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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Characterization of geostationary particle signatures based on the 'injection boundary' model

A simplified analytical procedure is used to characterize the details of geostationary particle signatures, in order to lend support to the 'injection boundary' concept. The signatures are generated by the time-of-flight effects evolving from an initial sharply defined, double spiraled boundary configuration. Complex and highly variable dispersion patterns often observed by geostationary satellites are successfully reproduced through the exclusive use of the most fundamental convection configuration characteristics. Many of the details of the patterns have not been previously presented. It is concluded that most of the dynamical dispersion features can be mapped to the double spiral boundary without further ad hoc assumptions, and that predicted and observed dispersion patterns exhibit symmetries distinct from those associated with the quasi-stationary particle convection patterns.

Mauk, B. H.↗
NASA NTRS1999

Self-organizing map (SOM) of space acceleration measurement system (SAMS) data

In this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.

STS-57 Shuttle Project↗
NASA NTRS1991

T on the Cray X/MP

This research was aimed at porting the T programming language, a dialect of LISP, to the Cray X/MP computer. The effort involved research into systems engineering and software engineering problems related not only to compiler design and implementation, but also to parallel computation, the X/MP being a shared-memory multiprocessor. Porting also involved the sub-tasks of retargeting the assembler, code-generator, and run-time system. A reasonably effective porting methodology that is relatively straight forward, although more difficult than table-driven approaches, has been developed. The run-time system was not ported, and thus the T programs cannot be run without explicit linking of the required run-time support. The run-time performance gain achieved in generated code was found to be disappointing. Recommendations for the achievement of higher performance are given.

Hudak, Paul↗
NASA NTRS1988

Effects of natural environment on first generation solid rocket booster thermal protection system materials

The effort to demonstrate, by real-time exposure, the effects of the natural environment at Kennedy Space Center, Florida, upon the Thermal Protection System (TPS) of the Solid Rocket Booster (SRB) is summarized, and that the overall SRB TPS configuration is verified to meet all requirements for resistance to the conditions associated with outdoor weathering, including: solar radiation; temperature; humidity; precipitation; wind; sand/dust abrasion; static electricity; salt spray; fungus; and atmospheric oxidants. The evaluation criterion for this project was based upon flatwise tensile properties, visual inspection, color change, and thermal performance. Based upon the evaluation of the changes in these properties, it is concluded that properly applied and topcoat-protected TPS can satisfactorily withstand the conditions of the natural environment at KSC for exposures up to six months.

Webb, D. D.↗
NASA NTRS1996

Electrohydrodynamic Pool Boiling in Reduced Gravity

This research is concerned with studying the effects of applied electric fields on pool boiling in a reduced-gravity environment. Experiments are conducted at the NASA Lewis 2.2 sec Drop tower using a drop rig constructed at UC Davis. In the experiments, a platinum wire is heated while immersed in saturated liquid refrigerants (FC-72 and FC-87), or water, causing vapor formation at the wire surface. Electric fields are applied between the wire surface and an outer screen electrode that surrounds the wire. Preliminary normal-gravity experiments with water have demonstrated that applied electric fields generated by the rig electronics can influence boiling characteristics. Reduced-gravity experiments will be performed in the summer of 1996. The experiments will provide fundamental data on electric field strengths required to disrupt film boiling (for various wire heat generation input rates) in reduced gravity for a cylindrical geometry. The experiments should also shed light on the roles of characteristic bubble generation times and charge relaxation times in determining the effects of electric fields on pool boiling. Normal-gravity comparison experiments will also be performed.

Shaw, Benjamin D.↗
NASA NTRS1971

NASA multidisciplinary research grant

Research is discussed in the multidisciplinary areas of space and planetary science; materials and radiation; systems, instrumentation, and structures; and technology and man. Highlights are identified as an alpha-recoil track method of archeological dating; infrared astronomical telescope; reaction rates data, semiconductor radiation detectors, and analysis of time-dependent systems; Gunn effect devices for microwave generation and detection, mode-locked lasers, and radiation theory; and the application of a satellite communication system to educational development. Detectors to be flown on Apollo 16 to measure heavy particle flux in the solar wind and to be part of the HEAO-A experiment on extremely heavy nuclei in cosmic rays were developed. The impact of the multidisciplinary research on university activities is described, and individual departmental reports are included.

Source record↗
NASA NTRS1977

Two types of magnetospheric ELF chorus and their substorm dependences

The distribution of extremely low frequency (10-1500 Hz) magnetospheric chorus to all local times and latitudes is investigated in order to determine dependence on substorms, and to evaluate the conditions under which chorus is generated. The analysis carefully separates space and time effects by an investigation of data obtained by the OGO 5 search coil magnetometer. A study of spatial dependencies shows that chorus occurs in two magnetic regions: equatorial chorus is located near the equator, and high-latitude chorus is located above 15 degrees. An analysis of chorus in each of the regions illustrates that equatorial chorus is definitely related to substorm, whereas high-latitude chorus often occurs within magnetically quiet intervals.

Tsurutani, B. T.↗
NASA NTRS1981

CADAT test pattern generator

CADAT test pattern generator (TPG) aids in checkout, fault detection, and fault isolation of complex digital circuits. Time and effort of manually generating digital test patterns can be major limiting factor in effectively utilizing automatic testing. This time and effort are reduced from several months to several days by TPG.

Source record↗
NASA NTRS1989

Chip Advancer For GPS Receiver

Instrument errors made negligible. For each integration interval, both delay and rate of change of delay initialized to small fraction of chip - for example, to order of 10 to the negative 7th power - thereby making feedback control and extraction of delay highly accurate and flexible. With appropriate selection of sampling rate relative to chip rate, commensurability errors reduced to extremely small levels. In Global Positioning System (GPS) receiver, pseudorandom code sequence generated by simple digital logic incorporating effects of time, delay, and rate of change of delay. Flexibility in starting time and sum interval very useful in aligning correlation interval with beginnings and endings of data bits.

Meehan, Thomas K.↗
NASA NTRS1992

Preliminary results of a Monte Carlo simulation of burst directions by BATSE

The effect of varying BATSE trigger parameters on the modeled BATSE detection rate is investigated numerically. Quantitative estimates are obtained of the systematic effects generated by the complex interplay of trigger times, variations in the signal-to-noise ratio for burst detection as well as the time scale over which backgrounds are determined, and the number of required detections above threshold. It is found, in particular that employing a third detection, at a reduced signal-to-noise ratio, to resolve a burst does not increase the detection rate. It is also shown that the BATSE detection rate is insensitive to variations in the time scale over which the background is determined.

Higdon, J. C.↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗
NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden Szeto↗
NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗
NASA NTRS2014

The Use of Redundancy to Improve Reliability of Deep Space Missions Using Stirling Radioisotope Generator Power Sources

This study will look at the 140 We class generator as originally envisioned for the ASRG and a larger generator that is scaled up to use four times the fuel. The results discussed below quantify the effect of the use of smaller generators and indicates that a scheme that makes use of several smaller generators enhances the system reliability and allows for more graceful degradation.

Bolotin, Gary↗
NASA NTRSDate not supplied

Optimization Algorithms as Quantum Performance Benchmarks

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) have the potential to demonstrate significant run-time performance benefits over current state-of-the-art solutions. Using existing methods for characterizing classical optimization algorithms, we analyze solution quality obtained by solving Max-Cut problems using a quantum annealing device and gate-model quantum simulators and devices. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through effective visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. The framework is an enhancement to the existing open-source QED-C Application-Oriented Benchmark suite and can connect to the open-source analysis libraries. The suite can be executed on various quantum simulators and quantum hardware systems.

benchmarking↗
NASA NTRS1983

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

Motyka, P.↗