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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 433 records · Page 24

Scientific and technical services directed toward the development of planetary quarantine measures for automated spacecraft

Planetary quarantine requirements and parameters are evaluated for their effects upon automated spacecraft flights data describing the heat resistance of naturally occuring microorganisms and sterilization requirements are analyzed and a possible method for assessment of these data is developed. Pertinent data from planetary mission microbial contamination logs are compiled and maintained in the quarantine document system.

Source record↗

Frequency of gamma-ray bursts greater than 3 x 10 to the -6th erg/sq cm

Results are presented for gamma-ray burst observations with the Large Area Sky Survey instrument on HEAO-1. It is noted that during the time HEAO-1 was operational, the instrument detected at least 12 confirmed gamma-ray bursts with intensities greater than 3 microerg/sq cm and identified six additional unconfirmed bursts. The rates of gamma-ray bursts are estimated to be about 125 per yr for intensities greater than 3 microerg/sq cm and approximately 50 per yr for intensities greater than 10 microerg/yr. The data are shown to yield a log N - log S relation for gamma-ray bursts that is consistent with a spherical distribution of sources within the Galaxy and having a broad range of intrinsic luminosities.

Share, G. H.↗

Compositional trends and cooling rates of group IVB iron meteorites

It is found, on the basis of new neutron activation data for group IVB, that log-element - log-Ni trends are best understood in terms of core formation and fractional crytstallizaion. The limited compositional range found in gorup IVB is thought to reflect the fact that, owing to the low concentrations of S, P, and C and the high concentration of Ni, the k sub x (the solid/liquid partition ratio) values are closer to unity than are those in other magmatic groups. Mean volatile abundances in group IVB are significantly lower than those found in any group of chondritic meteorites, indicating that these low abundances are not entirely the result of nebular processes and that planetary outgassing was also involved.

Rasmussen, K. L.↗

Blockchain Application Within a Multi-Sensor Satellite Architecture

With the thrust towards multi-sensor satellite architectures for earth and space exploration, such as constellations and swarms, new technologies are required to enable the transition to this future capability. One of the areas of interest is establishing secure, efficient and prioritized data and command communication pathways among ground and space-based sources for such systems. This paper presents early research results on the potential role, capabilities and value of blockchain usage within constellation and swarm satellite architectures. It demonstrates the use of blockchain's smart contract and distributed ledger capabilities for secure and prioritized multi-sensor satellite collaborative data exchanges, as well as the logging and tracking of command and control events. Adapting and utilizing this emerging technology will aid in addressing technology gaps expected from future constellation flight architectures, such as managing collective computational operations (correlation), dynamic and autonomous observation planning, time-critical events, and provenance tied to ground and space-based autonomous operations and control recordkeeping. In this scenario blockchain is applied in encrypted command transmittal to multiple, yet specific, entities enabling acknowledgement transmittals, performance scalability, and automatic event-based triggering.

Mital, Rohit↗

Structured Covariance Gaussian Networks for Orion Crew Module Aerodynamic Uncertainty Quantification

In this paper we propose a new approach for nonlinear regression and uncertainty quantification. The method is based on a pair of neural networks which parameterize mean and dense covariance functions of a multivariate Gaussian process, trained together to maximize the log-likelihood of observing the given data. The covariance matrix is made positive definite at every input by construction. We also propose a sampling approach that produces viable surrogate function realizations from the Gaussian process. We call the proposed model a Structured Covariance Gaussian Network (SCGN). We illustrate the use of SCGNs for learning an aerodynamic response surface with built-in uncertainty for the Orion crew module. We find that SCGN provides an efficient and systematic way to learn nonlinear functional relationships and dense covariances. We compare results to a baseline Gaussian process regressor and observe that the SCGN provides comparable uncertainty descriptions with improved scalability to dataset size. The sample functions generated by SCGN are fast to evaluate online and are therefore convenient for use in trajectory simulations. These results suggest that SCGN may be a viable computational method for aerodynamic uncertainty quantification.

machine learning↗

Structured Covariance Gaussian Networks for Orion Crew Module Aerodynamic Uncertainty Quantification

In this paper we propose a new approach for nonlinear regression and uncertainty quantification. The method is based on a pair of neural networks which parameterize mean and dense covariance functions of a multivariate Gaussian process, trained together to maximize the log-likelihood of observing the given data. The covariance matrix is made positive definite at every input by construction. We also propose a sampling approach that produces viable surrogate function realizations from the Gaussian process. We call the proposed model a Structured Covariance Gaussian Network (SCGN). We illustrate the use of SCGNs for learning an aerodynamic response surface with built-in uncertainty for the Orion crew module. We find that SCGN provides an efficient and systematic way to learn nonlinear functional relationships and dense covariances. We compare results to a baseline Gaussian process regressor and observe that the SCGN provides comparable uncertainty descriptions with improved scalability to dataset size. The sample functions generated by SCGN are fast to evaluate online and are therefore convenient for use in trajectory simulations. These results suggest that SCGN may be a viable computational method for aerodynamic uncertainty quantification.

machine learning↗

Metadata compression

A computer-executable method, system, and computer program product for managing a Parallel-Logged File System (PLFS) on a data storage system, wherein the data storage system is in communication with an application that updates the data storage system with checkpoint data, the computer-executable method, system, and computer program product comprising receiving a first checkpoint including data from the application; analyzing the data in the first checkpoint to determine whether a pattern exists in the checkpoint data; and upon a positive determination, adding the pattern into PLFS.

97 MATHEMATICS AND COMPUTING↗

A Unique Facility For Metabolic and Thermoregulatory Studies

A unique exercise facility has been developed and used to perform tipper body ergometry tests for space applications. Originally designed to simulate the muscular, cardiovascular and thermoregulatory responses to working in zero gravity, this facility may be used to conduct basic thermoregulatory investigations applicable to multiple sclerosis patients. An environmental chamber houses the tipper body ergometer and permits control of temperature, air now and humidify. The chamber is a closed system and recirculate-s air after conditioning if. A Cybex Lipper body ergometer has been mounted horizontally on the wall of the environmental chamber. In this configuration, the subject lies underneath the arm crank on a supine seat in order to turn the crank. The supine seat can be removed in order to introduce other equipment into the chamber such as a stool to allow upright arm cranking, or a treadmill to allow walk-run experiments. Physiological and environmental signals are fed into a Strawberry Tree data acquisition system while being monitored and logged using the Workbench software program. Physiological monitoring capabilities include 3-lead EKG using an H-P patient monitor, 5 site skin temperature and core temperature using YSI thermistors, and O2 consumption and CO2 production using AMFTFK Applied Electrochemistry analyzers and sensors. This comprehensive data acquisition set tip allows for calculation of various thermoregulatory indices including heat storage, evaporative heat loss, latent heat loss, and metabolic rate. The current system is capable of adding more data acquisition channels if needed. Some potential studies that could be carried out using the facility include: 1) An investigation into the efficiency of cooling various segments of the body to lower Tc 1-2 F. 2) A series of heat and mass balance studies comparing various LCG configurations.

Williamson, Rebecca C.↗

Measured oxygen fugacities of the Angra dos Reis achondrite as a function of temperature

Measurements of the oxygen fugacity, f(O2), as a function of temperature, T, were made on an interior bulk sample of the cumulate achondrite, Angra dos Reis. Data clustered between the f(O2)-T relationship of the iron-wustite assemblage and 1.2 log atm units above iron-wustite. Interpretation of the data indicates that, throughout most of the cooling history of the meteorite, f(O2) values were defined by equilibria involving iron-bearing species at values close to the f(O2) of the assemblage iron-wustite. Measured f(O2) data are compatible with crystallization and cooling at pressures greater than 50 bars.

Brett, R.↗

Curifactory: A research experiment manager

Curifactory is a command line tool and framework for organizing Python experiment code, configuration parameters, and results. It is an opinionated and lightweight approach to workflow management infrastructure and is primarily intended to support researchers conducting experiments on one machine. This software was developed to support the reproducibility of results for several data science projects in the Nuclear Nonproliferation Division at Oak Ridge National Laboratory. Curifactory is intended to be a general framework and is not specific to machine learning or data science. It can aid in any field in which experiments are primarily computation-based studies and can be implemented in Python (e.g., high-energy physics, astronomy, computational chemistry). Here, the design emphasizes the automated caching of intermediate data analysis artifacts to speed up development involving computationally intensive tasks. It also allows for data provenance and experiment reproduction. Individual experiment runs are tracked through logs and their output reports, and entire copies of a run with all cached data and metadata can be exported for others to run using Curifactory on another machine. Curifactory experiments can either be integrated into a project from the beginning or can be written on top of an existing codebase without needing significant modification. A few important views of the Curifactory library can be seen in Figure 1.

97 MATHEMATICS AND COMPUTING↗

An Exceptionally Powerful, Radiatively Driven Ultrafast Outflow in the Rapidly Accreting AGN RE J1034+396

We report the analysis of ∼1 Ms of XMM-Newton observations of the rapidly accreting active galactic nucleus RE J1034+396. The 0.3–9 keV EPIC-pn spectra are well described by a model consisting of steep continuum emission from the corona accompanied by relativistically blurred reflection from a highly ionized accretion disk. The source is known to exhibit strong excess soft X-ray emission, which we show is well represented by thermal disk photons Comptonized by a warm plasma spanning the inner accretion flow. Additionally, the EPIC-pn data provide compelling evidence (ΔC ∼ 60 for four additional parameters) for the presence of an ultrafast outflow (UFO) with a line-of-sight velocity v/c = 0.307$^{+0.001}_{-0.005}$, and an emission signature consistent with reflection of the corona from modestly ionized, outflowing gas. The simultaneous 0.5–2.5 keV RGS spectra show clear absorption lines. Modelling of these data confirms the presence of the UFO and constrains its equivalent hydrogen column density, log N H /(atom cm −2 ) = 21.7$^{+0.1}_{-0.2}$. The RGS data also reveal at least two warm absorber components with a modest outflow velocity (1680$^{+40}_{-50}$ km s -1 ). The measured properties and time evolution of the UFO in RE J1034+396 suggest that it is formed from collisionally ionized plasma, launched from the disk surface and accelerated by radiation pressure. The high terminal velocity and substantial absorbing column density imply that the outflow carries sufficient momentum and energy to transform its environment, being capable of driving out essentially all dust and gas it interacts with along the line of sight, even if the AGN were initially surrounded by a Compton-thick absorber.

79 ASTRONOMY AND ASTROPHYSICS↗

Statistics for ionospherically diffracted VHF/UHF signals.

In this paper, a general characterization of the statistics for an ionospherically diffracted, monochromatic plane wave is presented. The main results are restricted to weak scatter, although two possible extensions that accommodate large phase perturbations and multiple scatter are discussed. A detailed discussion of the first-order statistics of amplitude is given. The general Gaussian distribution is discussed together with its Nakagami-distribution approximation and the log-normal distribution. By using a segment of ATS-3 satellite data recorded at Lima, Peru, we show equally good fits to Gaussian and log-normal distributions at least for the limited dynamic range available. The Nakagami distribution provides only a poor approximation.

Rino, C. L.↗

2000 Knoxville Urban Area Household Travel Behavior Survey

This survey, conducted by NuStats, was a comprehensive study of travel behavior in Knox and Blount counties in the Knoxville urban area. The purpose of the survey was to collect weekday travel characteristics of household members (ages five and older) in the counties during a 24-hour timeframe. The data will be used by the Knoxville Urban Area Metropolitan Planning Organization and local agencies to update transportation and air quality models and to identify transportation needs in the region. The survey was conducted between November 2000 and February 2001. In total, 2,674 households were recruited to participate in the survey. Of these, 1,538 households reported data from a one-day travel log, totaling 12,631 trips by 3,522 persons. Of all trips originating in the study area, three-fourths were made by persons residing in Knox County.

1Hz data↗

Mesoscale variability of free tropospheric humidity near San Nicolas Island during FIRE

Humidity variability at the top of the marine boundary layer (MBL) and in the free troposphere was examined using a variety of measurements taken on and around San Nicolas Island (SNI) during the FIRE IFO in July, 1987. Doppler wind profiler reflectivity recorded at two minute time resolution has provided the most continuous record and detail of small scale humidity fluctuations. Rawinsonde data were available from both an island site and the research vessel Point Sur. The information extractable from these sources is somewhat limited due to the frequency of launches (3 to 4/day at SNI and 6/day on the Point Sur). Some additional data were available from instrumented aircraft although scheduling flights in the neighborhood of the island was difficult due to restrictions on the air space. Other relevant data were collected at SNI near the radar and rawinsonde launch sites. A continuous record of cloud base altitude was logged by a ceilometer. Doppler acoustic sounder (sodar) reflectivity data provided a good record of inversion height. The sodar also monitored turbulent temperature fluctuations in the MBL. A small ground station recorded hourly averages of solar irradiance and downward longwave irradiance. The analysis in progress of the various data sets for two adjacent two day periods from 11 July to 14 July is described. The earlier period was chosen because the marine inversion was unusually high and there was increased frequency of rawinsonde launches at SNI. The later period was chosen because of the significant descent with time of an elevated inversion indicated by the radar data. Throughout the four day period, but especially in the first half, the turbulent humidity structure calculated from Doppler radar reflectivity shows excellent agreement with humidity profiles evaluated from rawinsonde data.

White, A. B.↗

A comprehensive analysis of transient pressure and rate data from CO 2 storage projects in a depleted pinnacle reef oil field complex, Michigan, USA

Pressure and rate data are commonly recorded as part of a basic monitoring program in CCS projects. This paper discusses the application of multiple analytical techniques to interpret pressure and rate transient data from CO 2 injection and storage operations. The techniques of interest, i.e., injection-falloff analysis, injectivity/productivity index analysis and pressure pulse arrival time analysis, are commonly used in the oil and gas industry to assess reservoir properties, but not well known in the CCS literature (especially the last two). Injection-falloff analysis involves log-log pressure derivative plotting for the falloff data and history-matching of the entire injection-falloff sequence to determine permeability. In the injectivity/productivity index analysis, rate-normalized pressure buildup is plotted against material balance time or ratio of cumulative injection to injection rate to determine the injectivity index (ratio of injection rate to stabilized pressure buildup) which can be related to the permeability-thickness product. The arrival time analysis identifies the arrival of a pressure disturbance (~0.1 psi change from ambient) to determine the hydraulic diffusivity from which permeability can be estimated. The applicability of these techniques is demonstrated via illustrative examples from multiple wells in different pinnacle carbonate reefs undergoing CO 2 -EOR in Northern Michigan. The paper ends with a discussion of the relative merits of each interpretive technique, as well as recommendations that could be useful for other field projects.

42 ENGINEERING↗

The Environment for Application Software Integration and Execution (EASIE), version 1.0. Volume 3: Program execution guide

The Environment for Application Software Integration and Execution, EASIE, provides a methodology and a set of software utility programs to ease the task of coordinating engineering design and analysis codes. EASIE was designed to meet the needs of conceptual design engineers that face the task of integrating the results of many stand-alone engineering analysis programs. EASIE provides access to these programs via a quick, uniform, user-friendly interface. In addition, EASIE provides utilities which aid in the execution of the following tasks: selection of application programs, modification and review of program data, automatic definition and coordination of data files during program execution and a logging of steps executed throughout a design study. Volume 3, the Program Execution Guide, describes the executive capabilities provided by EASIE and defines the command language and menus available under Version 1.0. EASIE provides users with two basic modes of operation. One is the Application-Derived Executive (ADE) which provides users with sufficient guidance to quickly review data, select menu action items, and execute application programs. The second is the Complete Control Executive (CCE), which provides a full executive interface allowing users in-depth control of the design process.

Schwing, James L.↗

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Test Logs and Results

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. This data set is described in the "Test Log" excel file. Please refer to that document for details on each specific test date/time, constraint parameters and model hardware setup details. Sim model can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗

Condition-Based Maintenance of a Circulating Water System of a Canadian Nuclear Power Plant using Machine Learning and Statistical Tools

Canada Deuterium Uranium pressurized-heavy-water reactors (PHWR) are a type of nuclear power plant that generate clean and reliable energy. The scope of this work is to automate data analysis methodologies to inform a condition-based maintenance strategy of a circulating water system (CWS) of a PHWR. The multiunit CWS provides a continuous supply of water to cool steam condensers, even during transient scenarios, thereby improving the thermal efficiency. This work aims to develop a machine learning (ML) based approach to detect anomalies in heterogeneous data of a CWS in a PHWR to help inform a predictive maintenance strategy. The heterogeneous data include textual and numeric time series data for a PHWR. Natural-language-processing (NLP)-based models are used to analyze textual data contained in work orders and operator logs and an event-timeseries correlation detection method is applied to assist anomalies diagnoses for CWS. An ML model Robust Linear Model (RLM) is also used to remove the seasonal variations in the system variable distributions based on distributions of environmental variables. A machine learning model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), trained on both original data and data without any seasonal variations will then be used to detect if an anomaly exists. Thus, by moving to an automated methodology to detect, classify, and forecast anomalies, the maintenance strategy would be based on component condition instead of a time-based schedule.

97 - MATHEMATICS AND COMPUTING↗