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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A comparison of small-field tissue phantom ratio data generation methods for an Elekta Agility 6 MV photon beam

Tissue-phantom ratios (TPRs) are a common dosimetric quantity used to describe the change in dose with depth in tissue. These can be challenging and time consuming to measure. The conversion of percentage depth dose (PDD) data using standard formulae is widely employed as an alternative method in generating TPR. However, the applicability of these formulae for small fields has been questioned in the literature. Functional representation has also been proposed for small-field TPR production. This article compares measured TPR data for small 6 MV photon fields against that generated by conversion of PDD using standard formulae to assess the efficacy of the conversion data. By functionally fitting the measured TPR data for square fields greater than 4 cm in length, the TPR curves for smaller fields are generated and compared with measurements. TPRs and PDDs were measured in a water tank for a range of square field sizes. The PDDs were converted to TPRs using standard formulae. TPRs for fields of 4 × 4 cm{sup 2} and larger were used to create functional fits. The parameterization coefficients were used to construct extrapolated TPR curves for 1 × 1 cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields. The TPR data generated using standard formulae were in excellent agreement with direct TPR measurements. The TPR data for 1 × 1-cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields created by extrapolation of the larger field functional fits gave inaccurate initial results. The corresponding mean differences for the 3 fields were 4.0%, 2.0%, and 0.9%. Generation of TPR data using a standard PDD-conversion methodology has been shown to give good agreement with our directly measured data for small fields. However, extrapolation of TPR data using the functional fit to fields of 4 × 4 cm{sup 2} or larger resulted in generation of TPR curves that did not compare well with the measured data.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1988

The magnetosphere, ionosphere, and atmosphere as a system - Dynamics Explorer 5 years later

The Dynamics Explorer (DE) program summarizes its accomplishments during the first 5 years since the launch of the two DE satellites. This introduction to six review articles provides background information and a brief history of the program, especially citing the contributions of many people to its development. The principal investigators who had primary responsibility to implement the program are listed, together with the instruments they provided. Orbital information and approaches and constraints to data acquisition are explained. The brief description of the ground data processing and analysis system provides information on access to data catalogs and data sets. Each review article is then placed in the context of the categories of scientific objectives of the program.

Hoffman, R. A.↗
NASA NTRS2023

Experimental and Semiclassical Stark Widths and Shifts for Spectral Lines of Neutral and Ionized Atoms (A Critical Review of Experimental and Semiclassical Data for the Period 2008 through 2020)

This Review Article compares new experimental and corresponding semiclassical Stark broadened data for non-hydrogenic spectral lines of neutral atoms and positive ions. This Review covers the period 2008 until the end of 2020 and presents the continuation of previous critical reviews from 1976 (two), 1984 (two), 1990, 2002, and one from 2009. This Review reports the Stark broadening parameters of 1665 spectral lines belonging to 35 elements with 61 different atomic and ion species. The data are taken from 60 papers. Experimental data are arranged by elements and spectra, and these are reported in tables in alphabetical and numerical order, respectively. Each experimental Stark broadening parameter is followed with estimated accuracy. The experimental Stark broadening and shift data presented in the tables are compared with the corresponding semiclassical results available in the literature. In addition, for comparison experiments versus semiclassical theoretical Stark broadening parameters, a numerically improved theoretical approach developed based on Griem and co-workers’ theory is used to evaluate Stark widths and shifts of all studied lines whenever required atomic energy levels data and transition probabilities are available. At the end of the text report, for each analyzed neutral or ion species, the information about the location of the same species data in preceding reviews is given.

Plasma line broadening↗
DOE OSTI2015

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Spherical harmonic representation of the main geomagnetic field for world charting and investigations of some fundamental problems of physics and geophysics

The data processing of MAGSAT investigator B test tapes and data tapes, and tapes of selected data on 15 magnetically quiet days is reported. The 1980 World Chart spherical model was compared with the MAGSAT (3/80) and MAGSAT vector data were used in the models. An article on modelling the geomagnetic field using satellite data is included.

Barraclough, D. R.↗
NASA NTRS2000

Finite Elements Analysis of a Composite Semi-Span Test Article With and Without Discrete Damage

AS&M Inc. performed finite element analysis, with and without discrete damage, of a composite semi-span test article that represents the Boeing 220-passenger transport aircraft composite semi-span test article. A NASTRAN bulk data file and drawings of the test mount fixtures and semi-span components were utilized to generate the baseline finite element model. In this model, the stringer blades are represented by shell elements, and the stringer flanges are combined with the skin. Numerous modeling modifications and discrete source damage scenarios were applied to the test article model throughout the course of the study. This report details the analysis method and results obtained from the composite semi-span study. Analyses were carried out for three load cases: Braked Roll, LOG Down-Bending and 2.5G Up-Bending. These analyses included linear and nonlinear static response, as well as linear and nonlinear buckling response. Results are presented in the form of stress and strain plots. factors of safety for failed elements, buckling loads and modes, deflection prediction tables and plots, and strainage prediction tables and plots. The collected results are presented within this report for comparison to test results.

Lovejoy, Andrew E.↗
DOE OSTI2016

Comparisons between a priori Uncertainty Quantification and Calculation/Measurement Discrepancies Applied to the MERCI UO{sub 2} Fuel Rod Decay Heat Experiment

In 2008, an UO{sub 2} fuel rod was irradiated up to ∼ 3.5 GWd/tHL in the CEA/Saclay research reactor Osiris through the MERCI experiment. Some rod's pellets were analysed. Experimental results were obtained: - fuel rod decay heat measurement by calorimetry (cooling times from 27 minutes to 42 days), - evaluation of the amounts of some nuclei (U, Pu, Cs, Nd...) by isotopic dilution mass spectrometry, - nuclide activities. Comparison of type (C - M)/M where C is the calculated decay heat and M the experimentally measured decay heat was reported in reference. Neutronics flux was computed by CEA TRIPOLI-4 Monte-Carlo or APOLLO2 deterministic transport code system. Irradiation and cooling phases were simulated with CEA DARWIN/PEPIN2 code system. Good agreements were globally shown between numerical simulation results and experimental measurements on total decay heat. Uncertainty propagation in this previous work was established from Rebah's studies. These last years, within the framework of supports to its industrial partners EDF and Areva, the CEA/DEN has implemented two different approaches to propagate nuclear data uncertainties to depletion code outputs. A direct forward deterministic perturbation method using sensitivity profiles was implemented in the French industrial depletion code system DARWIN/PEPIN2. Meanwhile, a propagation based on Monte Carlo correlated sampling was achieved using the CEA uncertainty platform URANIE and the new generation depletion code MENDEL. Both methods will be described in this article. Uncertainties on nuclear data (independent fission yields, multigroup microscopic cross sections, radioactive decay constants, radioactive decay branching ratio and radioactive decay energies) are propagated to decay heat and isotopic concentrations. To match MERCI first study, flux computation is realized by APOLLO2. Furthermore, uncertainty quantification (UQ) is re-evaluated by both DARWIN/PEPIN2 and MENDEL codes. It is an important stage in the process of validating both depletion codes with their respective data library. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Publications of the Jet Propulsion Laboratory, 1992

JPL Bibliography 39-33 describes and indexes by primary author the externally distributed technical reporting, released during calendar year 1992, that resulted from scientific and engineering work performed or managed by the Jet Propulsion Laboratory. Three classes of publications are included: (1) JPL Publication (92-series) in which the information is complete for a specific accomplishment; (2) articles from the quarterly Telecommunications and Data Acquisition (TDA) Progress Report (42-series) (each collection of articles in this class of publication presents a periodic survey of current accomplishments by the Deep Space Network as well as other developments in Earth-based radio technology); and (3) articles published in the open literature.

Source record↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2016

Data Always Getting Bigger—A Scalable DOI Architecture for Big and Expanding Scientific Data

The Atmospheric Radiation Measurement (ARM) Data Archive established a data citation strategy based on Digital Object Identifiers (DOIs) for the ARM datasets in order to facilitate citing continuous and diverse ARM datasets in articles and other papers. This strategy eases the tracking of data provided as supplements to articles and papers. Additionally, it allows future data users and the ARM Climate Research Facility to easily locate the exact data used in various articles. Traditionally, DOIs are assigned to individual digital objects (a report or a data table), but for ARM datasets, these DOIs are assigned to an ARM data product. This eliminates the need for creating DOIs for numerous components of the ARM data product, in turn making it easier for users to manage and cite the ARM data with fewer DOIs. In addition, the ARM data infrastructure team, with input from scientific users, developed a citation format and an online data citation generation tool for continuous data streams. This citation format includes DOIs along with additional details such as spatial and temporal information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven methods for diffusivity prediction in nuclear fuels

The growth rate of structural defects in nuclear fuels under irradiation is intrinsically related to the diffusion rates of the defects in the fuel lattice. The generation and growth of atomistic structural defects can significantly alter the performance characteristics of the fuel. This alteration of functionality must be accurately captured to qualify a nuclear fuel for use in reactors. Predicting the diffusion coefficients of defects and how they impact macroscale properties such as swelling, gas release, and creep is therefore of significant importance in both the design of new nuclear fuels and the assessment of current fuel types. In this article, we apply data-driven methods focusing on machine learning (ML) to determine various diffusion properties of two nuclear fuels—uranium oxide and uranium nitride. We show that using ML can increase, often significantly, the accuracy of predicting diffusivity in nuclear fuels in comparison to current analytical models. We also illustrate how ML can be used to quickly develop fuel models with parameter dependencies that are more complex and robust than what is currently available in the literature. In conclusion, these results suggest there is potential for ML to accelerate the design, qualification, and implementation of nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2022

Systematic Detection of Anomalous Ionospheric Perturbations Above LEOs From GNSS POD Data Including Possible Tsunami Signatures

In this article, we show the capability of a global navigation satellite system (GNSS) precise orbit determination (POD) low Earth orbit (LEO) data to detect anomalous ionospheric disturbances in the spectral range of the signals associated with earthquakes and tsunamis, applied to two of these events in Papua New Guinea (PNG) and the Solomon Islands during 2016. This is achieved thanks to the new PIES approach (POD-GNSS LEO Detrended Ionospheric Electron Content Significant Deviations). The significance of such ionospheric signals above the swarm LEOs is confirmed with different types of independent data: in situ electron density measurements provided by the Langmuir Probe (LP) onboard swarm LEOs, DORIS, and ground-based GNSS colocated measurements, as it is described in this article. In this way, we conclude the possible detection of the tsunami-related ionospheric gravity wave in PNG 2016 event, consistent with the most-recent theory, which shows that a tsunami (which is localized in space and time) excites a spectrum of gravity waves, some of which have faster horizontal phase speeds than the tsunami. We believe that this work shows as well the feasibility of a future potential monitoring system of ionospheric disturbances, to be made possible by hundreds of CubeSats with POD GNSS receivers among other appropriate sensors, and supported for real-time or near real-time confirmation and characterization by thousands of worldwide existing ground GNSS receivers.

Global Navigation Satellite System↗
DOE OSTI2020

Principles of Corrosion in Nuclear Systems: Theory and Analytical Methods

This article is meant to provide the reader with the fundamental electrochemistry necessary to critically evaluate the data and discussions in the articles on corrosion that follow. As such it has two main sections, theory and analytical methods. In the section on theory, a review of half cell reactions, cell potentials and the Nernst equation, and reference electrodes in nuclear systems are discussed. In addition, a review of the thermodynamics from room temperature to the PWR and kinetics of dissolution and passive film formation is also presented. In the section on analytical methods, we review the principles of potentiodynamic polarization, electrochemical impedance spectroscopy, and we introduce a more seldom used technique, Mott-Schottky analysis.

Lillard, R Scott↗
NASA NTRS2008

Aerothermodynamic Testing and Boundary Layer Trip Sizing of the HIFiRE Flight 1 Vehicle

An experimental wind tunnel test was conducted in the NASA Langley Research Center s 20-Inch Mach 6 Air Tunnel in support of the Hypersonic International Flight Research Experimentation Program. The information in this article is focused on the Flight 1 configuration, the first in a series of flight experiments. The article documents experimental measurements made over a Reynolds numbers range of 2.1x10(exp 6)/ft to 5.6x10(exp 6)/ft and angles of attack of -5 to +5 deg on several scaled ceramic heat transfer models of the Flight 1 configuration. Global heat transfer was measured using phosphor thermography and the resulting images and heat transfer distributions were used to infer the state of the boundary layer on the vehicle windside and leeside surfaces. Boundary layer trips were used to force the boundary layer turbulent and the experimental data highlighted in this article were used to size and place the boundary layer trip for the flight vehicle. The required height of the flight boundary layer trip was determined to be 0.079 in and the trip was moved from the design location of 7.87 in to 20.47 in to ensure that augmented heating would not impact the laminar side of the vehicle. Allowable roughness was selected to be 3.2x10(exp -3) in.

Berger, Karen T.↗
DOE OSTI2023

Desmearing small-angle scattering data by central moment expansions

This article proposes a robust method for desmearing 1D small-angle scattering (SAS) intensity profiles. Using the central-moment-expansion technique, smearing in SAS intensity profiles is achieved in a model-free manner, eliminating the need for presumptive input during the desmearing. This innovative approach enables data analysis of SAS data without the resolution being convoluted with the structural model, thereby facilitating faster implementation and performance of fitting functions directly from the scattering models.

42 ENGINEERING↗
DOE OSTI2023

Soil temperature and soil moisture raw data, permafrost table depths, and accompanying environmental variable data, Kenai Wildlife Refuge, 2019-2022

Data package purpose: This data package was created to contain all data used in an upcoming article, "Canopy Cover and Microtopography Control Precipitation-Enhanced Thaw of Ecosystem-Protected Permafrost." In review.This data package includes: Raw output from 19 distributed temperature profilers with a thermistor every 10 cm along a 160 cm length at a measurement interval of 15 minutes (.CSV). Raw output from two soil moisture and temperature profilers (90 cm length and 120 cm length) that took composite soil moisture readings every 15 cm along the sensor length at a measurement interval of 30 minutes (.CSV). Permafrost depths were measured annually in mid-September at DTP sensor locations (.CSV) and along an across-site transect (.CSV). Environmental variables (snow depth, canopy closure, moss depth, and elevation) for all sensor locations. Real-time kinetic (RTK) GPS points showing site microtopography (.CSV).Analysis software: Our analysis was done in Matlab. File types can be used with any software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Privacy by Design in Distributed Edge Systems: Innovating Secure Workflows for Smart Cities

The proliferation of distributed edge systems, such as those in smart cities, healthcare, and industrial IoT, offers unprecedented opportunities for data processing closer to its source, thereby reducing latency and enhancing efficiency. However, these systems also present significant privacy challenges due to the handling of sensitive data from multiple sources. This article explores the critical need for designing privacy-preserving workflows in distributed edge systems to ensure data security while maximizing the potential of edge computing. By examining the challenges, technological advancements, and potential of privacy-by-design approaches, we highlight the importance of integrating advanced privacy-preserving techniques like federated learning, differential privacy, homomorphic encryption, secure multi-party computation, and zero-knowledge proofs. These innovations are crucial for enhancing data security, regulatory compliance, and public trust in smart city applications, ultimately leading to safer and more efficient urban environments.

Kotevska, Olivera↗
NASA NTRS2005

Data-Rate Estimation for Autonomous Receiver Operation

In this article, we present a series of algorithms for estimating the data rate of a signal whose admissible data rates are integer base, integer powered multiples of a known basic data rate. These algorithms can be applied to the Electra radio currently used in the Deep Space Network (DSN), which employs data rates having the above relationship. The estimation is carried out in an autonomous setting in which very little a priori information is assumed. It is done by exploiting an elegant property of the split symbol moments estimator (SSME), which is traditionally used to estimate the signal-to-noise ratio (SNR) of the received signal. By quantizing the assumed symbol-timing error or jitter, we present an all-digital implementation of the SSME which can be used to jointly estimate the data rate, SNR, and jitter. Simulation results presented show that these joint estimation algorithms perform well, even in the low SNR regions typically encountered in the DSN.

Tkacenko, A.↗