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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Data Analysis & Statistical Methods for Command File Errors

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Correlation Analysis↗
NASA NTRS2018

Coupling Fractional Thermal Runaway Calorimetry (FTRC) Results with Statistical Analysis Methods

Important factors to consider when optimizing Lithium-ion (Li-ion) battery thermal management systems, from a battery safety perspective, include the total energy released during a single cell thermal runaway (TR) event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A fractional thermal runaway calorimeter (FTRC) was used to examine the TR behavior of the following 18650-format Li-ion cells: (1) Molicel 18650-J, (2) LG 18650-HG2, (3) Samsung 18650-30Q, (4) 3.35 Ah LG 18650 test cell, (5) Sony 18650-VC7, and (6) LG 18650-MJ1. These cells were intentionally selected to represent a variety of manufacturers, chemistries, capacities, and safety features. Because of the large number of random and non-random variables associated with the FTRC results, a linear regression model, developed using engineering statistical methods, was utilized to provide final interpretation of the TR behavior for each cell type and design variable combination.

Walker, William↗
NASA NTRS2013

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Parsons, David S.↗
NASA NTRS2013

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Parsons, David S.↗
NASA NTRS2013

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to shock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to shock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite shock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to shock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and shock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to shock induced loading.

Parsons, David↗
NASA NTRS1998

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

Vestibule↗
NASA NTRS2011

Advanced Gear Alloys for Ultra High Strength Applications

Single tooth bending fatigue (STBF) test data of UHS Ferrium C61 and C64 alloys are presented in comparison with historical test data of conventional gear steels (9310 and Pyrowear 53) with comparable statistical analysis methods. Pitting and scoring tests of C61 and C64 are works in progress. Boeing statistical analysis of STBF test data for the four gear steels (C61, C64, 9310 and Pyrowear 53) indicates that the UHS grades exhibit increases in fatigue strength in the low cycle fatigue (LCF) regime. In the high cycle fatigue (HCF) regime, the UHS steels exhibit better mean fatigue strength endurance limit behavior (particularly as compared to Pyrowear 53). However, due to considerable scatter in the UHS test data, the anticipated overall benefits of the UHS grades in bending fatigue have not been fully demonstrated. Based on all the test data and on Boeing s analysis, C61 has been selected by Boeing as the gear steel for the final ERDS demonstrator test gearboxes. In terms of potential follow-up work, detailed physics-based, micromechanical analysis and modeling of the fatigue data would allow for a better understanding of the causes of the experimental scatter, and of the transition from high-stress LCF (surface-dominated) to low-stress HCF (subsurface-dominated) fatigue failure. Additional STBF test data and failure analysis work, particularly in the HCF regime and around the endurance limit stress, could allow for better statistical confidence and could reduce the observed effects of experimental test scatter. Finally, the need for further optimization of the residual compressive stress profiles of the UHS steels (resulting from carburization and peening) is noted, particularly for the case of the higher hardness C64 material.

Shen, Tony↗
DOE OSTI2022

Publishing unbinned differential cross section results

Machine learning tools have empowered a qualitatively new way to perform differential cross section measurements whereby the data are unbinned, possibly in many dimensions. Unbinned measurements can enable, improve, or at least simplify comparisons between experiments and with theoretical predictions. Furthermore, many-dimensional measurements can be used to define observables after the measurement instead of before. There is currently no community standard for publishing unbinned data. While there are also essentially no measurements of this type public, unbinned measurements are expected in the near future given recent methodological advances. The purpose of this paper is to propose a scheme for presenting and using unbinned results, which can hopefully form the basis for a community standard to allow for integration into analysis workflows. This is foreseen to be the start of an evolving community dialogue, in order to accommodate future developments in this field that is rapidly evolving.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing

The ability of tri-structural isotropic (TRISO) fuel to contain fission products is largely dictated by the quality of the manufacturing process, since most of the fission product release is expected to occur due to coating layer failure in a small number of particles containing defects. The Bison fuel performance code has capabilities to predict failure in individual particles, accounting for the presence of defects, and to apply statistical analysis methods to compute the probability of failure in a set of fuel particles. Bison has recently undergone significant development both to improve its physical representations of fuel particle behavior and to improve the efficiency of its statistical failure calculations. Physical model improvements include new capabilities to account for the pressure generated by fission gases on inner pyrolytic carbon (IPyC) crack surfaces and to use local material coordinate orientation to accurately incorporate the anisotropy in the material properties in aspherical particles. To improve statistical modeling efficiency, a direct integration approach which involves directly integrating the failure probability function associated with statistically varying parameters has been developed. The direct integration approach is much more efficient than the Monte Carlo (MC) schemes commonly employed, and allows Bison to directly run high-dimensional fuel performance models, which improves the accuracy of failure probability calculations. Finally, a set of benchmark problems is considered here to compare the MC and direct integration approaches, and a statistical failure analysis of compacts in the Advanced Gas Reactor (AGR)-2 experiments is performed using the direct integration approach.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Statistical optical link budget analysis

In this paper, we describe work on extending statistical analysis methods to optical communications links, with a primary focus on intensity modulated, direct detected photon-counting channel utilizing pulse-position-modulation (PPM). We performed analysis on the relationship between bit error rate (BER) requirement, statistical characteristics of the received signal power and noise power, and the coded performance curves. We presented link analysis results with preliminary uncertainty quantifications of signal power and noise power. We used the Consultative Committee for Space Data Systems (CCSDS) Serially Concatenated convolutionally coded Pulse Position Modulation (SCPPM) prototype software [1] to obtain coded performance curves under different operating conditions with varying signal power, background noise power, code rates,and PPM modulation orders. Comparison with traditional, deterministic analysis shows that extra margin needs to be reserved to compensate for the performance losses caused by uncertainties of the link parameters.

Cheung, Kar-Ming↗
NASA NTRSDate not supplied

An Overview of Printed Circuit Board Risks and Supplier Capability

This NESC Webinar provides the audience a snapshot of quality variations in printed circuit boards, as assessed, using experiences in processing and risk analysis of PCB structural integrity coupons. The presentation will focus on PCB quality metrics, the relative type and number of non-conformances observed and trend analysis using statistical methods. Trend analysis shows the top five non-conformances observed across suppliers, the associated root cause(s) behind these non-conformance, suggestions of mitigation plans and most importantly – the relation of these non-conformances to end item reliability. The statistical trends will then be matched with the current state of the domestic PCB supplier base, its key challenges and opportunities. The presentation further discusses the methods applied at GSFC for evaluating candidate PCB technologies that promote the adoption of higher throughput and faster processing technology for GSFC missions.

printed cricuit boards, supplier capability, risk ↗
NASA NTRSDate not supplied

An Overview of Printed Circuit Board Risks and Supplier Capability (Reuse Document ID 20205007963)

This HDPUG Webinar provides the audience a snapshot of quality variations in printed circuit boards, as assessed, using experiences in processing and risk analysis of PCB structural integrity coupons. The presentation will focus on PCB quality metrics, the relative type and number of non-conformances observed and trend analysis using statistical methods. Trend analysis shows the top five non-conformances observed across suppliers, the associated root cause(s) behind these non-conformance, suggestions of mitigation plans and most importantly – the relation of these non-conformances to end item reliability. The statistical trends will then be matched with the current state of the domestic PCB supplier base, its key challenges and opportunities. The presentation further discusses the methods applied at GSFC for evaluating candidate PCB technologies that promote the adoption of higher throughput and faster processing technology for GSFC missions.

printed cricuit boards, supplier capability, risk ↗
NASA NTRS1986

Continuum radiation from active galactic nuclei: A statistical study

The physics of the continuum spectrum of active galactic nuclei (AGNs) was examined using a large data set and rigorous statistical methods. A data base was constructed for 469 objects which include radio selected quasars, optically selected quasars, X-ray selected AGNs, BL Lac objects, and optically unidentified compact radio sources. Each object has measurements of its radio, optical, X-ray core continuum luminosity, though many of them are upper limits. Since many radio sources have extended components, the core component were carefully selected out from the total radio luminosity. With survival analysis statistical methods, which can treat upper limits correctly, these data can yield better statistical results than those previously obtained. A variety of statistical tests are performed, such as the comparison of the luminosity functions in different subsamples, and linear regressions of luminosities in different bands. Interpretation of the results leads to the following tentative conclusions: the main emission mechanism of optically selected quasars and X-ray selected AGNs is thermal, while that of BL Lac objects is synchrotron; radio selected quasars may have two different emission mechanisms in the X-ray band; BL Lac objects appear to be special cases of the radio selected quasars; some compact radio sources show the possibility of synchrotron self-Compton (SSC) in the optical band; and the spectral index between the optical and the X-ray bands depends on the optical luminosity.

Isobe, T.↗
DOE OSTI2020

Considerations for AMI-Based Operations for Distribution Feeders

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Leon, Sami↗