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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Total Lightning Activity as Observed from Space

ABSTRACT: Our knowledge of the global distribution of lightning has improved dramatically since the 1995 launch of the Optical Transient Detector (OTD), followed in 1997 by the launch of the Lightning Imaging Sensor (LIS). Together, these instruments have generated a continuous seven-year record of global lightning activity. These lightning observations have provided a new global perspective on total lightning activity. For the first time, total lightning activity (CG and IC) has been observed over large regions with high detection efficiencies and accurate geographic location. This has produced new insights into lightning distributions, times of occurrence and variability. It has produced a revised global flash rate estimate (44 flashes per second) and has lead to a new realization of the significance of total ligh&g activity in severe weather. Accurate flash rate estimates are now available for areas of the earth (+/- 72 deg. latitude). Ocean-land contrasts as a function of season are clearly reveled, as are orographic effects and seasonal and interannual variability. The data set indicates that air mass thunderstorms, not large storm system dominate global activity. The ability of LIS and OTD to detect total lightning has lead to improved insight into the correlation between lightning and storm development. The relationship between updraft development and lightning activity is now well established and presents an opportunity for providing a new mechanism for remotely monitoring storm development. In this concept, lightning would serve as a surrogate for updraft velocity. It is anticipated that this capability could lead to significantly improved severe weather warning times and reduced false warning rates.

Christian, Hugh J.↗
DOE OSTI2024

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗
NASA NTRS1991

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 6: The relationship between the use of US government technical reports by US aerospace engineers and scientists and selected institutional and sociometric variables

The relationship between the use of U.S. government technical reports by U.S. aerospace engineers and scientists and selected institutional and sociometric variables was investigated. The methodology used for this study was survey research. Data were collected by means of a self-administered mail questionnaire. The approximately 34,000 members of the American Institute of Aeronautics and Astronauts (AIAA) served as the study population. The response rate for the survey was 70 percent. A dependent relationship was found to exist between the use of U.S. government technical reports and three of the institutional variables (academic preparation, years of professional aerospace work experience, and technical discipline). The use of U.S. government technical reports was found to be independent of all of the sociometric variables. The institutional variables best explain the use of U.S. government technical reports by U.S. aerospace engineers and scientists.

Pinelli, Thomas E.↗
NASA NTRS1987

Observations of HCN in Comet Halley

Observations of the HCN J = 1-0 rotational transition at 3.4 mm wavelength in comet P/Halley are discussed. The data were obtained during a total of 56 individual observing sessions between Nov. 18, 1985 and May 11, 1986, and represent the first time that a cometary parent molecule has been so extensively monitored. The HCN production rate is well correlated with the total visual magnitude of the comet, indicating that HCN follows the overall gas production. There is also evidence of time variability and variations in the HCN hyperfine ratios from their LTE values. Spectra obtained by binning the HCN data with heliocentric distance show that the HCN line width, and thus the parent outflow velocity, increases with decreasing heliocentric distance.

Schloerb, F. Peter↗
NASA NTRS1983

Thunderstorm cloud top observations using satellite stereoscopy

The present investigation has as objective to take a detailed look at the intense squall line over Oklahoma on May 2-3, 1979, using GOES stereoscopy combined with GOES infrared data. The synoptic situation and data sources are considered along with the stereoscopically observed cloud top ascent rates. Cloud top observations of intense thunderstorms are discussed, taking into account a contouring technique, the interpretation of infrared cloud top temperature patterns, and small-scale structure and its variability. It is found that GOES IR cloud top temperatures grossly underestimate the actual cloud top height observed stereoscopically, especially for immature storms. It is difficult to define growing storms below about 10 km in the GOES infrared data.

Mack, R. A.↗
NASA NTRS2011

Variability of Thermosphere and Ionosphere Responses to Solar Flares

We investigated how the rise rate and decay rate of solar flares affect the thermosphere and ionosphere responses to them. Model simulations and data analysis were conducted for two flares of similar magnitude (X6.2 and X5.4) that had the same location on the solar limb, but the X6.2 flare had longer rise and decay times. Simulated total electron content (TEC) enhancements from the X6.2 and X5.4 flares were 6 total electron content units (TECU) and approximately 2 TECU, and the simulated neutral density enhancements were approximately 15% -20% and approximately 5%, respectively, in reasonable agreement with observations. Additional model simulations showed that for idealized flares with the same magnitude and location, the thermosphere and ionosphere responses changed significantly as a function of rise and decay rates. The Neupert Effect, which predicts that a faster flare rise rate leads to a larger EUV enhancement during the impulsive phase, caused a larger maximum ion production enhancement. In addition, model simulations showed that increased E x B plasma transport due to conductivity increases during the flares caused a significant equatorial anomaly feature in the electron density enhancement in the F region but a relatively weaker equatorial anomaly feature in TEC enhancement, owing to dominant contributions by photochemical production and loss processes. The latitude dependence of the thermosphere response correlated well with the solar zenith angle effect, whereas the latitude dependence of the ionosphere response was more complex, owing to plasma transport and the winter anomaly.

Qian, Liying↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS1993

Ozone depletion at northern and southern latitudes derived from January 1979 to December 1991 Total Ozone Mapping Spectrometer data

An extended version of the Nimbus 7/TOMS ozone data set from the period January 1, 1979 to December 31, 1991 is presented. It is shown that the ozone-trend data indicate that regions of enhanced ozone depletion rates have formed at middle and high latitudes during recent years. The seasonal dependence and geographical extent of the enhanced ozone-depletion rates for the Northern and Southern hemispheres are examined. The variability of the long-term ozone trend determination is discussed via consideration of the differences among 11-, 12-, and 13-yr trend calculations. The effects of the Mount Pinatubo eruption and other volcanic eruptions on the TOMS equatorial zonal average ozone measurements, and its influence on long-term trend determinations are discussed. On the basis of a determination of the aerosol phase function using TOMS data, the effect of stratospheric aerosols on determination of ozone amounts from TOMS are shown to be less than 1 percent.

Herman, J. R.↗
NASA NTRS1980

Extensional flow of dilute polymer solution

Simultaneous effects of temperature and concentration on tensile viscosity are investigated using a semi-empirical scaling law established to relate the concentration, temperature and deformation rate by a reduced deformation rate variable. Results show the onset of high viscosity occurring in the vicinity of the onset of non-Newtonian viscosity observed in a simple shear flow experiment. High viscosity is also compared with steady and dynamic shear data. Finally, the asymptotic solution of Hassager's kinetic theory of a bead-rod model for macromolecular solutions is compared with the data, indicating that tensile viscosity depends strongly on the molecular weight, the higher the molecular weight, the more sensitive the tensile viscosity in terms of the deformation rate.

Peng, S. T. J.↗
NASA NTRS1971

A study of boundary layer transition on outgassing cones in hypersonic flow

Surface heat-transfer rates and pressures were measured at hypersonic speeds on sharp cones at zero angle of attack with and without gas injection. Using the non-injection results for reference data the effects on heating and transition location of surface roughness and injectant rate, distribution and composition were determined. The transition location was sensitive to the injectant distribution. The transition Reynolds numbers were significantly greater when the injectant distribution was constant than with a variable distribution. The measured heat-transfer distribution were also strongly dependent upon the injectant distribution. Transition Reynolds number results obtained during this program with a variable injectant distribution were correlated with a limited amount of data available for a degrading model tested in a different facility. Transitional data with constant injectant distribution were correlated with earlier results. An empirical correlation of heat-transfer reduction due to gas injection in turbulent flow was developed for both distributions tested. Several effects of mass addition on heating and transition, which have been earlier reported, were observed.

Stalmach, C. J., Jr.↗
NASA NTRS2017

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗
NASA NTRS1993

Summary of the effects of engine throttle response on airplane formation-flying qualities

A flight evaluation was conducted to determine the effect of engine throttle response characteristics on precision formation-flying qualities. A variable electronic throttle control system was developed and flight-tested on a TF-104G airplane with a J79-11B engine at the NASA Dryden Flight Research Facility. This airplane was chosen because of its known, very favorable thrust response characteristics. Ten research flights were flown to evaluate the effects of throttle gain, time delay, and fuel control rate limiting on engine handling qualities during a demanding precision wing formation task. Handling quality effects of lag filters and lead compensation time delays were also evaluated. The Cooper and Harper Pilot Rating Scale was used to assign levels of handling quality. Data from pilot ratings and comments indicate that throttle control system time delays and rate limits cause significant degradations in handling qualities. Threshold values for satisfactory (level 1) and adequate (level 2) handling qualities of these key variables are presented. These results may provide engine manufacturers with guidelines to assure satisfactory handling qualities in future engine designs.

Walsh, Kevin R.↗
DOE OSTI2024

Radiation induced athermal diffusivity in uranium mononitride

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuel considered for light water reactors and advanced reactor designs. Properties like self- and fission gas diffusivity need to be better understood, given that they influence key fuel performance phenomena such as fission gas swelling and release. In particular, the radiation induced athermal (D 3 ) diffusivity remains challenging to accurately predict and has only been sparsely characterized in UN, despite its importance as it likely governs diffusion at the low temperatures this high-thermal-conductivity fuel form may operate. Molecular Dynamics simulations are used to estimate the mean square displacement induced by a primary knock-on atom (PKA) with a given kinetic energy. These results are combined with the PKA energy distributions obtained from binary collision approximation calculations to obtain the displacement due to a particular fission fragment. Finally, this is combined with experimental fission fragment yields to determine the displacement due to an average fission event and, thus, express the athermal diffusivity as a function of the fission rate density. These results are in excellent agreement with available experimental data. In conclusion, a particular importance is given to the understanding and the quantification of the variability of these results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1967

Digital-to-analog converter operates from low level inputs

Circuit controls a voltage controlled oscillator from computer output binary data representing a rate at which the oscillator is to change. It operates with low level output devices such as integrated circuit registers and devices with somewhat variable output levels.

Winkelstein, R. A.↗
NASA NTRS1982

High velocity gas outflow from the nova-like variable LSI 55 deg -8

Low and high dispersion International Ultraviolet Explorer observations and measurements of the optical brightness of LSI 55-8 taken on 5 December, 1981 are analyzed. The presence of the C IV resonance doublet showing a variable P Cygni type of profile with a blue shifted absorption component along with the blue shifted absorption features of the high temperature ions indicate the existence of outflowing hot plasma (i.e., a wind). An upper limit of the mass outflow rate was established from the shot wavelength edge of the C IV absorption. The normalized C IV profile is shown o be variable with the largest changes occurring in the relative strength and shape of the emission component. These changes appear to be systematic, and may be associated with the changing projection of the outflowing hot plasma against the disk as a function of orbital motion. LSI 55-8 demonstrates most of the spectral and photometric characteristics exhibited by the nova like, UX UMa type variables, as well as with the dwarf novae in outburst or standstill. The high accretion rate inferred from fitting the Williams theoretical disk model fluxes to IUE data support the hypothesis that LSI 55-8 and related nova like systems are in a state of prolonged outburst.

Guinan, E. F.↗
NASA NTRS2010

Possible Effects of Seasonal Fires on Drought Across the Northern Sub-Saharan African Region

Recent satellite-based studies have revealed that the northern sub-Saharan African (NSSA) region has one of the highest biomass-burning rates per unit land area among all regions of the world. Because of the high concentration and frequency of fires in this region, with the associated abundance of heat release and gaseous and particulate smoke emissions, biomass-burning activity is believed to be a major driver of the regional carbon, energy, and water cycles. We acknowledge that the rainy season in the NSSA region is from April to September while biomass burning occurs mainly during the dry season (October to March). Nevertheless, these two phenomena are indirectly coupled to each other through a chain of complex processes and conditions, including land-cover and surface-albedo changes, the carbon cycle, evapotranspiration, drought, desertification, surface water runoff, ground water recharge, and variability in atmospheric composition, heating rates, and circulation. In this presentation, we will examine the theoretical linkages between these processes, discuss the preliminary results based on satellite data analysis, and provide an overview of plans for more integrated research to be conducted over the next few years.

Ichoku, Charles↗
NASA NTRS2010

Assessment of the Vulnerability of Water Resources to Seasonal Fires Across the Northern Sub-Saharan African Region

The northern sub-Saharan African (NSSA) region, extending from the southern fringes of the Sahara to the Equator, and stretching west to east from the Atlantic to the Indian ocean coasts, plays a prominent role in the distribution of Saharan dust and other airborne matter around the region and to other parts of the world, the genesis of global atmospheric circulation, and the birth of such major (and often catastrophic) events as hurricanes. Therefore, this NSSA region represents a critical variable in the global climate change equation. Recent satellite-based studies have revealed that the NSSA region has one of the highest biomass-burning rates per unit land area among all regions of the world. Because of the high concentration and frequency of fires in this region, with the associated abundance of heat release and gaseous and particulate smoke emissions, biomass-burning activity is believed to be a major driver of the regional carbon, energy, and water cycles. We acknowledge that the rainy season in the NSSA region is from April to September while biomass burning occurs mainly during the dry season (October to March). Nevertheless, these two phenomena are indirectly coupled to each other through a chain of complex processes and conditions, including land-cover and surface-albedo changes, the carbon cycle, evapotranspiration, drought, desertification, surface water runoff, ground water recharge, and variability in atmospheric composition, heating rates, and circulation. In this presentation, we will examine the theoretical linkages between these processes, discuss the preliminary results based on satellite data analysis, and provide an overview of plans for more integrated research to be conducted over the next few years.

Ichoku, Charles M.↗