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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The ACRIM data in the context of stellar variability

The Active Cavity Radiometer Irradiance Monitor (ACRIM) total-irradiance data from the Solar Maximum Mission have given a first comprehensive view of solar variability in the stellar sense. Five types of solar variability have been identified thus far. These have small amplitudes, less than a few tenths of one percent, and are at levels generally not yet detectable on other stars. The possible stellar analogs are interesting physically, and in particular may help us to understand solar behavior on longer time scales. The ACRIM data is described from the stellar point of view. The present state of stellar time-series photometry is discussed.

Hudson, Hugh S.↗
NASA NTRS2003

Compressing Aviation Data in XML Format

Design, operations and maintenance activities in aviation involve analysis of variety of aviation data. This data is typically in disparate formats making it difficult to use with different software packages. Use of a self-describing and extensible standard called XML provides a solution to this interoperability problem. XML provides a standardized language for describing the contents of an information stream, performing the same kind of definitional role for Web content as a database schema performs for relational databases. XML data can be easily customized for display using Extensible Style Sheets (XSL). While self-describing nature of XML makes it easy to reuse, it also increases the size of data significantly. Therefore, transfemng a dataset in XML form can decrease throughput and increase data transfer time significantly. It also increases storage requirements significantly. A natural solution to the problem is to compress the data using suitable algorithm and transfer it in the compressed form. We found that XML-specific compressors such as Xmill and XMLPPM generally outperform traditional compressors. However, optimal use of Xmill requires of discovery of optimal options to use while running Xmill. This, in turn, depends on the nature of data used. Manual disc0ver.y of optimal setting can require an engineer to experiment for weeks. We have devised an XML compression advisory tool that can analyze sample data files and recommend what compression tool would work the best for this data and what are the optimal settings to be used with a XML compression tool.

Patel, Hemil↗
DOE OSTI2023

Bayesian optimal experimental design for constitutive model calibration

Computational simulation is increasingly relied upon for high/consequence engineering decisions, which necessitates a high confidence in the calibration of and predictions from complex material models. However, the calibration and validation of material models is often a discrete, multi-stage process that is decoupled from material characterization activities, which means the data collected does not always align with the data that is needed. To address this issue, an integrated workflow for delivering an enhanced characterization and calibration procedure—Interlaced Characterization and Calibration (ICC)—is introduced and demonstrated. Further, this framework leverages Bayesian optimal experimental design (BOED), which creates a line of communication between model calibration needs and data collection capabilities in order to optimize the information content gathered from the experiments for model calibration. Eventually, the ICC framework will be used in quasi real-time to actively control experiments of complex specimens for the calibration of a high-fidelity material model. This work presents the critical first piece of algorithm development and a demonstration in determining the optimal load path of a cruciform specimen with simulated data. Calibration results, obtained via Bayesian inference, from the integrated ICC approach are compared to calibrations performed by choosing the load path a priori based on human intuition, as is traditionally done. The calibration results are communicated through parameter uncertainties which are propagated to the model output space (i.e. stress–strain). In these exemplar problems, data generated within the ICC framework resulted in calibrated model parameters with reduced measures of uncertainty compared to the traditional approaches.

42 ENGINEERING↗
NASA NTRS2013

Global Data Assembly Center (GDAC) Report to the GHRSST Science Team

In 2012-2013 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational GHRSST data streams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Our presentation reported on our data management activities and infrastructure improvements since the last science team meeting in 2012.

user reports↗
NASA NTRS2005

Thermal Emission Variability of Zamama, Culann and Tupan on Io Using Galileo Near-Infrared Mapping Spectrometer (NIMS) Data

The Jovian satellite Io is the most volcanically active body in the Solar System. Previous analyses [e.g., 1-4] indicate the presence of high-temperature silicate volcanism on Io, similar to silicate volcanism occurring on Earth. Instruments onboard the Galileo spacecraft, especially the Near Infrared Mapping Spectrometer (NIMS) and the Solid State Imager (SSI), provided much data of Io s active volcanoes throughout the duration of the Galileo mission (June 1996-September 2003). NIMS data is particularly sensitive to thermal emission from active and cooling lava over cooling times of seconds to a few years. The objective of this ongoing study of Io s volcanism is to determine the variability of thermal emission from volcanoes on Io s surface, in order to better understand the styles of eruption, and to constrain the volumes of material erupted. Ultimately, this will help to constrain the contribution of active volcanism to Io s thermal budget. Data have been analyzed for the volcano Zamama, located at 173 W, 21 N, and the power output of Zamama, the volumes of lava being erupted, and the eruption rate determined. Culann and Tupan have also been analysed in this way. This abstract primarily concentrates on Zamama.

Ennis, M. E.↗
DOE OSTI2021

Time-temperature-superposition analysis of diverse datasets by the minimum-arclength method: long-term prediction with uncertainty margins

In a recent publication, we carried out an extensive analysis of an unsupervised method of determining optimum shift factors in time-temperature-superposition of accelerated-aging data that involves minimizing the vertical arclength to obtain the master curve. For synthetic Arrhenius data with a variety of noise distributions, the work showed that, in conjunction with bootstrap-resampling, the method can produce reliable estimates of the mean activation energy along with uncertainty quantification. Here, we apply the above method to six different datasets taken from the published literature and demonstrate accurate prediction of mean activation energy from the data as-is without the need for any pre-processing or fitting. We also compare uncertainty margins computed by second-order bootstrap with that by linear regression theory and show that the former appears to provide consistent margins in the presence of common noise types in real data, including intra-isotherm measurement-errors, sample-to-sample variations, and intrinsic deviation from perfect Arrhenius behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The aryl hydrocarbon receptor suppresses osteoblast proliferation and differentiation through the activation of the ERK signaling pathway

Ahr activation is known to be associated with synovitis and exacerbated rheumatoid arthritis (RA), but its contributions to bone loss have not been completely elucidated. Osteoblast proliferation and differentiation are abnormal at the erosion site in RA. Here, we reported that the expression of Ahr was increased in the hind paws' bone upon collagen-induced arthritis (CIA) in mice, and the levels of Ahr were negatively correlated with bone mineral density (BMD). In addition, immunofluorescent staining showed that the high expression of Ahr was mainly localized in osteoblasts from the CIA mice compared to normal controls. Moreover, the luciferase intensity of Ahr in the nucleus increased by 12.5% in CIA osteoblasts compared to that in normal controls. In addition, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) activation of the Ahr inhibited pre-osteoblast MC3T3-E1 cellular proliferation and differentiation in a dose-dependent manner. Interestingly, the levels of alkaline phosphatase (ALP) mRNA expression in the osteoblasts of CIA mice were reduced compared to normal controls. In contrast, decreased ALP expression by activated Ahr was completely reversed after pretreatment with an Ahr inhibitor (CH-223191) in MC3T3-E1 cell lines and primary osteoblasts on day 5. Our data further showed that activation of Ahr promoted the phosphorylation of ERK after 5 days. Moreover, Ahr-dependent activation of the ERK signaling pathway decreased the levels of proliferation cells and inhibited ALP activity in MC3T3-E1 cells. These results demonstrated that the high expression of Ahr may suppress osteoblast proliferation and differentiation through activation of the ERK signaling pathway, further enabling bone erosion in CIA mice. - Highlights: • The upregulation of Ahr was localized in osteoblasts of CIA mice. • The overexpression of Ahr suppressed osteoblast development. • The Ahr activated ERK signaling pathway to exacerbate bone erosion.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1983

On possible correlations in the photospheric magnetic field

A correlation analysis is performed upon the rate of change of the photospheric magnetic field in the north and south hemispheres of the sun. Both active region logs and data obtained from the daily Mount Wilson magnetograms are employed, and the analysis is performed for all available days, as well as for days in which active regions are near central meridian. The result of the analysis shows no correlation between these changes and it is concluded that local convective turbulence is more important than dynamo processes with regard to the appearance of individual active regions.

Wallenhorst, S. G.↗
NASA NTRS1985

Solar-geophysical data number 494, October 1985, Part 2: (Comprehensive reports). Data for April 1985, January-June 1984 and miscellanea

Contents include: detailed index for 1985; data for April 1985 (Meudon carte synoptique, solar radio bursts at fixed frequencies, solar X-ray radiation form GOES satellite, mass ejections from the sun, active prominences and filaments); data for January to June 1984 (solar flares January 1984, solar flares February 1984, solar flares March l984, solar flares April 1984, solar flares May 1984, solar flares June 1984, and number of flates August 1966 to June 1984); and miscellaneous data (interplanetary solar wind July 1984 to March 1985, errata solar X-rays event list January 1985).

Coffey, H. E.↗
NASA NTRS1998

An emerging network storage management standard: Media error monitoring and reporting information (MEMRI) - to determine optical tape data integrity

Sophisticated network storage management applications are rapidly evolving to satisfy a market demand for highly reliable data storage systems with large data storage capacities and performance requirements. To preserve a high degree of data integrity, these applications must rely on intelligent data storage devices that can provide reliable indicators of data degradation. Error correction activity generally occurs within storage devices without notification to the host. Early indicators of degradation and media error monitoring 333 and reporting (MEMR) techniques implemented in data storage devices allow network storage management applications to notify system administrators of these events and to take appropriate corrective actions before catastrophic errors occur. Although MEMR techniques have been implemented in data storage devices for many years, until 1996 no MEMR standards existed. In 1996 the American National Standards Institute (ANSI) approved the only known (world-wide) industry standard specifying MEMR techniques to verify stored data on optical disks. This industry standard was developed under the auspices of the Association for Information and Image Management (AIIM). A recently formed AIIM Optical Tape Subcommittee initiated the development of another data integrity standard specifying a set of media error monitoring tools and media error monitoring information (MEMRI) to verify stored data on optical tape media. This paper discusses the need for intelligent storage devices that can provide data integrity metadata, the content of the existing data integrity standard for optical disks, and the content of the MEMRI standard being developed by the AIIM Optical Tape Subcommittee.

Podio, Fernando↗
NASA NTRS2004

Agent Architecture for Aviation Data Integration System

This paper describes the proposed agent-based architecture of the Aviation Data Integration System (ADIS). ADIS is a software system that provides integrated heterogeneous data to support aviation problem-solving activities. Examples of aviation problem-solving activities include engineering troubleshooting, incident and accident investigation, routine flight operations monitoring, safety assessment, maintenance procedure debugging, and training assessment. A wide variety of information is typically referenced when engaging in these activities. Some of this information includes flight recorder data, Automatic Terminal Information Service (ATIS) reports, Jeppesen charts, weather data, air traffic control information, safety reports, and runway visual range data. Such wide-ranging information cannot be found in any single unified information source. Therefore, this information must be actively collected, assembled, and presented in a manner that supports the users problem-solving activities. This information integration task is non-trivial and presents a variety of technical challenges. ADIS has been developed to do this task and it permits integration of weather, RVR, radar data, and Jeppesen charts with flight data. ADIS has been implemented and used by several airlines FOQA teams. The initial feedback from airlines is that such a system is very useful in FOQA analysis. Based on the feedback from the initial deployment, we are developing a new version of the system that would make further progress in achieving following goals of our project.

Kulkarni, Deepak↗
DOE OSTI2017

Clean Energy Innovation Ecosystems Discovery - Measuring Innovation Through Data Analytics (MIDAS)

As part of the Mission Innovation rollout at the Paris COP 21, 20 countries announced to double their R&D budgets over 5 years to accelerate lab-to-market clean energy innovations. These innovations must address technical urgency and navigate complex institutional, social and financial environments. To inform budget and program development, policymakers need to understand existing clean energy innovation ecosystems (IE) and their characteristics at the local, state, and regional levels within the US. Researchers at ORNL have implemented a ground-breaking application of natural language processing, link analysis, and other computational techniques to transform text and numerical data into metrics on clean energy innovation activity and geography. The 'Measuring Innovation through Data Analytics' (MIDAS) application uses data to determine where clean energy innovation ecosystems exist and the underlying scoring algorithm "ranks" the strength of the ecosystem for several clean energy technologies. The selection of the data sources is driven by the fact that a clean energy IE can be identified as an intersection of nascent clean technology efforts and financing mechanisms and related large companies located in a geographically concentrated area with an enabling environment to encourage commercialization and networking assets to facilitate communication. MIDAS is a machine-assisted methodology that provides the user with a replicable method to rapidly identify, quantify and characterize clean energy innovation ecosystems. This software application and the underlying datasets have the potential to address many important policy questions. The initial broad list of U.S. clean energy ecosystems, with geographic area, technology focus, and list and types of involved organizations can help describe regional tech activities and capabilities. Other potential applications include understanding the effect of private sector investments on ecosystem activity, and trends analysis.

Chinthavali, Supriya↗
DOE OSTI2015

Structure sensitivity in oxide catalysis: First-principles kinetic Monte Carlo simulations for CO oxidation at RuO{sub 2}(111)

We present a density-functional theory based kinetic Monte Carlo study of CO oxidation at the (111) facet of RuO{sub 2}. We compare the detailed insight into elementary processes, steady-state surface coverages, and catalytic activity to equivalent published simulation data for the frequently studied RuO{sub 2}(110) facet. Qualitative differences are identified in virtually every aspect ranging from binding energetics over lateral interactions to the interplay of elementary processes at the different active sites. Nevertheless, particularly at technologically relevant elevated temperatures, near-ambient pressures and near-stoichiometric feeds both facets exhibit almost identical catalytic activity. These findings challenge the traditional definition of structure sensitivity based on macroscopically observable turnover frequencies and prompt scrutiny of the applicability of structure sensitivity classifications developed for metals to oxide catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A 1 km soil moisture dataset over eastern CONUS generated by assimilating SMAP data into the Noah-MP land surface model

An improved fine-scale soil moisture (SM) dataset at 1 km grid spacing, covering much of the eastern continental US, was generated by assimilating 9 km Soil Moisture Active Passive (SMAP) SM data into the v4.0.1 Noah-MP land surface model. With 12 ensemble members, the assimilation was carried out using the ensemble Kalman filter algorithm within NASA's Land Information System. The SM analysis for 2016 was fully validated against in situ observations from four different networks and compared with four other existing datasets. Results indicate that this SM analysis surpasses other datasets in top-layer SM distribution, including a machine-learning-based product, despite all SM estimates being less heterogeneous than observed. The analysis of anomalous errors suggests that large similarity in intrinsic errors is likely due to overlapping data sources among the selected SM datasets. More detailed evaluations were performed over two geographic areas. The observations collected by the Atmospheric Radiation Measurement facility in Oklahoma suggest that soil temperature and surface heat fluxes are concurrently simulated with good accuracy. Investigation into the 2016 southeastern US drought response further indicates drier conditions and higher evapotranspiration estimates compared to GLEAMv4.1. Notably, large errors are associated with grids having clay soil textures, underscoring the need for refined model treatments for specific soil types to further improve SM estimates. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.14370563 (Tai et al., 2024).

Tai, Sheng-Lun [Pacific Northwest National Laborat↗
NASA NTRS1999

Autonomous Science Decision Making for Mars Sample Return

In the near future NASA intends to explore Mars in preparation for a sample return mission using robotic devices such as landers, rovers, orbiters, airplanes, and/or balloons. Such platforms will likely carry imaging devices to characterize the surface morphology, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved the following sequence of activities: (1) return of scientific data from the vehicle; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) transmission of commands to the vehicle to achieve this activity; and (5) new activity by the vehicle in response to those commands. This is repeated for the duration of the mission, with command opportunities once or perhaps twice per day. In a rapidly changing environment, such as might be encountered by a rover traversing hundreds of meters a day or an airplane soaring over several hundred of kilometers, this traditional cycle of data evaluation and commands is not amenable to rapid long range traverses, discovery of novelty, or rapid response to any unanticipated situations. In addition, to issues of response time, the nature of imaging and/or spectroscopic devices are such that tremendous data volumes can be acquired, for example during a traverse. These data volumes can rapidly exceed on-board memory capabilities prior to an opportunity to transmit it to Earth.

Roush, Ted L.↗
NASA NTRS1991

Data evaluation, analysis, and scientific study

Extensive work was performed in data analysis and modeling of solar active phenomena. The work consisted in the study of UV data from the Ultraviolet Spectrometer and Polarimeter (UVSP) instrument on board the Solar Maximum Mission satellite. These data were studied in conjunction with X-rays from the Hard X-ray Imaging Spectrometer (HXIS) instrument, and with H-alpha and magnetographic data from ground-based observatories. The processes we studied are the active phenomena which result from the interaction of the solar magnetic fields with the plasma in the outer regions of the solar atmosphere. These processes include some very dynamic processes such as the prominence eruptions and the 'microflares'. Our research aimed at characterizing the following: the observed phenomena, the possible physical models, and the relevance to the chromospheric and coronal heating.

Wu, S. T.↗
DOE OSTI2015

Effect of diosgenin on metabolic dysfunction: Role of ERβ in the regulation of PPARγ

The present study was designed to investigate the effect of diosgenin (DSG) on metabolic dysfunction and to elucidate the possible molecular mechanisms. High fat (HF) diet-fed mice and 3T3-L1 preadipocytes was used to evaluate the effect of DSG. We showed that DSG attenuated metabolic dysfunction in HF diet-fed mice, as evidenced by reduction of blood glucose level and improvement of glucose and insulin intolerance. DSG ameliorated oxidative stress, reduced body weight, fat pads, and systematic lipid profiles and attenuated lipid accumulation. DSG inhibited 3T3-L1 adipocyte differentiation and reduced adipocyte size through regulating key factors. DSG inhibited PPARγ and its target gene expression both in differentiated 3T3-L1 adipocytes and fat tissues in HF diet-fed mice. Overexpression of PPARγ suppressed DSG-inhibited adipocyte differentiation. DSG significantly increased nuclear expression of ERβ. Inhibition of ERβ significantly suppressed DSG-exerted suppression of adipocyte differentiation and PPARγ expression. In response to DSG stimulation, ERβ bound with RXRα and dissociated RXRα from PPARγ, leading to the reduction of transcriptional activity of PPARγ. These data provide new insight into the mechanisms underlying the inhibitory effect of DSG on adipocyte differentiation and demonstrate that ERβ-exerted regulation of PPARγ expression and activity is critical for DSG-inhibited adipocyte differentiation. - Highlights: • Diosgenin (DSG) attenuated metabolic dysfunction in high fat (HF) diet-fed mice. • DSG reduced oxidative stress and lipid accumulation in HF diet-fed mice. • DSG inhibited 3T3-L1 adipocyte differentiation and reduced adipocyte size. • DSG induced the binding of ERβ with RXRα. • DSG-induced activation of ERβ dissociated RXRα from PPARγ and reduced PPARγ activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Septin 7 reduces nonmuscle myosin IIA activity in the SNAP23 complex and hinders GLUT4 storage vesicle docking and fusion

Glomerular epithelial cells, podocytes, are insulin responsive and can develop insulin resistance. Here, we demonstrate that the small GTPase septin 7 forms a complex with nonmuscle myosin heavy chain IIA (NMHC-IIA; encoded by MYH9), a component of the nonmuscle myosin IIA (NM-IIA) hexameric complex. We observed that knockdown of NMHC-IIA decreases insulin-stimulated glucose uptake into podocytes. Both septin 7 and NM-IIA associate with SNAP23, a SNARE protein involved in GLUT4 storage vesicle (GSV) docking and fusion with the plasma membrane. We observed that insulin decreases the level of septin 7 and increases the activity of NM-IIA in the SNAP23 complex, as visualized by increased phosphorylation of myosin regulatory light chain. Also knockdown of septin 7 increases the activity of NM-IIA in the complex. The activity of NM-IIA is increased in diabetic rat glomeruli and cultured human podocytes exposed to macroalbuminuric sera from patients with type 1 diabetes. Collectively, the data suggest that the activity of NM-IIA in the SNAP23 complex plays a key role in insulin-stimulated glucose uptake into podocytes. Furthermore, we observed that septin 7 reduces the activity of NM-IIA in the SNAP23 complex and thereby hinders GSV docking and fusion with the plasma membrane. - Highlights: • Septin 7, nonmuscle myosin heavy chain IIA (NMHC-IIA) and SNAP23 form a complex. • Knockdown of septin 7 increases NM-IIA activity in the SNAP23 complex. • Insulin decreases septin 7 level and increases NM-IIA activity in the SNAP23 complex. • Septin 7 hinders GSV docking/fusion by reducing NM-IIA activity in the SNAP23 complex.

60 APPLIED LIFE SCIENCES↗