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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Application of the Bootstrap Statistical Method in Deriving Vibroacoustic Specifications

This paper discusses the Bootstrap Method for specification of vibroacoustic test specifications. Vibroacoustic test specifications are necessary to properly accept or qualify a spacecraft and its components for the expected acoustic, random vibration and shock environments seen on an expendable launch vehicle. Traditionally, NASA and the U.S. Air Force have employed methods of Normal Tolerance Limits to derive these test levels based upon the amount of data available, and the probability and confidence levels desired. The Normal Tolerance Limit method contains inherent assumptions about the distribution of the data. The Bootstrap is a distribution-free statistical subsampling method which uses the measured data themselves to establish estimates of statistical measures of random sources. This is achieved through the computation of large numbers of Bootstrap replicates of a data measure of interest and the use of these replicates to derive test levels consistent with the probability and confidence desired. The comparison of the results of these two methods is illustrated via an example utilizing actual spacecraft vibroacoustic data.

Hughes, William O.↗
DOE OSTI2025

Expanded method for the determination of burnup in nuclear fuels using multiple neodymium isotopes

Established methods for the determination of burnup in nuclear fuels commonly rely on the measurement of 148Nd in the spent fuel in concert with known fission product yields to determine the atom percent of fissions in the fuel. This isotope of neodymium is used for various reasons, including chemical and radioactive stability, ease of measurement, and low rates of formation and destruction due to neutron flux apart from fission. However, careful calculation of effective cumulative fission yields and correction factors for (n,γ) capture reactions allows for additional stable and long-lived isotopes of neodymium to be used to provide additional independent measurements of burnup, reducing statistical uncertainty. This method was developed and successfully applied to measure the burnup of compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. The mean burnup measured using 143Nd, 145Nd, 146Nd, 148Nd, and 150Nd was statistically observed to be the same as that measured using 148Nd alone, but the statistical uncertainty in the measurement was reduced by a factor of 2, providing a tighter confidence interval in the final results.

Helmreich, Grant [ORNL] (ORCID:0000000330464394)↗
NASA NTRS1977

Development of a transfer function method for dynamic stability measurement

Flutter testing method based on transfer function measurements is developed. The error statistics of several dynamic stability measurement methods are reviewed. It is shown that the transfer function measurement controls the error level by averaging the data and correlating the input and output. The method also gives a direct estimate of the error in the response measurement. An algorithm is developed for obtaining the natural frequency and damping ratio of low damped modes of the system, using integrals of the transfer function in the vicinity of a resonant peak. Guidelines are given for selecting the parameters in the transfer function measurement. Finally, the dynamic stability measurement technique is applied to data from a wind tunnel test of a proprotor and wing model.

Johnson, W.↗
DOE OSTI2023

Evaluation protocol for revealing magnonic contrast in TR-STXM measurements

We present a statistically motivated method to extract magnonic contrast from time-resolved scanning transmission x-ray microscopy (TR-STXM) measurements. TR-STXM is an element-specific method for resolving spin-dynamics in space and time. It offers nanometer spatial resolution and picosecond temporal resolution. The presented method makes it possible to obtain phase and amplitude profiles of spin-waves from STXM measurements. Furthermore, it allows for a rigorous transformation to reciprocal magnon k⃗-space, revealing k⃗-dependent magnon properties such as the magnon dispersion in three dimensions and for all directions of the magnetic anisotropy. We demonstrate our method using X-band ferromagnetic resonance on a micrometer-sized permalloy assembly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1992

Possibilistic measurement and set statistics

Set-based statistics are necessary to generate possibility distributions from measured data. Methods by which physical measurements can generate statistical data on real intervals are considered, including the following: trials from multiple heterogeneous measurement devices rather than a single instrument at multiple times; classes of consistent intervals constructed from statistical data around a common point focus or interval core; and consonant intervals constructed from statistical data.

Joslyn, Cliff↗
DOE OSTI2021

Essential Statistical Concepts

Statistical methods are an essential element to making quality measurements, allowing the organization and interrogation of data in a structured way. This introductory chapter describes key concepts of measurement statistics that are used in many nondestructive assay (NDA) methods and is intended as a primer to the reading list provided in the reference section. (Croft and Burr 2016; Smith 1991; Smith 2013; Taylor 1997; Triola 2017). The textbooks by Triola on elementary statistics (Figure 1), Taylor, and Smith (2013) introduce uncertainty analysis in the physical sciences. Smith (1991) provides a rigorous introduction with examples to correlated variables. These texts collectively offer an excellent foundation for understanding essential statistical concepts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗
NASA NTRS1977

Estimation of regional heat flux from scanning radiometer measurements

The paper presents a statistical method for extracting regional information on the radiative heat flux at the top of the atmosphere from a satellite-borne scanning radiometer. The radiative heat flux distribution is denoted by a double Fourier series with coefficients to be determined from measurements. The method determines, in the sense of minimum variance, the best linear estimator of the total flux over a region. The heat flux distribution is represented by a truncated series which is unbiased.

Bess, T. D.↗
NASA NTRS1981

Estimation of trends

The application of statistical methods to recorded ozone measurements. The effects of a long term depletion of ozone at magnitudes predicted by the NAS is harmful to most forms of life. Empirical prewhitening filters the derivation of which is independent of the underlying physical mechanisms were analyzed. Statistical analysis performs a checks and balances effort. Time series filters variations into systematic and random parts, errors are uncorrelated, and significant phase lag dependencies are identified. The use of time series modeling to enhance the capability of detecting trends is discussed.

Source record↗
DOE OSTI2020

EMP-Resilient Electric Grid Transformer Analysis

The response of a high - voltage (HV) transformer to fast rise time voltages, such as that from a electromagnetic pulse (EMP) can result in interruption of power distribution and possibly system failure. To help identify these potential occurrences, it is necessary to develop a transformer model that not only captures the input/output response of the transformer but also the internal behavior. The model constructed should cover the frequency band of interest while capturing the internal physical and electrical characteristics. This broad-band, high-fidelity model would enable the prediction of unwanted effects through simulation. A proposed modeling scheme for a HV transformer is described in Part 1 of this report. Part 2 of this report details assessments of internal voltage and electrical field holdoff testing of transformer insulation dielectric breakdown, including comparison of low frequency (DC/60 Hz) holdoff to rise times characteristic of lightning (1 s) and EMP E1 transients (10 - 30 ns). This initial project is a path toward establishing electrical grid transformer failure criteria for EMP voltage transients. We developed modeling methods and measured breakdown electrical field statistical distributions for direct current, 60 Hz, lightning and EMP characteristic voltage rise times. Methods of nanosecond-scale capacitive discharge unit high voltage source development, suggestions for derating of 60 Hz insulation maximum electrical fields for EMP nanosecond pulse voltage withstand rating, and potential methods for increasing transformer resilience to such fast rise time pulses are described.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Comprehensive Open-Source R Software For Statistical Metrology Calculations: From Uncertainty Evaluation To Risk Analysis

Whether calibrating equipment or inspecting products on the factory floor, metrology requires many complicated statistical calculations to achieve a full understanding and evaluation of measurement uncertainty and quality. In order to assist its workforce in performing these calculations in a consistent and rigorous way, the Primary Standards Lab at Sandia National Laboratories (SNL) has developed a free and open-source software package for computing various metrology calculations from uncertainty propagation to risk analysis. In addition to propagating uncertainty through a measurement model using the well-known Guide to Expression of Uncertainty in Measurement or Monte Carlo approaches, evaluating the individual Type A and Type B uncertainty components that go into the measurement model often requires other statistical methods such as analysis of variance or determining uncertainty in a fitted curve. Once the uncertainty in a measurement has been calculated, it is usually evaluated from a risk perspective to ensure the measurement is suitable for making a particular conformance decision. Finally, SNL’s software can perform all these calculations in a single application via an easy-to-use graphical interface, where the different functions are integrated so the results of one calculation can be used as inputs to another calculation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Elucidating plasma dynamics in Hasegawa–Wakatani turbulence by information geometry

In this work, the impact of adiabatic electrons on drift-wave turbulence, modeled by the Hasegawa–Wakatani equations, is studied using information length. Information length is a novel theoretical method for measuring distances between statistical states represented by different probability distribution functions (PDFs) along the path of a system and represents the total number of statistically different states that a system evolves through in time. Specifically, the time-dependent PDFs of turbulent fluctuations for a given adiabatic index $A$ are computed. The changes in fluctuation statistics are then quantified in time by using information length. The numerical results provide time traces exhibiting intermittent plasma dynamics, and such behavior is identified by a rapid change in the information length. The effects of $A$ are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Multi-omics Characterization of the Host Response to COVID-19

This project is a multi-disciplinary collaboration between investigators at PNNL with expertise in mass spectrometry (MS)-based omics technology development, omics measurement methods development and application, statistics, machine learning and integration of disparate datasets for a systems-level understanding, and expertise in pathogenic coronaviruses, and investigators at the University of Wisconsin-Madison (UW-Madison) with expertise in pathogenic respiratory viruses (e.g. influenza). The goal of this project is to obtain a comprehensive picture of the human host factors critical for the outcome of SARS-CoV-2 infection. We will generate broad untargeted multi-omics profiles using both state-of-the-art and novel instrumentation and approaches to enable the identification of the molecular mechanisms and host response pathways that impact human COVID-19 outcomes. We anticipate these results will lead to the generation of biomarker panels that are predictive of disease outcomes and mechanistic hypotheses that can be further interrogated in future studies and will provide the basis for vaccine or therapeutic development. To do so, we are obtaining and analyzing blood samples from COVID-19 patients with a range of disease outcomes that were treated at the Center Hospital of the National Center for Global Health and Medicine in Tokyo, Japan and other collaborating hospitals in our network. Specifically, this project will fund proteomics and metabolomics analyses of clinical COVID samples, machine learning-based integration of the data, and pathway-based interpretation of the data. This project was funded in June 2020. In the time span of June to September 2020, the project team developed an analytically and statistically robust analysis plan and made various preparations to facilitate sample receipt from our UW-Madison collaborators. This included blocking and randomization of sample prep orders, ordering of reagents and reference materials, and shipping of materials needed for preparation of the samples under BSL3 conditions to our collaborators at UW-Madison. As of FY21, this project has been picked up via a sponsor, the Naval Medical Research Center, which will cover the remainder of the proposed scope of work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Nuclear Material Control & Accounting for Pebble Bed Reactors (FY 2023 Summary Report)

This report discusses the work done under the US Department of Energy NE-5 Advanced Reactor Safeguards and Security Program during FY 2023. It provides a summary of material control and accounting (MC&A) for pebble bed reactors (PBRs) and addresses some of the main challenges with current PBR MC&A approaches that will inform safeguards and security by design efforts. The efforts to date have focused on tristructural isotropic (TRISO) pebble fuel material accounting and control including working with partners in industry, loss and production of nuclear material as part of reactor operations, burnup modeling and measurements, uncertainty quantifications for such modeling and measurements, statistical approaches needed, and measurement methods. The unique fuel management and utilization in a PBR, where the fuel in spherical form is introduced and circulates through the reactor, poses special challenges for MC&A. This contrasts with traditional water-cooled reactors in which the fuel is contained in large assemblies and can be easily identified and counted. Even online fueled reactors, such as the CANDU reactors (none of which operate in the United States), are significantly different because the fuel is still contained in relatively large assemblies, is uniquely identified, and the number of assemblies that pass through the core on an annual basis is much fewer than the hundreds of thousands that circulate in a PBR, none of which are uniquely identified. Additionally, the nature of the TRISO fuel results in very low heavy metal loading with each pebble containing less than 10 g of uranium and on the order of less than 1 g of fissile material. This low fuel density and the robustness of the TRISO particles are major features of the TRISO fuel from a safety basis as each TRISO particle and pebble acts as a containment for the nuclear material and fission products during normal and accident conditions. This also results in very low plutonium loading per pebble during normal operations, which is on the order of 0.1 g at full burnup. A major feature of PBRs is that they will allow for significantly higher burnup, on the order of 160 GWd/THM compared to the burnup of traditional LWRs, which is on the order of 45 GWd/THM. This is achieved by monitoring the pebbles as they circulate through the reactor and allowing them to be reintroduced into the core until the desired burnup is achieved and they are removed from the reactor and enter the spent fuel storage areas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

A data fusion algorithm for multi-sensor microburst hazard assessment

A recursive model-based data fusion algorithm for multi-sensor microburst hazard assessment is described. An analytical microburst model is used to approximate the actual windfield, and a set of 'best' model parameters are estimated from measured winds. The winds corresponding to the best parameter set can then be used to compute alerting factors such as microburst position, extent, and intensity. The estimation algorithm is based on an iterated extended Kalman filter which uses the microburst model parameters as state variables. Microburst state dynamic and process noise parameters are chosen based on measured microburst statistics. The estimation method is applied to data from a time-varying computational simulation of a historical microburst event to demonstrate its capabilities and limitations. Selection of filter parameters and initial conditions is discussed. Computational requirements and datalink bandwidth considerations are also addressed.

Wanke, Craig R.↗
NASA NTRS1994

A data fusion algorithm for multi-sensor microburst hazard assessment

A recursive model-based data fusion algorithm for multi-sensor microburst hazard assessment is described. An analytical microburst model is used to approximate the actual windfield, and a set of 'best' model parameters are estimated from measured winds. The winds corresponding to the best parameter set can then be used to compute alerting factors such as microburst position, extent, and intensity. The estimation algorithm is based on an iterated extended Kalman filter which uses the microburst model parameters as state variables. Microburst state dynamic and process noise parameters are chosen based on measured microburst statistics. The estimation method is applied to data from a time-varying computational simulation of a historical microburst event to demonstrate its capabilities and limitations. Selection of filter parameters and initial conditions is discussed. Computational requirements and datalink bandwidth considerations are also addressed.

Wanke, Craig R.↗