols and chemical vapors at an altitude of 60,000 - 70,000 feet. The ER-2 is primarily used by NASA for Earth resources to test new sensor systems before they are placed aboard satellites. One of the main reasons the ER-2 is used for this flight experiment is its capability to fly approximately twelve miles above sea level (can reach an altitude of 78,000 feet). Because the ER-2 operates at such a high altitude, it is of special interest to scientists interested in space exploration or supersonic aircraft. Some of the experiments are designed to extract data from the atmosphere around the ER-2. For the current flight experiment, the QCM is housed in a frame that is connected to an outer pod that is attached to the fuselage of the ER-2. Due to the location of the QCM within the housing frame and the location of the pod on the ER-2, the pod and its contents are subject to structural loads. In addition to structural loads, structural vibrations are also of importance because the QCM is a frequency induced instrument. Therefore, a structural analysis of the instrument within the frame is imperative to determine if resonance and/or undesirable deformations occur.

Jones, Phyllis D.↗
DOE OSTI2021

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗
DOE OSTI2020

Structural Transformation and Chemical Stability of a Shock-Compressed Insensitive High Explosive Single Crystal: Time-Resolved Raman Spectroscopy

Despite the considerable interest in insensitive high explosives (IHE) as a safer alternative to conventional high explosives, a good understanding of the low sensitivity of IHEs to shock initiation is lacking. In particular, real-time measurements to directly probe the molecular-level response of shock compressed IHE single crystals constitute an important need. To address this need, plate impact experiments were conducted to determine time-resolved changes in the Raman spectra of 1,1-diamino-2,2-dinitroethene (FOX-7) single crystals – a representative IHE crystal – shock compressed up to 20 GPa longitudinal stress. The Raman measurements examined vibrational frequencies from 800 cm-1 to 1500 cm-1 with 15 nanosecond time resolution and were conducted at several peak stresses. At 4 – 6 GPa, two new Raman peaks appeared, in addition to the original peaks, consistent with onset of the α' – ε structural transformation reported previously in static compression work. The measured spectra indicated completion of the transformation at 10 GPa. Raman data to 20 GPa showed neither additional transformations nor any indication of chemical decomposition. This finding, though consistent with recent continuum measurements, is in marked contrast to the chemical decomposition observed at lower stresses in shock compressed conventional high explosive single crystals. Our Raman results support the previous suggestion that strengthening of intra- and inter-molecular bonds, due to the α' – ε structural transformation, plays a significant role in the insensitivity of FOX-7 single crystals to shock initiation. In conclusion, the present work, in conjunction with previous static compression studies, provides the first experimental insight into the molecular-level response of a shock compressed IHE single crystal and can serve as a bench mark for theoretical studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine learning for automated experimentation in scanning transmission electron microscopy

Abstract Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows, as well as the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Line identification of boron and nitrogen emissions in EUV and VUV wavelength ranges in the impurity powder dropping experiments of LHD and its application to spectroscopic diagnostics

An impurity powder dropper was installed in the 21st campaign of the Large Helical Device experiment (Oct. 2019–Feb. 2020) under a collaboration between the National Institute for Fusion Science and the Princeton Plasma Physics Laboratory for the purposes of real-time wall conditioning and edge plasma control. In order to assess the effective injection of the impurity powders, spectroscopic diagnostics were applied to observe line emission from the injected impurity. Therefore, extreme-ultraviolet (EUV) and vacuum-ultraviolet (VUV) emission spectra were analyzed to summarize observable impurity lines with B and BN powder injection. Emission lines released from B and N ions were identified in the EUV wavelength range of 5–300 Å measured using two grazing incidence flat-field EUV spectrometers and in the VUV wavelength range of 300–2400 Å measured using three normal incidence 20 cm VUV spectrometers. BI–BV and NIII–NVII emission lines were identified in the discharges with the B and BN powder injection, respectively. Useful B and N emission lines which have large intensities and are isolated from other lines were successfully identified as follows: BI (1825.89, 1826.40) Å (blended), BII 1362.46 Å, BIII (677.00, 677.14, 677.16) Å (blended), BIV 60.31 Å, BV 48.59 Å, NIII (989.79, 991.51, 991.58) Å (blended), NIV 765.15 Å, NV (209.27, 209.31) Å (blended), NVI 1896.80 Å, and NVII 24.78 Å. Applications of the line identifications to the advanced spectroscopic diagnostics were demonstrated, such as the vertical profile measurements for the BV and NVII lines using a space-resolved EUV spectrometer and the ion temperature measurement for the BII line using a normal incidence 3 m VUV spectrometer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

FPV Video Adaptation for UAV Collision Avoidance

First person view (FPV) technology for unmanned aerial vehicles (UAVs) provides an immersive experience for pilots and enables various personal and commercial applications such as aerial photography, drone racing, search and rescue operations, agricultural surveillance, and structural inspection. While real time video streaming from a UAV and vision-based collision avoidance strategies have been studied in literature as separate topics, in this paper we tackle collision avoidance in FPV scenarios, taking into account network delays and real time video parameters. We present a theoretical model for obstacle collisions that considers the current communication channel conditions, the real time video parameters, and the UAV's position relative to the closest obstacle. A video adaptation algorithm is then designed, using this metric, to tune the FPV video resolution, number of re-transmission attempts, and the modulation scheme to maximize the probability of avoiding collisions. This algorithm also takes into account specific latency constraints of the application. This video algorithm was evaluated in various scenarios and its ability to respond to both distances to the obstacle as well as the communication channel conditions was demonstrated. It was found that, for the considered scenarios, the performance of the proposed adaptive algorithm was, on an average, 58.63% higher than the closest non-adaptive one in terms of maximizing the probability of avoiding collision. Such collision avoidance strategies could be used to make UAV FPV applications safer and more reliable.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Control and Real-Time Simulation of Microgrids with EV Fast-Charging and Grid-Forming Resources

Fast charging stations (FCSs) for electric vehicles (EVs) can behave as constant power loads, which is problematic for the operation of grid-forming (GFM) inverter-based resources (IBRs). To tackle this problem, this paper proposes a control suite that makes FCSs responsive to ac voltage and frequency disturbances. To test the performance of the FCS controls, the paper also sets forth theory to compensate for time-delays appearing in the real-time simulation of microgrid models divided into several central processing units (CPUs). Furthermore, these contributions are showcased via multi-CPU real-time simulations of a faulted microgrid having EV FCSs and GFM IBRs powered by photovoltaic solar arrays as well as power hardware-in-the-loop experiments. These contributions are significant to address NERC recommendations and IEEE standards.

14 SOLAR ENERGY↗
DOE OSTI2021

Challenges and Potential of Waveform Modeling for Crustal Scale Predictions

Waveform modeling is crucial to improving our understanding of observed seismograms. Forward simulation of wavefields provides quantitative methods of testing interactions between complicated source functions and the propagation medium. Here, we discuss three experiments designed to improve under standing of high frequency seismic wave propagation. First, we compare observed and predicted travel times of crustal phases for a set of real observed earthquakes with calculations and synthetic seismograms. Second, we estimate the frequency content of a series of nearly co-located earthquakes of varying magnitude for which we have a relatively well- known 1D velocity model. Third, we apply stochastic perturbations on top of a 3D tomographic model and qualitatively assess how those variations map to differences in the seismograms. While different in scope and aim, these three vignettes illustrate the current state of crustal scale waveform modeling and the potential for future studies to better constrain the structure of the crust.

58 GEOSCIENCES↗
DOE OSTI2025

Enhanced H 2 production from subsurface through organic acids stimulation Report

Geologic hydrogen (H 2 ) generation through serpentinization of ultramafic rocks presents a promising alternative to conventional hydrogen production, utilizing Earth's abundant magnesium- and iron-rich minerals. This study explores the use of short-chain organic acids (specifically malic acid, MA; and citric acid, CA) to enhance hydrogen yields by stimulating mineral dissolution and iron oxidation from ultramafic rock samples. Batch experiments were conducted with crushed peridotite samples from the Tamarack Complex (Minnesota) and Del Puerto Ophiolite (California). Experiments employed 0.05 M and 0.1 M solutions of MA or CA, under 500 psi (35 bar) nitrogen pressure, at temperatures up to 150 °C. Real-time gas monitoring, aqueous chemistry and solid-phase analyses were performed to track reaction progress and hydrogen production.

08 HYDROGEN↗
DOE OSTI2025

Enhanced H 2 production from subsurface through organic acids stimulation

Geologic hydrogen (H₂) generation through serpentinization of ultramafic rocks presents a promising alternative to conventional hydrogen production, utilizing Earth's abundant magnesium- and iron-rich minerals. This study explores the use of short-chain organic acids (specifically malic acid, MA; and citric acid, CA) to enhance hydrogen yields by stimulating mineral dissolution and iron oxidation from ultramafic rock samples. Batch experiments were conducted with crushed peridotite samples from the Tamarack Complex (Minnesota) and Del Puerto Ophiolite (California). Experiments employed 0.05 M and 0.1 M solutions of MA or CA, under 500 psi (35 bar) nitrogen pressure, at temperatures up to 150 °C. Real-time gas monitoring, aqueous chemistry and solid-phase analyses were performed to track reaction progress and hydrogen production.

08 HYDROGEN↗
DOE OSTI2021

A New Field Instrument for Leaf Volatiles Reveals an Unexpected Vertical Profile of Isoprenoid Emission Capacities in a Tropical Forest

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m -2 leaf s -1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

MOSS, an evaluation of software engineering techniques

An evaluation of the software engineering techniques used for the development of a Modular Operating System (MOSS) was described. MOSS is a general purpose real time operating system which was developed for the Concept Verification Test (CVT) program. Each of the software engineering techniques was described and evaluated based on the experience of the MOSS project. Recommendations for the use of these techniques on future software projects were also given.

Bounds, J. R.↗
NASA NTRS1976

A combined boundary-profile and automated data-reduction and analysis system

A portable boundary-layer meteorological data-acquisition and analysis system is described which employs a small tethered balloon and a programmable calculator. The system is capable of measuring pressure, wet- and dry-bulb temperature, wind speed, and temperature fluctuations as a function of height and time. Other quantities, which can be calculated in terms of these, can also be made available in real time. All quantities, measured and calculated, can be printed, plotted, and stored on magnetic tape in the field during the data-acquisition phase of an experiment.

Deloach, R.↗
NASA NTRS1985

The AMPTE IRM Science Data Center

The creation of artificial ion clouds is a major aspect of the AMPTE program. The IRM Science Data center supports real-time decision for a release with real-time scientific data processing and display including model calculations of ion trajectories. Additionally, survey plots and summary data records are generated in near real time thus allowing to start the data analysis as early as possible. For detailed analyses, interactive programs were developed so that physical parameters of all IRM experiments can be combined to produce common spectra or line plots.

Bauer, O. H.↗
NASA NTRS1990

Applications of ISES for vegetation and land use

Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management.

Wilson, R. Gale↗
NASA NTRS1990

Low-dimensional modelling and prediction in fluid dynamics

Research into the development of a simplified, low-dimensional, state-variable model for a fluid dynamics system is discussed. The model would be capable of predicting the state of the system in as nearly real time as possible and would be suitable for implementation in a control loop. It is noted that state-variable modeling has an advantage for real-time health monitoring and control application over the Navier-Stokes equations since the latter require an enormous amount of real time. In this study, a dynamic procedure is developed for modeling and prediction using the CFD data generated for this model centerbody-combustor configuration. Some experiences with the NASA data available for the SSME are also reported. Application of this procedure to pressure and velocity measurements in an actual wind-tunnel experiment is described, and the applicability of the approach to health monitoring is considered.

Ghia, U.↗
NASA NTRS1999

Autonomous Science Analyses of Digital Images for Mars Sample Return and Beyond

To adequately explore high priority landing sites, scientists require rovers with greater mobility. Therefore, future Mars missions will involve rovers capable of traversing tens of kilometers (vs. tens of meters traversed by Mars Pathfinder's Sojourner). However, the current process by which scientists interact with a rover does not scale to such distances. A single science objective is achieved through many iterations of a basic command cycle: (1) all data must be transmitted to Earth and analyzed; (2) from this data, new targets are selected and the necessary information from the appropriate instruments are requested; (3) new commands are then uplinked and executed by the spacecraft and (4) the resulting data are returned to Earth, starting the process again. Experience with rover tests on Earth shows that this time intensive process cannot be substantially shortened given the limited data downlink bandwidth and command cycle opportunities of real missions. Sending complete multicolor panoramas at several waypoints, for example, is out of the question for a single downlink opportunity. As a result, long traverses requiring many science command cycles would likely require many weeks, months or even years, perhaps exceeding rover design life or other constraints. Autonomous onboard science analyses can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands, for example acquiring and returning spectra of "interesting" rocks along with the images in which they were detected. Such approaches, coupled with appropriate navigational software, address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing algorithms to enable such intelligent decision making by autonomous spacecraft. Reflecting the ultimate level of ability we aim for, this program has been dubbed the "Grad Student on Mars Project". We envision, for example, an appropriately intelligent Athena-like rover at the Pathfinder landing site might be able to traverse over the ridge towards "Twin Peaks" to obtain better information on the stratigraphy of these "streamlined islands" or of the size, composition and morphology of boulders located on them. Along the traverse, the intelligent rover would collect and analyze images and obtain spectra of geologically interesting features or regions. The intelligent rover might also traverse further up Arcs Vallis, and find additional paleoflood stage indicators such as slackwater deposits. Recognizing additional regions where boulders are imbricated, noting changes in their size, distribution, morphology, composition and the associated changes in channel geometry would yield important information on the outflow channel's paleoflood history, Representative images and associated supporting data from these locations could be downlinked to Earth along with the data requested by scientists from the previous uplink opportunity. Our initial work has focused on recognizing geologically interesting portions of images. Here we summarize some of the algorithms to date.

Gulick, V. C.↗
NASA NTRS1998

A New Optical Aerosol Spectrometer

An optical particle spectrometer capable of measuring aerosol particle size distributions from 0.02 to 100 micrometers has been developed. This instrument combines several optical methods in one, in-situ configuration; it can provide continuous data collection to encompass the wide dynamic size ranges and concentrations found in studies of modeled planetary atmospheres as well as terrestrial air quality research. Currently, the system is incorporated into an eight liter capacity spherical pressure vessel that is appropriate both for flowthrough and for in-situ particle generation. The optical sizing methods include polarization ratio, The scattering, and forward scattering detectors, with illumination from a fiber-coupled, Argon-ion laser. As particle sizes increase above 0.1 micrometer, a customized electronics and software system automatically shifts from polarization to diffraction-based measurements as the angular scattering detectors attain acceptable signal-to-noise ratios. The number concentration detection limits are estimated to be in the part-per-trillion (ppT by volume) range, or roughly 1000 submicron particles per cubic centimeter. Results from static experiments using HFC134A (approved light scattering gas standard), flow-through experiments using sodium chloride (NaCl) and carbon particles, and dynamic 'Tholin' (photochemical produced particles from ultraviolet (UV)-irradiated acetylene and nitrogen) experiments have been obtained. The optical spectrometer data obtained with particles have compared well with particle sizes determined by electron microscopy. The 'Tholin' tests provided real-time size and concentration data as the particles grew from about 30 nanometers to about 0.8 micrometers, with concentrations ranging from ppT to ppB, by volume. Tests are still underway, to better define sizing accuracy and concentration limits, these results will be reported.

Fonda, Mark↗