Search NASA⌕ Search

SEARCH · Search NASA

Results for “potential data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

Backus Effect on a Perpendicular Errors in Harmonic Models of Real vs. Synthetic Data

Measurements of geomagnetic scalar intensity on a thin spherical shell alone are not enough to separate internal from external source fields; moreover, such scalar data are not enough for accurate modeling of the vector field from internal sources because of unmodeled fields and small data errors. Spherical harmonic models of the geomagnetic potential fitted to scalar data alone therefore suffer from well-understood Backus effect and perpendicular errors. Curiously, errors in some models of simulated 'data' are very much less than those in models of real data. We analyze select Magsat vector and scalar measurements separately to illustrate Backus effect and perpendicular errors in models of real scalar data. By using a model to synthesize 'data' at the observation points, and by adding various types of 'noise', we illustrate such errors in models of synthetic 'data'. Perpendicular errors prove quite sensitive to the maximum degree in the spherical harmonic expansion of the potential field model fitted to the scalar data. Small errors in models of synthetic 'data' are found to be an artifact of matched truncation levels. For example, consider scalar synthetic 'data' computed from a degree 14 model. A degree 14 model fitted to such synthetic 'data' yields negligible error, but amplifies 4 nT (rmss) added noise into a 60 nT error (rmss); however, a degree 12 model fitted to the noisy 'data' suffers a 492 nT error (rmms through degree 12). Geomagnetic measurements remain unaware of model truncation, so the small errors indicated by some simulations cannot be realized in practice. Errors in models fitted to scalar data alone approach 1000 nT (rmss) and several thousand nT (maximum).

Voorhies, C. V.↗

Metabolome of human gut microbiome is predictive of host dysbiosis

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

human microbiome↗

An instrument thermal data base system

The rationale for the implementation of an Instrument Thermal Data Base System (ITDBS) is discussed and the potential application of a data base management system in support of future space missions, the design of scientific instruments needed, and the potential payload groupings is described. Two basic data files are suggested, the first containing a detailed narrative information list pertaining to design configurations and optimum performance of each instrument, and the second consisting of a description of the parameters pertinent to the instruments' thermal control and design in the form of a summary record of coded information, and serving as a recall record. The applicability of a data request sheet for preliminary planning is described and is concluded that the proposed system may additionally prove to be a method of inventory control.

Bartoszek, J. T.↗

Ab Initio -Based Bond Order Potential to Investigate Low Thermal Conductivity of Stanene Nanostructures

We introduce a bond order potential (BOP) for stanene based on an ab initio derived training data set. The potential is optimized to accurately describe the energetics, as well as thermal and mechanical properties of a free-standing sheet, and used to study diverse nanostructures of stanene, including tubes and ribbons. As a representative case study, using the potential, we perform molecular dynamics simulations to study stanene’s structure and temperature-dependent thermal conductivity. We find that the structure of stanene is highly rippled, far in excess of other 2-D materials (e.g., graphene), owing to its low in-plane stiffness (stanene: ~ 25 N/m; graphene: ~ 480 N/ m). The extent of stanene’s rippling also shows stronger temperature dependence compared to that in graphene. Furthermore, we find that stanene based nanostructures have significantly lower thermal conductivity compared to graphene based structures owing to their softness (i.e., low phonon group velocities) and high anharmonic response. Our newly developed BOP will facilitate the exploration of stanene based low dimensional heterostructures for thermoelectric and thermal management applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data Testing CIELO Evaluations with ICSBEP Benchmarks

We review criticality data testing performed at Los Alamos with a combination of ENDF/B-VII.1 + potential CIELO nuclear data evaluations. The goal of CIELO is to develop updated, best available evaluated nuclear data files for 1 H, 16 O, 56 Fe, 235,238 U and 239 Pu. because the major international evaluated nuclear data libraries don’t agree on the internal cross section details of these most important nuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Assessment of the Idaho National Laboratory Remote-Handled Low-Level Waste Disposal Facility Vault Concrete Data

This document provides a summary of the concrete performance data collected during vault fabrication and installation. The report includes the process by which quality data was collected during vault fabrication and installation, the inspection requirements, and a summary of resulting test data with the potential to impact vault system durability. This report also includes quantitative data collected on cured concrete samples poured for random concrete batches throughout the concrete component fabrication process. Quantitative data includes total porosity, bulk density, absorption, effective porosity, and gas-phase permeability. Chloride diffusivity data collected during the concrete mix selection process are also included for completeness. Data shows that the vault quality assurance program resulted in components received insignificant defects and damaged areas during the fabrication stage and during the vault installation stage. Data collected on the cured concrete samples show the gas-phase permeability and effective porosity are slightly higher than the data used to select the concrete mix designs.

99 GENERAL AND MISCELLANEOUS↗

DMTN-065: Data Management for LSST Special Programs

Special Programs are additional survey areas and/or observing strategies that are driven by specific science goals which build on, or are beyond, the core science pillars of the Wide Fast Deep Main Survey. In order to meet the requirements and enable science related to Special Programs, this document provides recommendations for Rubin Data Management regarding processing and serving data products for Special Programs. Hardware and processing boundaries on the potential diversity of data from Special Programs are discussed along with scenarios in which user-generated processing and data products might be needed to meet Special Programs' science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

Amplitude calibrating the Seasat SAR imagery

The Seasat Synthetic Aperture Radar is described with emphasis placed on those aspects of the system that affect the amplitude calibration of the radar. Imagery produced by several Seasat passes over Death Valley, California are examined in an effort to determine the reproducibility of the data and the potential for relative and absolute calibration of the overall SAR image data set.

Held, D.↗

An unusual charging event on ISEE 1

Electrostatic cleanliness requirements on ISEE 1 were expected to prevent negative charging in sunlight. This has largely been true, but on three occasions, ISEE 1 has been observed to charge to significant negative potentials in sunlight. Data from the two electric field experiments and from the plasma composition experiment on ISEE 1 show that the spacecraft charged to close to -70 V in sunlight at about 0700 UT on March 17, 1978. Data from the electron spectrometer experiment show that there was a potential barrier of some -10 to -20 V about the spacecraft during this event. The potential barrier was effective in turning back emitted photoelectrons to the spacecraft. Potential barriers can be formed by differential charging on the spacecraft or by the presence of excess space charge in the plasma. The shape of the barrier suggests that it is due to the former, even though electrostatic cleanliness specifications imposed on ISEE were intended to eliminate differential charging. Modeling of this event showed that the barrier could not be produced by the presence of space charge but that it was most likely produced by differential charging of the solar arrays.

Olsen, R. C.↗

Practical applications of remote sensing technology

Land managers increasingly are becoming dependent upon remote sensing and automated analysis techniques for information gathering and synthesis. Remote sensing and geographic information system (GIS) techniques provide quick and economical information gathering for large areas. The outputs of remote sensing classification and analysis are most effective when combined with a total natural resources data base within the capabilities of a computerized GIS. Some examples are presented of the successes, as well as the problems, in integrating remote sensing and geographic information systems. The need to exploit remotely sensed data and the potential that geographic information systems offer for managing and analyzing such data continues to grow. New microcomputers with vastly enlarged memory, multi-fold increases in operating speed and storage capacity that was previously available only on mainframe computers are a reality. Improved raster GIS software systems have been developed for these high performance microcomputers. Vector GIS systems previously reserved for mini and mainframe systems are available to operate on these enhanced microcomputers. One of the more exciting areas that is beginning to emerge is the integration of both raster and vector formats on a single computer screen. This technology will allow satellite imagery or digital aerial photography to be presented as a background to a vector display.

Whitmore, Roy A., Jr.↗

Telemetry Options for LDB Payloads

The Columbia Scientific Balloon Facility provides Telemetry and Command systems necessary for balloon operations and science support. There are various Line-Of-Sight (LOS) and Over-The-Horizon (OTH) systems and interfaces that provide communications to and from a science payload. This presentation will discuss the current data throughput options available and future capabilities that may be incorporated in the LDB Support Instrumentation Package (SIP) such as doubling the TDRSS data rate. We will also explore some new technologies that could potentially expand the data throughput of OTH communications.

Balloon↗

The Effect of Dopant Concentration and Annealing Treatments on N-Type Iodine Doped CdTe

We report properties of highly conducting n-type cadmium telluride single crystals doped with iodine (CdTe:I). These crystals were grown with dopant concentrations in the range of 10^17 cm-3 to 10^19 cm-3 by Modified Vertical Bridgman (MVB) melt growth. Post-growth dopant activation, including Cd annealing, Te annealing, and rapid thermal annealing (RTA), was applied to improve free carrier density. The structural, optical, and electrical properties were analyzed by Glow Discharge Mass Spectroscopy (GDMS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Photoluminescence Spectroscopy (PL), optical absorption, Hall measurements, Capacitance-Voltage (CV) measurements, and time-resolved photoluminescence (TRPL). The results indicate that Cd annealing is the most effective activation method to get 100% donor activation (n is approximately 2 x 10^18 cm-3), which is close to the room temperature solubility limit of iodine. This leads to the lowest resistivity and the highest mobility. Moreover, this data suggests a potential role of Cd vacancy-related defects on electrical self-compensation.

annealing↗

Parcel-Scale Assessment of Rooftop Solar Technical Potential

Understanding the potential for rooftop solar and other distributed energy resources (DERs) to contribute to power system planning is increasingly relevant for cities, utilities, and other planning entities. Such planning efforts typically require an estimate of technical potential, or the feasible technology potential independent of economic considerations. Currently, best-in-class rooftop solar technical potential methods use Light Detection and Ranging (LiDAR) data which can identify each roof plane tilt, azimuth, and unshaded area. However, LiDAR data is not universally available and, even when available, obtaining and processing this data can be expensive. In contrast, parcel-level data is easy to use and widely available as it is generated by jurisdictions to levy property taxes. Such data universally reports building footprint area, which is highly correlated with roof area suitable (developable) for rooftop solar. Moreover, parcel data identifies building end-use, tenure, and other building characteristics not provided by LiDAR. To explore the feasibility of using parcel data to assess technical potential more broadly, we compare estimates using parcel data in Orlando, Florida (HIFLD 2020) to those generated using LiDAR data (Koebrich et al. 2021). We find that the parcel-based method results in accurate technical potential estimates at a block and city-scale, though only after accounting for shading and other factors that derate developable roof area. The results of this study demonstrate a scalable, low-effort approach to assess rooftop solar technical potential for every city and community in the U.S.

census blocks↗

Intelligent Systems Technologies and Utilization of Earth Observation Data

The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

Ramapriyan, H. K.↗

Explicit expressions of the potential and its derivatives at the origin in terms of the scattering data

The quantum mechanical theory of scattering of a particle by a spherically symmetrical potential is presented. As in the inverse scattering problem, the input of the calculation is the scattering and bound-state data, and the output is data on the potential. The results discussed are explicit expressions for the values of the potential and its derivatives at the origin in terms of the scattering and boundstate data. Various methods to obtain these results are outlined. The presentation is aimed at introducing these various approaches. The simplest scattering problem (nonrelativistic S-wave scattering on a holomorphic potential without bound states) is used as the basis for discussion, and technicalities are omitted whenever possible without loss of clarity. A complete compilation is given of the results obtained to date in this field, including the treatment of higher partial waves and the Klein-Gordon and Dirac equations.

Calogero, F.↗

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗

Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗