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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 199 records · Page 11

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗

U.S. national report to the International Union of Geodesy and Geophysics

This paper highlights progress by U.S. authors during 1983-1986 in the broad area of auroral research. Atmospheric emissions and their use as a tool for remote-sensing the dynamics, energetics, and effects of auroral activity is a subject which is emphasized here because of the vast progress made in this area on both observational and theoretical fronts. The evolution of primary auroral electrons, the acceleration of auroral ions, small-scale electric fields, auroral kilometric radiation, auroral empirical models and activity indices are also reviewed. An extensive bibliography is supplied.

Gorney, D. J.↗

Utilization of space resources in the space transportation system

Utilization of space resources (i.e., raw materials obtained from nonterrestrial sources) has often been cited as a prerequisite for large-scale industrialization and habitation of space. While transportation of extremely large quantities of material from Earth would be costly and potentially destructive to our environment, vast quantities of usable resources might be derived from the Moon, the asteroids, and other celestial objects in a cost-effective and environmentally benign manner. The primary purpose of the parametric cost model developed as part of this study is to identify the factors that have the greatest influence on the economics of space resource utilization. In the near term, this information can be used to devise strategies for technology development so that capabilities developed will produce cost-effective results.

Simon, Michael C.↗

Severe storms requirements for precipitation information

Moisture can play an important if not dominant role in supplying energy to tropical and extra-tropical weather systems. In the tropics where the air is almost saturated only the slightest amount of uplift is required to initiate the release of vast amounts of latent heat to fuel systems as diverse as convective cloud clusters and hurricanes. The role of latent heating on extra-tropical systems is much more subtle. While the primary energy source for synoptic-scale systems is often the release of gravitational potential energy through the sinking of cold air and the rising of warm, it seems that the latent heat that is eventually realized through slow uplift of large masses of air can significantly modify the evolution of the system. An analysis of the energetics of the storm of March 25 to 27, 1978 over the eastern USA to understand the implications of the heat released due to the vast cloudy area associated with warm frontal overrunning was performed.

Adler, R. F.↗

Recent progress in VSTOL technology

Progress in vertical and short takeoff and landing (V/STOL) aircraft technology, in particular, during the 1970 to 1980 period at Ames Research Center is discussed. Although only two kinds of V/STOL aircraft (the helicopter and the British direct lift Harrier) have achieved operational maturity, understanding of the technology has vastly improved during this 10 year period. To pursue an aggressive R and D program at a reasonable cost, it was decided to conduct extensive large scale testing in wind tunnel and flight simulation facilities, to develop low cost research aircraft using modified airframes or engines, and to involve other agencies and industry contractors in joint technical and funding arrangements. The STOL investigations include exploring STOL performance using the rotating cylinder flap concept, the augmentor wing, upon initiation of the Quiet Short Haul Research Aircraft program, the upper surface blown flap concept. The VTOL investigations were conducted using a tilt rotor aircraft, resulting in the XV-15 tilt rotor research aircraft. Direct jet lift is now being considered for application to future supersonic fighter aircraft.

Roberts, L.↗

Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities

Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.

Quattrochi, Dale A.↗

Machine learning enabling high-throughput and remote operations at large-scale user facilities

Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher resolution, thus producing vast amounts of data for analysis. These innovations are particularly pronounced at user facilities and synchrotron light sources. Machine learning (ML) methods are regularly developed to process and interpret large datasets in real-time with measurements. However, there remain conceptual barriers to entry for the facility general user community, whom often lack expertise in ML, and technical barriers for deploying ML models. Herein, we demonstrate a variety of archetypal ML models for on-the-fly analysis at multiple beamlines at the National Synchrotron Light Source II (NSLS-II). We describe these examples instructively, with a focus on integrating the models into existing experimental workflows, such that the reader can easily include their own ML techniques into experiments at NSLS-II or facilities with a common infrastructure. The framework presented here shows how with little effort, diverse ML models operate in conjunction with feedback loops via integration into the existing Bluesky Suite for experimental orchestration and data management.

36 MATERIALS SCIENCE↗

Turbulence theories and statistical closure approaches

When discussing research in physics and in science more generally, it is common to ascribe equal importance to the three components of the scientific trinity: theoretical, experimental, and computational studies. This review will explore the future of modern turbulence theory by tracing its history, which began in earnest with Kolmogorov’s 1941 analysis of turbulence cascade and inertial range [A.N. Kolmogorov, Dokl. Akad. Nauk SSSR, 30, 299, (1941); 32, 19, (1941)]. The 80th Anniversary of Kolmogorov’s landmark study is a welcome opportunity to survey the achievements and evaluate the future of the theoretical approach of turbulence research. Over the years, turbulence theories have been critically important in laying the foundation of our understanding of the nature of turbulent flows. In particular, the Direct Interaction Approximation (DIA) [R.H. Kraichnan, J. Fluid Mech., 5, 497 (1959)] and its subsequent development, known as the statistical closure approach, can be identified as perhaps the most profound single advancement. The remarkable success of the statistical closure has furnished a platform to study such essential concepts as the energy transfer process and interacting scales, and the roles of the straining and sweeping motions. More recently, the quasi-Lagrangian formulation of V. L’vov & I. Procaccia and Kraichnan’s solvable passive scalar model provided powerful ways to explore another fundamental aspect of turbulent flows, the phenomena of intermittency, and the associated anomalous scaling exponents. In the meantime, the theory of fluid equilibria has been developed to describe the large-scale structures that can emerge from turbulent cascades of two-dimensional and geophysical flows at a later time. And yet, despite all these successes, analytical treatments suffer from mathematical complexities. As a result, the utility of theoretical approaches has been limited to relatively idealized flows. On the other hand, in recent decades, computational abilities and experimental facilities have reached an unprecedented scale. Looking beyond the horizon, the imminent deployment of exascale supercomputers will generate complete datasets of the entire flow field of key benchmark flows, allowing researchers to extract additional measurements concerning fully developed, complex turbulent flow fields far beyond those available from the statistical closure theories. Some other developments that could potentially influence the future course of turbulence theories include the advancement of machine learning, artificial intelligence, and data science; likely disruptions arising from the advent of quantum computation; and the increasingly prominent role of turbulence research in providing more accurate climate scientific data. Finally, turbulence theorists can leverage these developments by asking the right questions and developing advanced, sophisticated frameworks that will be able to predict and correlate vast amounts of data from the other two components of the trinity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adaptive pruning-based optimization of parameterized quantum circuits

Abstract Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by the difficulty of optimizing in the vast parameter space. In this work, we propose a heuristic optimization strategy for such ansatze used in variational quantum algorithms, which we call ‘parameter-efficient circuit training (PECT)’. Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms, in which each iteration of the algorithm activates and optimizes a subset of the total parameter set. To update the parameter subset between iterations, we adapt the Dynamic Sparse Reparameterization scheme which was originally proposed for training deep convolutional neural networks. We demonstrate PECT for the Variational Quantum Eigensolver, in which we benchmark unitary coupled-cluster ansatze including UCCSD and k -UpCCGSD, as well as the Low-Depth Circuit Ansatz (LDCA), to estimate ground state energies of molecular systems. We additionally use a layerwise variant of PECT to optimize a hardware-efficient circuit for the Sycamore processor to estimate the ground state energy densities of the one-dimensional Fermi-Hubbard model. From our numerical data, we find that PECT can enable optimizations of certain ansatze that were previously difficult to converge and more generally can improve the performance of variational algorithms by reducing the optimization runtime and/or the depth of circuits that encode the solution candidate(s).

Physics↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE

The Random Ray Method (TRRM) is a recently developed approach to solving neutral particle transport problems based on the Method of Characteristics. While the method previously has been implemented only in closed-source or limited-functionality codes, this work describes its implementation in two open-source Monte Carlo codes: OpenMC and SCONE. The random ray implementations required small modifications to the existing Multigroup Monte Carlo (MGMC) solvers, offering a rare venue for redundant, fine-grained, "apples-to-apples" speed and accuracy comparisons between transport methods. To this end, TRRM and MGMC solvers are evaluated against each other using each code's native capabilities on reactor eigenvalue problems with different degrees of energy discretization. On the C5G7 benchmark (featuring only seven energy groups), TRRM achieves a maximum pin power error comparable to or lower than that of MGMC for a given run time. On a problem with 69 energy groups, MGMC is found to scale more efficiently, obtaining a lower pin power error for a given run time. However, the defining difference between the two transport methods is found to be their vastly different uncertainty distributions. Specifically, TRRM is found to maintain similar levels of accuracy and uncertainty throughout the simulation domain whereas MGMC can exhibit orders-of-magnitude greater errors in areas of the problem that feature low neutron flux. For instance, TRRM provided an up to 373 times speed advantage compared with MGMC for computing the flux in low-flux regions in the moderator surrounding the C5G7 core.

42 ENGINEERING↗

Combinatorial Evaluation of Physical Feature Engineering, Classical Machine Learning, and Deep Learning Models for Synchrophasor Data at Scale

A major objective of the project was to train and evaluate the effectiveness of multiple event and anomaly detection, identification and classification deep temporal learning models for processing of real-time phasor measurement unit (PMU) data streams. A vast dataset, consisting of two years of phasor measurements from all three U.S. Interconnections, was curated and released by the Department of Energy (DOE) through Pacific Northwest National Laboratory (PNNL). The dataset also included an event log that provided event times and types (e.g. generator trips, line trips, planned service events, transformer operations, etc.). Our analysis of this dataset addressed six (6) of the eleven (11) research priorities identified in Funding Opportunity Announcement (FOA) DE-FOA-0001861 “Big Data Analysis of Synchrophasor Data” (FOA 1861). Rather than being limited to pre-determined specific algorithms, this project relied on the uniquely structured, highly performant underlying time series database capabilities of the PredictiveGrid platform to assess the vast dataset utilizing a wide variety of algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Stereo Topography of the South Polar of Mar: Volatile Inventory and Mars Polar Landing Landing Site

Viking stereo images and topographic maps reveal that the south polar layered deposits of Mars are topographically complex and morphologically distinct from the north polar layered deposits. The dominant feature is a 500-km-wide topographic dome that rises 3 km above the surrounding plains. This dome underlies the residual ice cap but is at least 50% larger in area. Erosional scarps and terraces indicate that this dome was once more extensive and has undergone erosional retreat. Adjacent to the dome, layered deposits form a vast plateau 1-1.5 km high extending approximately 1000 km beyond and to one side of the residual south polar cap. This plateau is relatively flat at kilometer scales, although it is cut in places by troughs and depressions, which have locally steep scarps up to 2 km high and sloping up to roughly 10 deg. Contiguously flat kilometer-scale regions the size of the Mars Polar Lander (MPL) landing ellipse are present. These are in the form of plateaus 100-300 km wide and 1-2 km high. One of the largest of these plateaus has been proposed as a landing site for the Mars Polar Lander (MPL). The volume associated with the south polar layered deposits may be comparable to those of the layered deposits at the north pole. Although this doubles the current probable inventory of surface ice on Mars, it still falls far short of accounting for the inferred volume of water on Mars in the past.

Schenk, Paul M.↗

Ocean Energy for Ocean Worlds

Energy systems generating power from ocean waves, currents, tides, and thermal and salinity gradients are being developed to power oceanographic instrumentation and autonomous vehicles in Earth’s oceans. Exploration missions enabled or extended with in-situ energy harvesting on Earth may be similar to those on extra-terrestrial ocean worlds including mapping, biogeochemical sampling, acoustic monitoring, search for building blocks of life, and physical oceanographic characterization. With the addition of ocean energy available at the point of observation, data can be collected on larger spatial and temporal scales, enabling more comprehensive missions on other worlds. Power resource characteristics (e.g. current speed, variability) will similarly need to be assessed. Earth and extra-terrestrial ocean missions share vast technical challenges including high expense, need for advanced autonomy, ability to survive in the harshest environments, and limited communications or opportunities for intervention. Marine energy systems may be the only option for in-situ generation in certain scenarios (e.g., under a thick layer of ice) or advantageous over onboard energy storage options that may interfere with the natural environment (e.g., radioisotope thermoelectric generators). This work provides an overview of existing marine energy technology pertaining to ocean observations, highlights emerging research and development and new funding and program initiatives, explores similarities in mission requirements between terrestrial and extra-terrestrial applications, and suggests innovation pathways towards enabling high-value ocean world exploration powered by ocean energy.

Cavagnaro, Robert J.↗

An Experimental Study of the Fluid Mechanics Associated With Porous Walls

The fluid mechanics of air exiting from a porous material is investigated. The experiments are filter rating dependent, as porous walls with filter ratings differing by about three orders of magnitude are studied. The flow behavior is investigated for its spatial and temporal stability. The results from the investigation are related to jet behavior in at least one of the following categories: (1) jet coalescence effects with increasing flow rate; (2) jet field decay with increasing distance from the porous wall; (3) jet field temporal turbulence characteristics; and (4) single jet turbulence characteristics. The measurements show that coalescence effects cause jet development, and this development stage can be traced by measuring the pseudoturbulence (spatial velocity variations) at any flow rate. The pseudoturbulence variation with increasing mass flow reveals an initial increasing trend followed by a leveling trend, both of which are directly proportional to the filter rating. A critical velocity begins this leveling trend and represents the onset of fully developed jetting action in the flow field. A correlation is developed to predict the onset of fully developed jets in the flow emerging from a porous wall. The data further show that the fully developed jet dimensions are independent of the filter rating, thus providing a length scale for this type of flow field (1 mm). Individual jet characteristics provide another unifying trend with similar velocity decay behavior with distance; however, the respective turbulence magnitudes show vast differences between jets from the same sample. Measurements of the flow decay with distance from the porous wall show that the higher spatial frequency components of the jet field dissipate faster than the lower frequency components. Flow turbulence intensity measurements show an out of phase behavior with the velocity field and are generally found to increase as the distance from the wall is increased.

N Ramachandran↗

Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data

Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery.

Optical Flow↗

Repair of Sandwich Structure in Support of the Payload Adapter Fitting

As part of a program examining a composite payload adaptor fitting (PAF) for NASA’s Space Launch System (SLS), a repair study of impact damage and misdrilled holes was undertaken. At the beginning of this repair study, the PAF was baselined as a honeycomb sandwich structure with eight-ply quasi-isotropic, carbon-fiber-reinforced epoxy facesheets. Although the baseline configuration could change, the repair program presented herein is generic enough in nature such that it will apply to most sandwich configurations. The vast majority of loads experienced by this structure will be in-plane compression; thus, this repair study concentrates on the in-plane compression strength of representative sandwich structure specimens. The PAF is a truncated cone with a minimum diameter of about 170 inches at the top and a maximum diameter of about 335 inches at the bottom. While the launch vehicle hardware should be protected throughout its life on the ground, rogue events (or misdrilled holes) are still a possibility. This study is not meant to address large scale damage or damage to the part other than in the acreage (the uniform portion of the structure that does not consist of joints or other detailed areas), but address the most probable type of damages (small impacts and misdrilled holes) in the vast majority of the structure (the acreage).

Nettles, A. T.↗