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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Real-time remote scientific model validation

This paper describes flight results from the use of a CLIPS-based validation facility to compare analyzed data from a space life sciences (SLS) experiment to an investigator's preflight model. The comparison, performed in real-time, either confirms or refutes the model and its predictions. This result then becomes the basis for continuing or modifying the investigator's experiment protocol. Typically, neither the astronaut crew in Spacelab nor the ground-based investigator team are able to react to their experiment data in real time. This facility, part of a larger science advisor system called Principal Investigator in a Box, was flown on the space shuttle in October, 1993. The software system aided the conduct of a human vestibular physiology experiment and was able to outperform humans in the tasks of data integrity assurance, data analysis, and scientific model validation. Of twelve preflight hypotheses associated with investigator's model, seven were confirmed and five were rejected or compromised.

Frainier, Richard↗
DOE OSTI2021

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a non-overlapping window from the original acoustic data. The first column is the time of the window. The second and third columns are the mean and the variance of the acoustic data in this window, respectively. The 4th-11th column is the the power spectrum density ranging from low to high frequency. And the last column is the corresponding label (shear stress level). The name of the file means which driving velocity the sequence is generated from. Data were generated from laboratory friction experiments conducted with a biaxial shear apparatus. Experiments were conducted in the double direct shear configuration in which two fault zones are sheared between three rigid forcing blocks. Our samples consisted of two 5-mm-thick layers of simulated fault gouge with a nominal contact area of 10 by 10 cm^2. Gouge material consisted of soda-lime glass beads with initial particle size between 105 and 149 micrometers. Prior to shearing, we impose a constant fault normal stress of 2 MPa using a servo-controlled load-feedback mechanism and allow the sample to compact. Once the sample has reached a constant layer thickness, the central block is driven down at constant rate of 10 micrometers per second. In tandem, we collect an AE signal continuously at 4 MHz from a piezoceramic sensor embedded in a steel forcing block about 22 mm from the gouge layer The data from this experiment can be used with the deep learning algorithm to train it for future fault property prediction.

15 GEOTHERMAL ENERGY↗
NASA NTRS1973

Development of flight experiment work performance and workstation interface requirements. Part 2: Appendix H

A skill requirement definition method was applied to the problem of determining, at an early stage in system/mission definition, the skills required of on-orbit crew personnel whose activities will be related to the conduct or support of earth-orbital research. The experiment data base was selected from proposed experiments in NASA's Earth Orbital Research and Application Investigation program as related to space shuttle missions, specifically those being considered for sortie lab. Activities during the study, include identification of basic functions dealing with man's research and/or servicing activities on orbit. A crew function taxonomy was prepared relative to these activities. Likely candidate experiments for shuttle sortie missions were selected through extensive review of experiment and mission descriptions. Crew functions and tasks were initially identified for more than fifty representative earth orbital experiments, and a comprehensive task analysis was conducted on these tasks for selected payloads.

Hatterick, R. G.↗
NASA NTRS1980

Solar flux variation of the thermospheric molecular oxygen density

The paper presents measurements of the thermospheric molecular oxygen density obtained from the Atmosphere Explorer (AE) satellites and composition data obtained from rocket-based experiments which provide information on the distribution of O2 between 120 and 200 km as a function of solar flux. The rocket experiment data can be analyzed for long-term variations, which show that the O2 density at 200 km shows little variation but at 120 km decreases approximately 30% for the F sub 10.7-cm flux.

Kayser, D. C.↗
NASA NTRS1996

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Rafael, Qihang Li↗
NASA NTRS1991

Cosmoids - Solution to the Pioneer 10 and 11 meteoroid measurement enigma

Experimental results from the three dust experiments on the Pioneer 11 and 12 spacecraft are used here to define the distribution and structural characteristics of what is believed to be the dominant population of meteoroids in the inner solar system. No two experiments agreed on the dust distribution and only the Imaging Photopolarimeter experiment could be fitted to the prevailing model of dust spiraling inward from the asteroid belt. Meteoroid Detection Experiment data showed a nearly constant flux from 1 to 18 AU. Reexamination of Asteoroid/Meteoroid Experiment or 'Sisyphus' data shows that the instrument measured a population of long-period meteoroids called cosmoids, composed mainly of water which dominates the dust distribution. Once the prevailing short period dust model is discounted, the results from the three instruments are shown to agree.

Dubin, Maurice↗
NASA NTRS1982

Pioneer 10/11 data analysis of the trapped radiation experiment

The data handling operations and the database produced by the Trapped Radiation Experiment on the NASA Pioneer 10 and 11 spacecraft are outlined. In situ measurements of trapped radiation at both Jupiter and Saturn, the extension of cosmic ray observations to the outer heliosphere, the presence of Jovian electrons in interplanetary space, analyses of the interaction between planetary satellites and the trapped radiation that engulfs them, and further investigations of the radiation enviroments of both planets are reported.

Fillius, W.↗
NASA NTRS1975

Skylab program: Earth resources experiment package. Sensor performance evaluation. Volume 6: (S194) L-band radiometer

Analysis of the Skylab S194 L-band radiometer experiment data provided significant results pertaining to the actual realized performance during flight. Analysis of preflight test data provided a baseline from which to compare the experiment flight performance, although many radiometric data performance capabilities could only be demonstrated in the flight environment. The final results establish the overall hardware performance of the S194 system from which prospective users of the flight data can refer for various scientific applications. Instrument performance is presented in the areas of housekeeping and internal calibration parameters, antenna system integrity, dynamic range, linearity, precision, resolution, and absolute accuracy. Supplementary evaluations were included for an error analysis of system calibration stability. Results of the evaluation show that the instrument performance was generally as expected. Conclusions are drawn from the final evaluation results, and recommendations for improving the effectiveness of a future program are offered.

Kenney, G. P.↗
NASA NTRS1984

Project Explorer: Get Away Special #007

Tentatively scheduled to fly on STS-17 (41G), this get away special aims to demonstrate amateur radio transmissions to global ground stations in the English language. Experiments No. 1, 2, and 3 use the micro-gravity of space flight to study the solidification of lead-antimony and aluminum-copper alloys, the germination of radish seeds, and the growth of potassium-tetracyanoplatinate hydrate crystals in an aqueous solution. Flight results are to be compared with Earth-based data. Experiment No. 4 (the Marshall Amateur Radio Club Experiment - MARCE) features radio transmissions and also provides timing for the start of all other experiments. A microprocessor obtains real-time data from all experiments as well as temperature and pressure measurements within the GAS canister. These data are to be transmitted on previously announced amateur radio frequencies after they are converted into the English language by a digitalker for general reception. The support structure for the G #007 experiments consists of two primary plates and four bumper assemblies.

Henderson, A. J., Jr.↗
NASA NTRS1975

Data for NASA's AVE 4 experiment: 25-mb sounding data and synoptic charts

The AVE 4 Experiment is described and tabulated rawinsonde data at 25-mb intervals from the surface to 25 mb for the 42 stations participating in the experiment are presented. Soundings were taken between 0000 GMT, April 24 and 1200 GMT, April 25, 1975. The methods of data processing and accuracy are discussed. Synoptic charts prepared from the data are presented, as well as an example of contact data.

Fucik, N. F.↗
NASA NTRS1977

Data for NASA's AVE 5 experiment: 25 mb sounding data and synoptic charts

The AVE V Experiment is described and tabulated rawinsonde data at 25-mb intervals from the surface to 25 mb for the 23 stations participating in the experiment are presented. Soundings were taken between 0000 GMT, June 11, and 1200 GMT, June 12, 1976. The methods of data processing and accuracy are briefly discussed. An example of contact data is also included.

Humbert, M. E.↗
NASA NTRS1977

Data for NASA's AVE 6 experiment: 25-mb sounding data and synoptic charts

The Atmospheric Variability Experiments 6 experiment is described, and tabulated rawinsonde data at 25-mb intervals from the surface to 25 mb for the 22 stations participating in the experiment is presented. Soundings were taken between 0000 GMT 27 May and 1200 GMT 28 May 1977. The methods of data processing and their accuracy are briefly discussed. Synoptic charts prepared from the data are presented together with an example of contact data.

Dupuis, L. R.↗
DOE OSTI2022

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1976

Data for NASA's AVE 4 experiment: 25 mb sounding data and synoptic charts

The AVE IV Experiment is described and tabulated rawinsonde data at 25 mb intervals from the surface to 25 mb for the 42 stations participating in the experiment are presented. Soundings were taken between 0000 GMT, April 24, and 1,200 GMT, April 25, 1975. The methods of data processing and accuracy are briefly discussed. Synoptic charts prepared from the data are presented, as well as an example of contact data.

Fucik, N. F.↗
NASA NTRS1976

Data for NASA's AVSSE 2 experiment: 25 mb sounding data and synoptic charts

The AVSSE II experiment is described and tabulated rawinsonde data at 25 mb intervals from the surface to 25 mb for the 23 stations participating in the experiment are presented. Soundings were taken between 1,200 GMT, May 6, and 1,200 GMT, May 7, 1975. The methods of data processing and accuracy are briefly discussed. Synoptic charts prepared from the data are presented, as well as an example of contact data.

Fucik, N. F.↗
NASA NTRS1976

Data for NASA's AVSSE 1 Experiment: 25 Mb Sounding Data and Synoptic Charts

The AVSSE 1 Experiment is described and tabulated rawinsonde data at 25 mb intervals from the surface to 25 mb are presented for the 24 stations participating in the experiment. Soundings were taken between 1,200 GMT, April 27, and 1,200 GMT, April 28, 1975. The methods of data processing and accuracy are briefly discussed. Synoptic charts prepared from the data are presented, as well as an example of contact data.

Fucik, N. F.↗
NASA NTRS1975

Data for NASA's AVSSE 1 experiment: 25-mb sounding data and synoptic charts

The AVSSE I Experiment and is described tabulated rawinsonde data is presented for 25-mb intervals from the surface to 25mb for the 24 stations participating in the experiment. Soundings were taken between 1200 GMT, April 27, and 1200 GMT, April 28, 1975. Brief discussions are given on the methods of data processing and accuracy. Synoptic charts prepared from the data are presented, as well as an example of contact data.

Fucik, N. F.↗