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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS1961

Analysis of X-15 Landing Approach and Flare Characteristics Determined from the First 30 Flights

The approach and flare maneuvers for the first 30 flights of the X-15 airplane and the various control problems encountered are discussed. The results afford a relatively good cross section of landing conditions that might be experienced with future glide vehicles having low lift-drag ratios. Flight-derived drag data show that preflight predictions based on wind-tunnel tests were, in general, somewhat higher than the values measured in flight. Depending on configuration, the peak lift-drag ratios from flight varied from 3.5 to 4.5 as compared with a predicted range of from 3.0 to 4.2. By employing overhead, spiral-type patterns beginning at altitudes as high as 40,000 feet, the pilots were consistently able to touch down within about +/-1,000 feet of a designated point. A typical flare was initiated at a "comfortable" altitude of about 800 feet and an indicated airspeed of approximately 300 knots., which allowed a margin of excess speed. The flap and gear were extended when the flare was essentially completed, and an average touchdown was accomplished at a speed of about 185 knots indicated airspeed, an angle of attack of about 7 deg, and a rate of descent of about 4 feet per second. In general, the approach and landing characteristics were predicted with good accuracy in extensive preflight simulations. F-104 airplanes which simulated the X-15 landing characteristics were particularly valuable for pilot training.

Matranga, Gene J.↗
NASA NTRS1998

The Isothermal Dendritic Growth Experiment

The growth of dendrites is one of the commonly observed forms of solidification encountered when metals and alloys freeze under low thermal gradients, as occurs in most casting and welding processes. In engineering alloys, the details of the dendritic morphology directly relates to important material responses and properties. Of more generic interest, dendritic growth is also an archetypical problem in morphogenesis, where a complex pattern evolves from simple starting conditions. Thus, the physical understanding and mathematical description of how dendritic patterns emerge during the growth process are of interest to both scientists and engineers. The Isothermal Dendritic Growth Experiment (IDGE) is a basic science experiment designed to measure, for a fundamental test of theory, the kinetics and morphology of dendritic growth without complications induced by gravity-driven convection. The IDGE, a collaboration between Rensselaer Polytechnic Institute, in Troy NY, and NASA's Lewis Research Center (LeRC) was developed over a ten year period from a ground-based research program into a space flight experiment. Important to the success of this flight experiment was provision of in situ near-real-time teleoperations during the spaceflight experiment.

Glicksman, M. E.↗
NASA NTRS1968

Noise Considerations for V/STOL Transports

Noise consideration may well be as important a factor in future aircraft concept selection as such economic factors as operating cost and profitability. The impact of noise on some of the design and operational aspects of future V/STOL transports is examined in detail, including consideration of configuration, attitude-control system, lift system, and terminal flight pattern. Extended vertical rise of VTOL aircraft as a method of limiting the intense noise exposure to the terminal area is shown to be only partially effective as well as costly. Comparisons are made of noise contours for conceptual V/STOL transports for several PNdB criteria. The variation in extent of affected area with configuration and criterion emphasizes the importance of establishing an "acceptable" noise level for "city-center" operation.

Kenyon, George C.↗
NASA NTRS2004

Fabrication of MEMS-Based Microshutter Arrays for Optical Transmission Selection

A MEMS-based programmable aperture mask is under development at the NASA Goddard Space Flight Center. Termed the Microshutter (u-shutter) Array, the device will be used to control the transmission of light, with both high efficiency and contrast, to a multi-object spectrometer on the James Webb Space Telescope. Fabrication of the p-shutter array employs several novel designs and processing techniques. The current generation of micro-shutters consists of 128x64 pixel arrays with unit cell dimensions of 100x200 microns. Shutters are patterned in silicon nitride and sit on a 100 micron silicon frame that is DRIE etched below each shutter. The front and back sides of the device are shown. A magnetic cobalt-iron alloy patterned on top of the shutter allows it to be actuated 90 degrees out-of-plane, into the frame, by an external magnetic field. An electrode on the shutter and a vertical electrode on the sidewall of the frame, approximately 90pm deep, allow them to be electrostatically latched in their rotated position. The vertical electrode is deposited and patterned on the backside of the frame in a single step using a directionally controlled evaporation. Individual addressing of shutters for electrostatic latching is accomplished via a crosspoint addressing scheme, with no on-chip active components. A portion of an array with shutters in the open, latched, and closed positions is shown. Light loss at shutter edges is minimized by an overhanging aluminum light-shield that is anchored to the frame. A photoresist sacrificial layer is used to raise the light-shield up and over the 2 micron gap that surrounds each pixel. After completion, arrays are subjected to life cycle, environmental and optical testing. Fabricated devices have survived 10(exp 6) actuation cycles at both room and cryogenic temperatures and a 14g rms launch-simulation test. Optical testing has shown contrast measurements between open and closed shutters up to 10000:1.

Lynch, Bernard A.↗
NASA NTRS2016

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

balloons - instrumentation: detectors - techniques↗
NASA NTRSDate not supplied

Lunar Excavator Mission Operations using Dynamic Movement Primitives

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

Space Robotics and Automation↗
NASA NTRS2021

A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion

Dense time-series remote sensing data with detailed spatial information are highly desired for the monitoring of dynamic earth systems. Due to the sensor tradeoff, most remote sensing systems cannot provide images with both high spatial and temporal resolutions. Spatiotemporal image fusion models provide a feasible solution to generate such a type of satellite imagery, yet existing fusion methods are limited in predicting rapid and/or transient phenological changes. Additionally, a systematic approach to assessing and understanding how varying levels of temporal phenological changes affect fusion results is lacking in spatiotemporal fusion research. The objective of this study is to develop an innovative hybrid deep learning model that can effectively and robustly fuse the satellite imagery of various spatial and temporal resolutions. The proposed model integrates two types of network models: super-resolution convolutional neural network (SRCNN) and long short-term memory (LSTM). SRCNN can enhance the coarse images by restoring degraded spatial details, while LSTM can learn and extract the temporal changing patterns from the time-series images. To systematically assess the effects of varying levels of phenological changes, we identify image phenological transition dates and design three temporal phenological change scenarios representing rapid, moderate, and minimal phenological changes. The hybrid deep learning model, alongside three benchmark fusion models, is assessed in different scenarios of phenological changes. Results indicate the hybrid deep learning model yields significantly better results when rapid or moderate phenological changes are present. It holds great potential in generating high-quality time-series datasets of both high spatial and temporal resolutions, which can further benefit terrestrial system dynamic studies. The innovative approach to understanding phenological changes’ effect will help us better comprehend the strengths and weaknesses of current and future fusion models.

spatiotemporal fusion↗
DOE OSTI2024

System Modeling of Frost/Defrost Cycles in Heat Pumps

Accurately modeling frost/defrost cycles is crucial for guiding heat exchanger design, appropriately sizing the compressor, and quantifying seasonal energy consumption for heating. While previous modelling studies of frosting cycle have predominantly focused on the component level of fin-and-tube coils, there has been limited development of models for system defrosting cycles. This study enhances the existing knowledge by improving a detailed, segment-to-segment heat exchanger model to simulate frost/defrost cycles for both fin-and-tube coils and microchannel heat exchangers. Furthermore, it integrates this component-level model into a steady-state/quasi-steady-state system modeling framework to simulate complete frost/defrost processes, i.e. the ORNL Heat Pump Design Model (HPDM). This comprehensive approach will unveil differences in coil types, and their interactions with the outdoor fan. It will also predict energy consumption patterns and time intervals associated with these processes.

Shen, Bo↗
DOE OSTI2024

The Effect of Luminance Pattern on Nighttime Discomfort Glare Response - CRADA 653 (Abstract)

Light Emitting Diode (LED) adoption is critical for widespread energy savings from commercial outdoor lighting systems. A complaint from the public, concerns glare from LED light fixtures especially those with exposed LED arrays. This human factor study will examine luminance uniformity of the fixture aperture to identify parameters related to this response. The outcome will inform optical design by lighting manufacturers, retaining LED energy efficiency while mitigating glare. The results may also lead to improved industry standard glare metrics for lighting. Pacific Northwest National Laboratory’s (PNNL) Lighting Science and Technology Lab in Portland OR has a purpose-built apparatus with exposed LED arrays that have been used for prior work. It can easily be adapted for use in this experiment. Interchangeable templates will allow changing patterns for the stimulus. Glare ratings from the recruited subjects will be analyzed and reported in a peer-reviewed journal for application by luminaire manufacturers for improved products. The McClung Foundation’s interest is to better understand human perception of lighting, leading to more comfortable and effective visual environments. Members of the Foundation’s Technical Review Committee will be instrumental in reviewing the experimental design, analysis, and the final report. They will also help disseminate information about the results within the lighting community.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Inverse design of pore wall chemistry and topology through active learning of surface group interactions

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. Furthermore, this proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Spatiotemporal Sequence Forecasting Platform to Advance the Prediction of Changing Spatiotemporal Patterns of CO 2 Concentration by Incorporating Human Activity and Hydrological Extremes

Focal Areas (2): Predictive modeling using AI techniques and AI-derived model components. It describes the use of AI and other tools to design a prediction system comprising a hierarchy of models. Specifically, this white paper focuses on the development of a collaborative deep learning platform for evaluating and predicting spatiotemporal relationships between the hydrological and carbon cycles and includes capabilities for considering biogenic and anthropogenic inputs to these systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Predominance of two-armed spirals

A physical process accounts for the origin and widespread occurrence of two-armed spiral patterns with a high degree of symmetry extending from the nucleus to the outermost part of a galaxy. Self-gravitating systems, starting from a wide variety of initial conditions, settle down into twofold symmetries through a sequence of forms that were identified in numerical experiments. Twofold symmetries rarely develop directly. Instead, the systems pass through a sequence of more complicated shapes. The computer experiments and the sequence leading to twofold symmetries are described. At the end of this process, a two-armed spiral density wave with a 'grand design' has been set up in the galaxy, and the stage has been set for some mechanism, such as that of Lin and Shu (1971), to take over to assure a long lifetime for the pattern.

Miller, R. H.↗
NASA NTRS1999

Non-Intrusive Laser-Induced Imaging for Speciation and Patternation in High Pressure Gas Turbine Combustors

The next generation of was turbine combustors for aerospace applications will be required to meet increasingly stringent constraints on fuel efficiency, noise abatement, and emissions. The power plants being designed to meet these constraints will operate at extreme conditions of temperature and pressure, thereby generating unique challenges to the previously employed diagnostic methodologies. Current efforts at NASA Glenn Research Center (GRC) utilize optically accessible, high pressure flametubes and sector combustor rigs to probe, via advanced nonintrusive laser techniques, the complex flowfields encountered in advanced combustor designs. The fuel-air mixing process is of particular concern for lowering NO(x) emissions generated in lean, premixed engine concepts. Using planar laser-induced fluorescence (PLIF) we have obtained real-time, detailed imaging of the fuel spray distribution for a number of fuel injector over a wide range of operational conditions that closely match those expected in the proposed propulsion systems. Using a novel combination of planar imaging, of fuel fluorescence and computational analysis that allows an examination of the flowfield from any perspective, we have produced spatially and temporally resolved fuel-air distribution maps. These maps provide detailed insight into the fuel injection at actual conditions never before possible, thereby greatly enhancing the evaluation of fuel injector performance and combustion phenomena.

Locke, Randy J.↗
DOE OSTI2024

Perspectives and progress on wurtzite ferroelectrics: Synthesis, characterization, theory, and device applications

Wurtzite ferroelectrics are an emerging material class that expands the functionality and application space of wide bandgap semiconductors. Promising physical properties of binary wurtzite semiconductors include a large, reorientable spontaneous polarization, direct band gaps that span from the infrared to ultraviolet, large thermal conductivities and acoustic wave velocities, high mobility electron and hole channels, and low optical losses. The ability to reverse the polarization in ternary wurtzite semiconductors at room temperature enables memory and analog type functionality and quasi-phase matching in optical devices and boosts the ecosystem of wurtzite semiconductors, provided the appropriate combination of properties can be achieved for any given application. In this article, advances in the design, synthesis, and characterization of wurtzite ferroelectric materials and devices are discussed. Highlights include: the direct and quantitative observation of polarization reversal of ~135 μC/cm 2 charge in Al 1-x B x N via electron microscopy, Al 1-x B x N ferroelectric domain patterns poled down to 400 nm in width via scanning probe microscopy, and full polarization retention after over 1000 h of 200 °C baking and a 2× enhancement relative to ZnO in the nonlinear optical response of Zn 1-x Mg x O. In conclusion, the main tradeoffs, challenges, and opportunities in thin film deposition, heterostructure design and characterization, and device fabrication are overviewed.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1992

Optical pattern recognition III; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

Consideration is given to transitioning of optical processing into systems (TOPS), optical correlator hardware, phase-only optical correlation filters, optical distortion-invariant correlation filters, and optical neural networks. Particular attention is given to a test target for optical correlators, a TOPS electronic warfare channelizer program, a portable video-rate optical correlator, a joint transform correlator employing electron trapping materials, a novelty filtered optical correlator using a photorefractive crystal, a comparison of correlation performance of smart ternary phase-amplitude filters with gray-scale and binary input scenes, real-time distortion-tolerant composite filters for automatic target identification, landscaping the correlation surface, fast designing of a circular harmonic filter using simulated annealing, feature-based correlation filters for distortion invariance, automatic target recognition using a feature-based optical neural network, and a holographic inner-product processor for pattern recognition.

Casasent, David P.↗
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↗
NASA NTRS1979

Wind study for high altitude platform design

An analysis of upper air winds was performed to define the wind environment at potential operating altitudes for high altitude powered platform concepts. Wind conditions of the continental United States, Pacific area (Alaska to Sea of Japan), and European area (Norwegian and Mediterranean Sea) were obtained using a representative network of sites selected based upon adequate high altitude sampling, geographic dispersion, and observed upper wind patterns. A data base of twenty plus years of rawinsonde gathered wind information was used in the analysis. Annual variations from surface to 10 mb pressure altitude were investigated to encompass the practical operating range for the platform concepts. Parametric analysis for the United States and foreign areas was performed to provide a basis for vehicle system design tradeoffs. This analysis of wind magnitudes indicates the feasibility of annual operation at a majority of sites and more selective seasonal operation for the extreme conditions between the pressure altitudes of 100 to 25 mb based upon the assumed design speeds.

High altitude powered platform studies↗
NASA NTRS2010

FPGA Coprocessor Design for an Onboard Multi-Angle Spectro-Polarimetric Imager

A multi-angle spectro-polarimetric imager (MSPI) is an advanced camera system currently under development at JPL for possible future consideration on a satellite-based Aerosol-Cloud-Environ - ment (ACE) interaction study. The light in the optical system is subjected to a complex modulation designed to make the overall system robust against many instrumental artifacts that have plagued such measurements in the past. This scheme involves two photoelastic modulators that are beating in a carefully selected pattern against each other. In order to properly sample this modulation pattern, each of the proposed nine cameras in the system needs to read out its imager array about 1,000 times per second. The onboard processing required to compress this data involves least-squares fits (LSFs) of Bessel functions to data from every pixel in realtime, thus requiring an onboard computing system with advanced data processing capabilities in excess of those commonly available for space flight. As a potential solution to meet the MSPI onboard processing requirements, an LSF algorithm was developed on the Xilinx Virtex-4FX60 field programmable gate array (FPGA). In addition to configurable hardware capability, this FPGA includes Power -PC405 microprocessors, which together enable a combination hardware/ software processing system. A laboratory demonstration was carried out based on a hardware/ software co-designed processing architecture that includes hardware-based data collection and least-squares fitting (computationally), and softwarebased transcendental function computation (algorithmically complex) on the FPGA. Initial results showed that these calculations can be handled using a combination of the Virtex- 4TM Power-PC core and the hardware fabric.

Pingree, Paula J.↗