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At least 973 records · Page 54

Assessing the Use of UAS-Related Terms in ASRS using Seeds for Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential system that disseminates reports received from personnel involved in aviation operations after de-identifying them. These reports are used by the community to improve overall aviation system safety. Aim: We propose and execute an experiment to assess the use of seed term topic modeling over the database narratives to identify Unmanned Aircraft System (UAS) reports. The use of seed term topic modeling enables users to identify groups of conceptually similar narratives associated to a topic of their interest. Method: We use a collection of narratives, expert-selected words, and report metadata that separates UAS from non-UAS reports to assess if seed topic modeling can be used to improve ASRS searches. Results: For simpler queries, seed topic search observes a higher recall and lower precision than the existing DBOL (DataBase OnLine) search in operation. However, the best results are obtained when seed topic search is used as a search suggestion system to be executed on the DBOL. Conclusion: Utilizing a combination of both the existing method and the proposed method, users can expand their search vocabulary about subjects of interest while improving the quality of results.

LDA↗

FLUKA simulation validation to measure the beam energy of a cyclotron

FLUKA is a fully integrated particle physics MonteCarlo simulation package which has many applications in high energy experimental physics and engineering. When using a cyclotron for medical radionuclide production, it is important to know that the beam energy is suitable to cause the intended nuclear reaction and minimize unwanted impurities. Here, this work focuses on the comparison of FLUKA as a tool to measure the beam energy of a cyclotron with experimental results using the method of stacked copper foils interspaced by an aluminum degrader. We compared two methods to determine the activity ratio: determining the activity in each foil using the experimentally measured cross-sections from the National Nuclear Data Center (NNDC) cross-section data and calculating the activity in the two Cu foils using the FLUKA program. These results were compared to those reported by Gagnon et al., 2011. The FLUKA results gave energy measurements that were different than the true energy by a percentage in the range of 2.4% to 13%, suggesting that FLUKA is not recommended for pre-calculating the cyclotron beam energy using these low Z materials without experimental confirmation. It also confirms that the experimental cross-section data from the NNDC database is superior for this application giving energy values that ranged from 0.1% to 1.6% from the true energy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

54 ENVIRONMENTAL SCIENCES↗

Cryogenic hydrogen-induced air liquefaction technologies

Extensively utilizing a special advanced airbreathing propulsion archives database, as well as direct contacts with individuals who were active in the field in previous years, a technical assessment of cryogenic hydrogen-induced air liquefaction, as a prospective onboard aerospace vehicle process, was performed and documented. The resulting assessment report is summarized. Technical findings are presented relating the status of air liquefaction technology, both as a singular technical area, and also that of a cluster of collateral technical areas including: compact lightweight cryogenic heat exchangers; heat exchanger atmospheric constituents fouling alleviation; para/ortho hydrogen shift conversion catalysts; hydrogen turbine expanders, cryogenic air compressors and liquid air pumps; hydrogen recycling using slush hydrogen as heat sink; liquid hydrogen/liquid air rocket-type combustion devices; air collection and enrichment systems (ACES); and technically related engine concepts.

Escher, William J. D.↗

NASA's SPICE System Models the Solar System

SPICE is NASA's multimission, multidiscipline information system for assembling, distributing, archiving, and accessing space science geometry and related data used by scientists and engineers for mission design and mission evaluation, detailed observation planning, mission operations, and science data analysis.

mission design↗

Inductive monitoring system constructed from nominal system data and its use in real-time system monitoring

The present invention relates to an Inductive Monitoring System (IMS), its software implementations, hardware embodiments and applications. Training data is received, typically nominal system data acquired from sensors in normally operating systems or from detailed system simulations. The training data is formed into vectors that are used to generate a knowledge database having clusters of nominal operating regions therein. IMS monitors a system's performance or health by comparing cluster parameters in the knowledge database with incoming sensor data from a monitored-system formed into vectors. Nominal performance is concluded when a monitored-system vector is determined to lie within a nominal operating region cluster or lies sufficiently close to a such a cluster as determined by a threshold value and a distance metric. Some embodiments of IMS include cluster indexing and retrieval methods that increase the execution speed of IMS.

Iverson, David L.↗

Assessment of Ku- and Ka-band Dual-Frequency Radar for Snow Retrieval

Dual-frequency Ku/Ka-band radar retrievals of snow parameters such as liquid-equivalent snowfall rate (R) and mass-weighted diameter (Dm) have two principal errors, namely, the differences between the assumed particle size distribution (PSD) model from the actual PSD and inadequacies in characterizing the single-scattering properties of snowflakes. Regarding the first issue, this study, based on radar simulations from a large amount of observed PSD data, shows that there exist relatively high correlations between the estimated snow parameters and their true values derived directly from the measured PSD. For PSD data with R greater than 0.1 mm h−1, a gamma PSD model with a fixed shape factor (μ) equal to 0 (or exponential distribution) provides the best estimates of R and Dm. This is despite negative biases of up to −15 % in R and underestimates and overestimates in Dm for small and large Dm, respectively. The μ = 0 assumption, however, produces relatively poor estimates of normalized intercepts of a gamma PSD (Nw), whereas the best estimates are obtained when μ is considered either 3 or 6. However, the use of an inappropriate scattering table increases the errors in snow retrieval. Simple evaluations are made for cases where the scattering databases used for the algorithm input differ from that used for retrieval. The mismatched scattering databases alone could cause at least 30 %-50 % changes in the estimates of snow water content (SWC) and R and could affect the retrievals of Dm and Nw and their dependence on μ.

Liang Liao↗

Managing Multi-Instrument Data Streams in Secure Environments

The capture and curation of all primary instrument data is a potentially valuable source of added insight into experiments or diagnostics in laboratory experiments. The data can, when properly curated, enable analysis beyond the current practice that uses just a subset of the as-measured data. Complete curated data can also be input for machine learning and other data exploration tools. Conveniently storing and accessing instrument data requires that the instruments are connected to databases and users through a networking infrastructure. This infrastructure needs to accommodate a wide array of instruments which can range from single laboratory mounted probes for environment monitoring to computers managing multiple instruments. These resources may also include mobile devices on which researchers record instrument and experiment state related notes. These varied data sources bring with them the challenges of different communications capabilities and protocols as well as the primary data typically being produced in proprietary formats. These challenges are further compounded when the instruments need to operate in secure environments such as required in national laboratories. We will discuss the SmartLab, an ongoing effort to set up a system for instrument and simulation data curation at NASA Langley Research Center. We will outline the challenges faced in managing the data sources required for ongoing research activities and the solutions that are being considered and implemented to address those challenges.

instrument data management↗

Development and Analysis of a Thick Cloud Layers Database for Lightning Launch Commit Criteria Improvement

Lightning can pose a potential threat to space launch vehicles. In response to this, rules were created called the Lightning Launch Commit Criteria (LLCC) that help weather personnel evaluate the potential for natural and rocket-triggered lightning. One of the ten LLCC with the least research is called the Thick Cloud Layers rule. To further understand electrification of thick cloud layers and potentially improve the Thick Cloud Layers rule, a database of thick cloud layers that occurred over the Eastern Range was created. This database is then used to create an algorithm for identifying and differentiating thick cloud layers from other cloud types based on radar characteristics, temperature levels in reference to cloud height, and the surface electric field. By analyzing and identifying thick cloud events, this project could help narrow down when thick clouds are occurring and potentially minimize unnecessary launch delays. Events that caused LLCC violations involving the Thick Cloud Layers rule were analyzed by hand using Level-2 NEXRAD radar data from the National Weather Service WSR-88D radar in Melbourne with the program GR2Analyst. Cases that were found to be isolated and not involved with convection were recorded (date, start/end time, location) in a database. Radar data associated with these cases was collected and gridded using Python radar packages. Once gridded, I calculated and recorded for each radar scan the following radar reflectivity driven parameters within an 11x11 km bin centered on each 1 square km grid point: the mean reflectivity colder than 0 degrees Celsius, Maximum Radar Reflectivity (MRR) colder than 0 degrees Celsius, Volume Averaged Height Integrated Radar Reflectivity (VAHIRR), Hydrometeor Identification (HID), the difference between the maximum and mean reflectivity, the cloud depth colder than 0 degrees Celsius, the overall cloud depth, the cloud top, and the cloud bottom. Soundings for each event were used to determine cloud temperature levels, and where the cloud is in relation to the freezing level. Electric field mill data collected over the Eastern Range was used to determine surface electric fields below each cloud. All parameters were analyzed in depth for several thick cloud cases to gain an understanding of typical thick cloud characteristics. Cases of thick clouds and other isolated cloud types were also recorded for training purposes to see if enough differences exist between cloud types to differentiate them with an algorithm. Each case along with its corresponding characteristics was recorded in a database, and this database was used to compare differing cloud types, as well as train the algorithm to detect thick clouds.

Lightning↗

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Utilizing Ontology Structures To Curate the DOE-NETL Carbon Storage Open Database

The specialized ontology for the Carbon Storage Open Database will enable more rapid assignment of appropriate symbology standards for visualization improvements, optimize topical and spatial tagging within keywords, and improve flexibility for utilization in existing data repositories such as EDX. This effort also aims to establish a foundation for utilization of ontologies for organization of other data related to geologic carbon storage in the future.

Martin, Abigail↗

Two-dimensional computations of multi-stage compressor flows using a zonal approach

A clear understanding of the fluid dynamics associated with rotor/stator configurations can be very helpful when optimizing the performance of turbomachinery. In this study, a two-dimensional, implicit, thin-layer, Navier-Stokes zonal approach has been used to investigate the flow within a 2 1/2-stage compressor. Relative motion between the rotor and stator airfoils is made possible with the use of systems of patched and overlaid grids that move with respect to each other. The treatment of multistage turbomachines with arbitrary numbers of airfoils per row is made possible by the use of a flexible database system. Results in the form of instantaneous pressure and entropy contours and time-averaged pressures are presented for the 2 1/2-stage compressor. Time-averaged pressures and pressure amplitudes for a single-stage turbine configuration are also presented. The numerical results compare well with experimental data.

Gundy-Burlet, Karen L.↗

Recent technology products from Space Human Factors research

The goals of the NASA Space Human Factors program and the research carried out concerning human factors are discussed with emphasis given to the development of human performance models, data, and tools. The major products from this program are described, which include the Laser Anthropometric Mapping System; a model of the human body for evaluating the kinematics and dynamics of human motion and strength in microgravity environment; an operational experience data base for verifying and validating the data repository of manned space flights; the Operational Experience Database Taxonomy; and a human-computer interaction laboratory whose products are the display softaware and requirements and the guideline documents and standards for applications on human-computer interaction. Special attention is given to the 'Convoltron', a prototype version of a signal processor for synthesizing the head-related transfer functions.

Jenkins, James P.↗

KSC History Project

The project is a joint endeavor between Dr. Henry Dethloff and myself and is producing a number of products related to KSC history. This report is a summary of those projects. First, there is an overview monograph covering KSC history. Second, there is a chapter outline for an eventual book-length history. Third, there is monograph on safety at KSC. Finally, there is a web page and database dedicated to the KSC oral history project.

Snaples, Lee↗

Explore Full Range of QSO/AGN Properties

The goal of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory s Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic databases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program had the following goals: 1) Refine the data analysis of IS0 observations to obtain deeper and better SNR results on selected sources. The IS0 data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the IS0 teams in 2001. The Fabry-Perot database is particularly sensitive to noise and slight calibration errors. 2) Model the atomic and molecular line shapes, in particular the OH lines, using revised monte- carlo techniques developed by the SWAS team at the Center for Astrophysics; 3) Attend scientific meetings and workshops; 4) Do E&PO activities related to infrared astrophysics and/or spectroscopy.

Oliversen, Ronald↗

A Conventional Liner Acoustic/Drag Interaction Benchmark Database

The aerodynamic drag of acoustic liners has become a significant topic in the design of such for aircraft noise applications. In order to evaluate the benefits of concepts designed to reduce liner drag, it is necessary to establish the baseline performance of liners employing the typical design features of conventional configurations. This paper details a set of experiments in the NASA Langley Grazing Flow Impedance Tube to quantify the relative drag of a number of perforate-over-honeycomb liner configurations at flow speeds of M=0.3 and 0.5. These conventional liners are investigated to determine their resistance factors using a static pressure drop approach. Comparison of the resistance factors gives a relative measurement of liner drag. For these same flow conditions, acoustic measurements are performed with tonal excitation from 400 to 3000 Hz at source sound pressure levels of 140 and 150 dB. Educed impedance and attenuation spectra are used to determine the interaction between acoustic performance and drag.

Howerton, Brian M.↗

A Rapid, Low-Cost Approach to Permanently Extend Life Beyond Earth

This presentation covers the value proposition and challenges of permanently extending life beyond Earth. It proposes that this can be most expeditiously accomplished by starting with a population of small Closed Ecological Systems (CES)s, each with several specie populations that enable each CES to persist indefinitely without the need to add resources, remove wastes, or require human intervention. Each CES is instrumented and controlled so that it can be remotely maintained, experiments performed, and data collected. Data from the entire population of CESs are managed in a cloud server database for analyses on how to improve the performance of each CES as well as formulate new CESs. The presentation discusses a modular, artificial-spacecraft prototype that could be used to fly CES modules in space under various gravity and radiation conditions to study changes in the CESs relative to their counterparts that remain on Earth as the control group. The presentation concludes with the next, low-cost steps for rapidly executing the approach described.

Dorais, Gregory A.↗

Usage-Based Discovery of Earth Observations

Most providers of Earth Observation data enable search via dataset characteristics, (e.g., quantity being measured, instrument, location, and time). However, the Earth Science Information Partners Federation (ESIP) is attempting to improve dataset discovery by capturing information on how datasets are used. At a usage-based discovery hackfest at the July 2020 ESIP Summer Meeting, participants pooled their collective skills to implement a prototype based on the connections between datasets and data usage, which can reveal unanticipated patterns in dataset connectivity that are not apparent through traditional approaches. A survey of natural hazards websites, focusing on hydrology-related hazards such as floods and hydrology datasets such as rainfall, illustrated the difficulty of gleaning which dataset was actually used and how it was accessed. This difficulty highlights the need for greater transparency on dataset usage in website design. An application wireframe for a usage-based discovery database was conceptualized as a tool to help applications data specialists rapidly assemble a fit-for-purpose website as part of a disaster response, where customer feedback was integral to the manner in which the website would be developed and delivered. Capturing connections among datasets and instances of usage, either for research or applications, could help users identify datasets with a proven track record of utility or those that have been supplanted by more accurate and(or) precise representations. It may also help Earth Observation providers maximize returns on investments in data services. Social discovery, i.e, following discovery paths laid down by previous users of the data, could be a critical tool for improving the timeliness and applicability of dataset delivery at times and in circumstances where practitioners don’t have the capacity to evaluate the deluge of datasets that are returned by today’s search tools.

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