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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Documentation for the machine-readable version of the Bright Star Catalogue

The machine-readable version of The Bright Star Catalogue, 4th edition, is described. In addition to the large number of newly determined fundamental data, such as photoelectric magnitudes, MK spectral types, parallaxes, and radial velocities, the new version contains data and information not included in the third edition such as the identification of IR sources, U-B and R-I colors, radial velocity comments (indication and identification of spectroscopic and occultation binaries), and projected rotational velocities. The equatorial coordinates for equinoxes 1900 and 2000 are recorded to greater precision details concerning variability, spectral characteristics, duplicity, and group membership are included. Data compiled through 1979, some information and variable-star designations found through 1981 are considered.

Warren, W. H., Jr.↗
NASA NTRS2011

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

anomaly detection↗
NASA NTRS2013

Compact Focal Plane Assembly for Planetary Science

A compact radiometric focal plane assembly (FPA) has been designed in which the filters are individually co-registered over compact thermopile pixels. This allows for construction of an ultralightweight and compact radiometric instrument. The FPA also incorporates micromachined baffles in order to mitigate crosstalk and low-pass filter windows in order to eliminate high-frequency radiation. Compact metal mesh bandpass filters were fabricated for the far infrared (FIR) spectral range (17 to 100 microns), a game-changing technology for future planetary FIR instruments. This fabrication approach allows the dimensions of individual metal mesh filters to be tailored with better than 10- micron precision. In contrast, conventional compact filters employed in recent missions and in near-term instruments consist of large filter sheets manually cut into much smaller pieces, which is a much less precise and much more labor-intensive, expensive, and difficult process. Filter performance was validated by integrating them with thermopile arrays. Demonstration of the FPA will require the integration of two technologies. The first technology is compact, lightweight, robust against cryogenic thermal cycling, and radiation-hard micromachined bandpass filters. They consist of a copper mesh supported on a deep reactive ion-etched silicon frame. This design architecture is advantageous when constructing a lightweight and compact instrument because (1) the frame acts like a jig and facilitates filter integration with the FPA, (2) the frame can be designed so as to maximize the FPA field of view, (3) the frame can be simultaneously used as a baffle for mitigating crosstalk, and (4) micron-scale alignment features can be patterned so as to permit high-precision filter stacking and, consequently, increase the filter bandwidth and sharpen the out-of-band rolloff. The second technology consists of leveraging, from another project, compact and lightweight Bi0.87Sb0.13/Sb arrayed thermopiles. These detectors consist of 30-layer thermopiles deposited in series upon a silicon nitride membrane. At 300 K, the thermopile arrays are highly linear over many orders of magnitude of incident IR power, and have a reported specific detectivity that exceeds the requirements imposed on future mission concepts. The bandpass filter array board is integrated with a thermopile array board by mounting both boards on a machined aluminum jig.

Brown, Ari↗
NASA NTRS1996

A Flexible Alignment Fixture for the Fabrication of Replication Mandrels

NASA uses precision diamond turning technology to fabricate replication mandrels for its X-ray Calibration Facility (XRCF) optics. The XRCF optics are tubular, and the internal surface contains a parabolic profile over the first section and a hyperbolic profile over the last. The optic is fabricated by depositing layers of gold and nickel on to the replication mandrel and then separating it from the mandrel. Since the mandrel serves as a replication form, it must contain the inverse image of the surface. The difficulty in aligning the mandrel comes from the fabrication steps which it undergoes. The mandrel is rough machined and heat treated prior to diamond turning. After diamond turning, silicon rubber separators which are undercut in radius by 3 mm (0.12 in.) are inserted between the two end caps of the mandrel to allow the plating to wrap around the ends (to prevent flaking). The mandrel is then plated with a nickel-phosphor alloy using an electroless nickel process. At this point, the separators are removed and the mandrel is reassembled for the final cut on the DTM. The mandrel is measured for profile and finish, and polished to achieve an acceptable surface finish. Wrapping the plating around the edges helps to prevent flaking, but it also destroys the alignment surfaces between the parts of the mandrel that insure that the axes of the parts are coincident. Several mandrels have been realigned by trial-and-error methods, consuming significant amounts of setup time. When the mandrel studied in this paper was reassembled, multiple efforts resulted in a minimum radial error motion of 100 microns. Since 50 microns of nickel plating was to be removed, and a minimum plating thickness of 25 microns was to remain on the part, the radial error motion had to be reduced to less than 25 microns. The mandrel was therefore not usable in its current state.

Cuttino, James F.↗
NASA NTRS2003

Microelectromechanical System (MEMS) Device Being Developed for Active Cooling and Temperature Control

High-capacity cooling options remain limited for many small-scale applications such as microelectronic components, miniature sensors, and microsystems. A microelectromechanical system (MEMS) using a Stirling thermodynamic cycle to provide cooling or heating directly to a thermally loaded surface is being developed at the NASA Glenn Research Center to meet this need. The device can be used strictly in the cooling mode or can be switched between cooling and heating modes in milliseconds for precise temperature control. Fabrication and assembly employ techniques routinely used in the semiconductor processing industry. Benefits of the MEMS cooler include scalability to fractions of a millimeter, modularity for increased capacity and staging to low temperatures, simple interfaces, limited failure modes, and minimal induced vibration. The MEMS cooler has potential applications across a broad range of industries such as the biomedical, computer, automotive, and aerospace industries. The basic capabilities it provides can be categorized into four key areas: 1) Extended environmental temperature range in harsh environments; 2) Lower operating temperatures for electronics and other components; 3) Precision spatial and temporal thermal control for temperature-sensitive devices; and 4) The enabling of microsystem devices that require active cooling and/or temperature control. The rapidly expanding capabilities of semiconductor processing in general, and microsystems packaging in particular, present a new opportunity to extend Stirling-cycle cooling to the MEMS domain. The comparatively high capacity and efficiency possible with a MEMS Stirling cooler provides a level of active cooling that is impossible at the microscale with current state-of-the-art techniques. The MEMS cooler technology builds on decades of research at Glenn on Stirling-cycle machines, and capitalizes on Glenn s emerging microsystems capabilities.

Beach, Duane E.↗
NASA NTRS2005

Gears Based on Carbon Nanotubes

Gears based on carbon nanotubes (see figure) have been proposed as components of an emerging generation of molecular- scale machines and sensors. In comparison with previously proposed nanogears based on diamondoid and fullerene molecules, the nanotube-based gears would have simpler structures and are more likely to be realizable by practical fabrication processes. The impetus for the practical development of carbon-nanotube- based gears arises, in part, from rapid recent progress in the fabrication of carbon nanotubes with prescribed diameters, lengths, chiralities, and numbers of concentric shells. The shafts of the proposed gears would be made from multiwalled carbon nanotubes. The gear teeth would be rigid molecules (typically, benzyne molecules), bonded to the nanotube shafts at atomically precise positions. For fabrication, it may be possible to position the molecular teeth by use of scanning tunneling microscopy (STM) or other related techniques. The capability to position individual organic molecules at room temperature by use of an STM tip has already been demonstrated. Routes to the chemical synthesis of carbon-nanotube-based gears are also under investigation. Chemical and physical aspects of the synthesis of molecular scale gears based on carbon nanotubes and related molecules, and dynamical properties of nanotube- based gears, have been investigated by computational simulations using established methods of quantum chemistry and molecular dynamics. Several particularly interesting and useful conclusions have been drawn from the dynamical simulations performed thus far: The forces acting on the gears would be more sensitive to local molecular motions than to gross mechanical motions of the overall gears. Although no breakage of teeth or of chemical bonds is expected at temperatures up to at least 3,000 K, the gears would not work well at temperatures above a critical range from about 600 to about 1,000 K. Gear temperature could probably be controlled by use of coolant gases. For a given application, the gears would work well at temperatures below the critical range, provided that the rotational energy was less than the energy required to tilt the teeth through an angle of 20 . The predominant mechanism of gear failure would be slippage caused by tilting of teeth. Gears would resume functioning if the slipping gears were decelerated sufficiently.

Jaffe, Richard↗
NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗
NASA NTRSDate not supplied

Space-Based Lidar Observations of the 3D Structure of the Earth System

Lidar provides precise measurements of the three-dimensional structure of the clouds, aerosols, ocean/land/snow/ice surfaces, as well as ocean subsurface. Lidar also provides unique information about physical propertiesof particulates in the atmosphere for both radiative transfer and air quality applications.In this talk, I will present an overview of our recent studies of aerosols, clouds, ocean and snow using space-based lidar measurements (e.g., LITE, CALIPSO and ICESat-2), such as classifications of aerosols and thermodynamics phase of clouds, cloud microphysical properties, snow depths and phytoplankton biomass. I will also introduce a new concept of 3D Earth system observations with data fusion though combined active/passive remote sensing and machine learning. The new concept aims to reveal vertical structure of the aerosols/clouds/surfaces/subsurface from passive sensors by taking advantage of lidar measurements to effectively resolve the vertical structureby unscrambling the highly convoluted multi-angle, spectral and polarization information from passive sensors and apply the knowledge to a large swath where lidar measurements are not available.

Ali Omar↗
NASA NTRS2024

Automatic Detection of Large-scale Flux Ropes and Their Geoeffectiveness with a Machine-learning Approach

Detecting large-scale flux ropes (FRs) embedded in interplanetary coronal mass ejections (ICMEs) and assessing their geoeffectiveness are essential, since they can drive severe space weather. At 1 au, these FRs have an average duration of 1 day. Their most common magnetic features are large, smoothly rotating magnetic fields. Their manual detection has become a relatively common practice over decades, although visual detection can be time-consuming and subject to observer bias. Our study proposes a pipeline that utilizes two supervised binary classification machine-learning models trained with solar wind magnetic properties to automatically detect large-scale FRs and additionally determine their geoeffectiveness. The first model is used to generate a list of autodetected FRs. Using the properties of the southward magnetic field, the second model determines the geoeffectiveness of FRs. Our method identifies 88.6% and 80% of large-scale ICMEs (duration 1day) observed at 1au by the Wind and the Solar TErrestrial RElations Observatory missions, respectively. While testing with continuous solar wind data obtained from Wind, our pipeline detected 56 of the 64 large-scale ICMEs during the 2008–2014 period (recall = 0.875), but also many false positives (precision = 0.56), as we do not take into account any additional solar wind properties other than the magnetic properties. We find an accuracy of 0.88 when estimating the geoeffectiveness of the autodetected FRs using our method. Thus, in space-weather nowcasting and forecasting at L1 or any planetary missions, our pipeline can be utilized to offer a first-order detection of large-scale FRs and their geoeffectiveness.

Sanchita Pal↗
NASA NTRS2009

Testing First-Order Logic Axioms in AutoCert

AutoCert [2] is a formal verification tool for machine generated code in safety critical domains, such as aerospace control code generated from MathWorks Real-Time Workshop. AutoCert uses Automated Theorem Provers (ATPs) [5] based on First-Order Logic (FOL) to formally verify safety and functional correctness properties of the code. These ATPs try to build proofs based on user provided domain-specific axioms, which can be arbitrary First-Order Formulas (FOFs). These axioms are the most crucial part of the trusted base, since proofs can be submitted to a proof checker removing the need to trust the prover and AutoCert itself plays the part of checking the code generator. However, formulating axioms correctly (i.e. precisely as the user had really intended) is non-trivial in practice. The challenge of axiomatization arise from several dimensions. First, the domain knowledge has its own complexity. AutoCert has been used to verify mathematical requirements on navigation software that carries out various geometric coordinate transformations involving matrices and quaternions. Axiomatic theories for such constructs are complex enough that mistakes are not uncommon. Second, adjusting axioms for ATPs can add even more complexity. The axioms frequently need to be modified in order to have them in a form suitable for use with ATPs. Such modifications tend to obscure the axioms further. Thirdly, speculating validity of the axioms from the output of existing ATPs is very hard since theorem provers typically do not give any examples or counterexamples.

Ahn, Ki Yung↗
NASA NTRS2025

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic↗
NASA NTRS1994

Flexible manufacturing for photonics device assembly

The assembly of photonics devices such as laser diodes, optical modulators, and opto-electronics multi-chip modules (OEMCM), usually requires the placement of micron size devices such as laser diodes, and sub-micron precision attachment between optical fibers and diodes or waveguide modulators (usually referred to as pigtailing). This is a very labor intensive process. Studies done by the opto-electronics (OE) industry have shown that 95 percent of the cost of a pigtailed photonic device is due to the use of manual alignment and bonding techniques, which is the current practice in industry. At Lawrence Livermore National Laboratory, we are working to reduce the cost of packaging OE devices through the use of automation. Our efforts are concentrated on several areas that are directly related to an automated process. This paper will focus on our progress in two of those areas, in particular, an automated fiber pigtailing machine and silicon micro-technology compatible with an automated process.

Lu, Shin-Yee↗
NASA NTRS2023

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential for mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. For this project, NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail travel and U.S.-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986-2022. Using data from Landsat 5 and 8, Sentinel-2, NAIP, and PlanetScope, the team computed NDVI, NDMI, MSAVI2, EVI, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on vegetation indices and spectral bands before running k-means clustering and random forest classification algorithms. Between all datasets, the team found that the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants, and this project can serve as a jumping off point for future invasive species monitoring. The NPS’s collection of ground data for 2022-2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive species spread over time.

Coronado National Memorial↗
NASA NTRS1992

Superplastic forming of ceramic insulation

Superplasticity has been demonstrated in many fine-grained structural ceramics and ceramic composites, including yttria-stabilized tetragonal zirconia polycrystal (YTZP), alumina, and Al2O3-reinforced zirconia (Al2O3/YTZ) duplex composites and SiC-reinforced Si3N4. These superplastic ceramics obviously offer the potential benefit of forming net shape or near net shape parts. This could be particularly useful for forming complicated shapes that are difficult to achieve using conventional forming techniques, or require elaborate, subsequent machining. In the present study, we successfully demonstrated the following: (1) superplastic 3Y-TXP and 20 percent Al2O3/YTZ composite have for the first time been successfully deformed into hemispherical caps via a biaxial gas-pressure forming technique; (2) no experimental difficulty was encountered in applying the required gas pressures and temperatures to achieve the results, thus, it is certain that higher rates of deformation than those presented in this study will be possible by using the current test apparatus at higher temperatures and pressures; and (3) an analytical model incorporating material parameters, such as variations during forming in the strain rate sensitivity exponent and grain growth-induced strain hardening, is needed to model accurately and therefore precisely control the biaxial gas-pressure forming of superplastic ceramics. Based on the results of this study, we propose to fabricate zirconia insulation tubes by superplastic extrusion of zirconia polycrystal. This would not only reduce the cost, but also improve the reliability of the tube products.

Nieh, T. G.↗
NASA NTRS2005

New Deep Reactive Ion Etching Process Developed for the Microfabrication of Silicon Carbide

Silicon carbide (SiC) is a promising material for harsh environment sensors and electronics because it can enable such devices to withstand high temperatures and corrosive environments. Microfabrication techniques have been studied extensively in an effort to obtain the same flexibility of machining SiC that is possible for the fabrication of silicon devices. Bulk micromachining using deep reactive ion etching (DRIE) is attractive because it allows the fabrication of microstructures with high aspect ratios (etch depth divided by lateral feature size) in single-crystal or polycrystalline wafers. Previously, the Sensors and Electronics Branch of the NASA Glenn Research Center developed a DRIE process for SiC using the etchant gases sulfur hexafluoride (SF6) and argon (Ar). This process provides an adequate etch rate of 0.2 m/min and yields a smooth surface at the etch bottom. However, the etch sidewalls are rougher than desired, as shown in the preceding photomicrograph. Furthermore, the resulting structures have sides that slope inwards, rather than being precisely vertical. A new DRIE process for SiC was developed at Glenn that produces smooth, vertical sidewalls, while maintaining an adequately high etch rate.

Evans, Laura J.↗
NASA NTRS1982

Crystal cleaving machine

A machine is disclosed for cleaving hard crystals. A typical example of which is lithium fluoride, with prcision and uniformity and includes vertical axis positioning control means for an adjustable spring tension guided hammer mechanism employed to strike an anvil. A crystal cleaving shock wave transmitted to a cleaving blade is generated having an angulated cleaving edge in contact with one corner of the crystal. Connection between the anvil and the blade is by means of a pair of vertical shafts held in substantially friction free engagement by two pairs of adjustable linear bearings. An underlying crystal holding fixture with horizontal position control means includes a zero reference stop face for the crystal and opposing spring-loaded clamping and vertical positioning elements which are precisely guided.

Hallberg, F. C.↗
NASA NTRS2004

Blackbody Cavity for Calibrations at 200 to 273 K

A laboratory blackbody cavity has been designed and built for calibrating infrared radiometers used to measure radiant temperatures in the range from about 200 to about 273 K. In this below-room-temperature range, scattering of background infrared radiation from room-temperature surfaces could, potentially, contribute significantly to the spectral radiance of the blackbody cavity, thereby contributing a significant error to the radiant temperature used as the calibration value. The present blackbody cavity is of an established type in which multiple reflections from a combination of conical and cylindrical black-coated walls are exploited to obtain an effective emissivity greater than the emissivity value of the coating material on a flat exposed surface. The coating material in this case is a flat black paint that has an emissivity of approximately of 0.91 in the thermal spectral range and was selected over other, higher-emissivity materials because of its ability to withstand thermal cycling. We found many black coatings cracked and flaked after thermal cycling due to differences in the coefficient of expansion differences. On the basis of theoretical calculations, the effective emissivity is expected to approach 0.999. The cylindrical/conical shell enclosing the cavity is machined from copper, which is chosen for its high thermal conductivity. In use, the shell is oriented vertically, open end facing up, and inserted in a Dewar flask filled with isopropyl alcohol/dry-ice slush. A flange at the open end of the shell is supported by a thermally insulating ring on the lip of the Dewar flask. The slush cools the shell (and thus the black-body cavity) to the desired temperature. Typically, the slush starts at a temperature of about 194 K. The slush is stirred and warmed by bubbling dry air or nitrogen through it, thereby gradually increasing the temperature through the aforementioned calibration range during an interval of several hours. The temperature of the slush is monitored by use of a precise thermocouple probe.

Howell, Dane↗
NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗