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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 NTRS1974

NASTRAN variance analysis and plotting of HBDY elements

The NASTRAN Thermal Analyzer has been intended to do variance analysis and plot the thermal boundary elements. The objective of the variance analysis addition is to assess the sensitivity of temperature variances resulting from uncertainties inherent in input parameters for heat conduction analysis. The plotting capability provides the ability to check the geometry (location, size and orientation) of the boundary elements of a model in relation to the conduction elements. Variance analysis is the study of uncertainties of the computed results as a function of uncertainties of the input data. To study this problem using NASTRAN, a solution is made for both the expected values of all inputs, plus another solution for each uncertain variable. A variance analysis module subtracts the results to form derivatives, and then can determine the expected deviations of output quantities.

Harder, R. L.↗
NASA NTRS1972

Two-dimensional finite-element temperature variance analysis

The finite element method is extended to thermal analysis by forming a variance analysis of temperature results so that the sensitivity of predicted temperatures to uncertainties in input variables is determined. The temperature fields within a finite number of elements are described in terms of the temperatures of vertices and the variational principle is used to minimize the integral equation describing thermal potential energy. A computer calculation yields the desired solution matrix of predicted temperatures and provides information about initial thermal parameters and their associated errors. Sample calculations show that all predicted temperatures are most effected by temperature values along fixed boundaries; more accurate specifications of these temperatures reduce errors in thermal calculations.

Heuser, J. S.↗
NASA NTRS1993

A multi-variance analysis in the time domain

Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.

Walter, Todd↗
NASA NTRS2013

View-angle-dependent AIRS Cloudiness and Radiance Variance: Analysis and Interpretation

Upper tropospheric clouds play an important role in the global energy budget and hydrological cycle. Significant view-angle asymmetry has been observed in upper-level tropical clouds derived from eight years of Atmospheric Infrared Sounder (AIRS) 15 um radiances. Here, we find that the asymmetry also exists in the extra-tropics. It is larger during day than that during night, more prominent near elevated terrain, and closely associated with deep convection and wind shear. The cloud radiance variance, a proxy for cloud inhomogeneity, has consistent characteristics of the asymmetry to those in the AIRS cloudiness. The leading causes of the view-dependent cloudiness asymmetry are the local time difference and small-scale organized cloud structures. The local time difference (1-1.5 hr) of upper-level (UL) clouds between two AIRS outermost views can create parts of the observed asymmetry. On the other hand, small-scale tilted and banded structures of the UL clouds can induce about half of the observed view-angle dependent differences in the AIRS cloud radiances and their variances. This estimate is inferred from analogous study using Microwave Humidity Sounder (MHS) radiances observed during the period of time when there were simultaneous measurements at two different view-angles from NOAA-18 and -19 satellites. The existence of tilted cloud structures and asymmetric 15 um and 6.7 um cloud radiances implies that cloud statistics would be view-angle dependent, and should be taken into account in radiative transfer calculations, measurement uncertainty evaluations and cloud climatology investigations. In addition, the momentum forcing in the upper troposphere from tilted clouds is also likely asymmetric, which can affect atmospheric circulation anisotropically.

AIRS↗
NASA NTRS1996

Variance Analysis of Unevenly Spaced Time Series Data

We have investigated the effect of uneven data spacing on the computation of delta (sub chi)(gamma). Evenly spaced simulated data sets were generated for noise processes ranging from white phase modulation (PM) to random walk frequency modulation (FM). Delta(sub chi)(gamma) was then calculated for each noise type. Data were subsequently removed from each simulated data set using typical two-way satellite time and frequency transfer (TWSTFT) data patterns to create two unevenly spaced sets with average intervals of 2.8 and 3.6 days. Delta(sub chi)(gamma) was then calculated for each sparse data set using two different approaches. First the missing data points were replaced by linear interpolation and delta (sub chi)(gamma) calculated from this now full data set. The second approach ignored the fact that the data were unevenly spaced and calculated delta(sub chi)(gamma) as if the data were equally spaced with average spacing of 2.8 or 3.6 days. Both approaches have advantages and disadvantages, and techniques are presented for correcting errors caused by uneven data spacing in typical TWSTFT data sets.

Hackman, Christine↗
NASA NTRS1981

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Alston, D. W.↗
DOE OSTI2016

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analysis of Variance of Functional Data (F-ANOVA) [Slides]

Goals: What is Analysis of Variance (ANOVA); Extending Analysis of Variance to Function Data (F-ANOVA); The role of stochastic processes in F-ANOVA; One and Two Sample Problems for F-ANOVA; One-Way F-ANOVA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Allan Variance is Bootstrap Aggregation for Spectral Estimation

Characterization of clocks and inertial sensors, such as accelerometers and gyroscopes, typically includes Allan variance analysis. Allan variance is ubiquitous in timing and navigation communities which may appear niche compared with generalized spectral analysis. This note provides some motivation for Allan Variance for audiences more familiar with spectral analysis.

Walker, Michael Ray [Sandia National Laboratories ↗
DOE OSTI2014

SU-E-J-227: Breathing Pattern Consistency and Reproducibility: Comparative Analysis for Supine and Prone Body Positioning

Purpose: Evaluate and compare the cycle-to-cycle consistency of breathing patterns and their reproducibility over the course of treatment, for supine and prone positioning. Methods: Respiratory traces from 25 patients were recorded for sequential supine/prone 4DCT scans acquired prior to treatment, and during the course of the treatment (weekly or bi-weekly). For each breathing cycle, the average(AVE), end-of-exhale(EoE) and end-of-inhale( EoI) locations were identified using in-house developed software. In addition, the mean values and variations for the above quantities were computed for each breathing trace. F-tests were used to compare the cycle-to-cycle consistency of all pairs of sequential supine and prone scans. Analysis of variances was also performed using population means for AVE, EoE and EoI to quantify differences between the reproducibility of prone and supine respiration traces over the treatment course. Results: Consistency: Cycle-to-cycle variations are less in prone than supine in the pre-treatment and during-treatment scans for AVE, EoE and EoI points, for the majority of patients (differences significant at p<0.05). The few cases where the respiratory pattern had more variability in prone appeared to be random events. Reproducibility: The reproducibility of breathing patterns (supine and prone) improved as treatment progressed, perhaps due to patients becoming more comfortable with the procedure. However, variability in supine position continued to remain significantly larger than in prone (p<0.05), as indicated by the variance analysis of population means for the pretreatment and subsequent during-treatment scans. Conclusions: Prone positioning stabilizes breathing patterns in most subjects investigated in this study. Importantly, a parallel analysis of the same group of patients revealed a tendency towards increasing motion amplitude of tumor targets in prone position regardless of their size or location; thus, the choice for body positioning during radiation therapy will have to consider the clinical relevance of the two opposing trends - breathing consistency and motion amplitude.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

The stability of individual patterns of autonomic responses to motion sickness stimulation

As part of a program to develop a treatment for motion sickness based on self-regulation of autonomic nervous system (ANS) activity, this study examined the stability of an individual's pattern of ANS responses to motion sickness stimulation on repeated occasions. Motion sickness symptoms were induced in 58 people during two rotating chair test. Physiological responses measured were heart rate, finger pulse volume, respiration rate, and skin conductance. Using standard scores, stability of responses of specific magnitudes across both tests is as examined. Correlational analyses, analysis of variance, and a components of variance analysis all revealed marked, but quite stable, individual differences in ANS responses to both mild and severe motion sickness. These findings confirm the prior observation that people are sufficiently unique in their ANS responses to motion sickness provocation to make it nesessary to individually tailor self-regulation training. Further, these data support the contention that individual ANS patterns are sufficiently consistent from test to test so as to serve as an objective indicator of individual motion sickness malaise levels.

Cowings, Patricia S.↗
NASA NTRS1980

A VLBI variance-covariance analysis interactive computer program

An interactive computer program (in FORTRAN) for the variance covariance analysis of VLBI experiments is presented for use in experiment planning, simulation studies and optimal design problems. The interactive mode is especially suited to these types of analyses providing ease of operation as well as savings in time and cost. The geodetic parameters include baseline vector parameters and variations in polar motion and Earth rotation. A discussion of the theroy on which the program is based provides an overview of the VLBI process emphasizing the areas of interest to geodesy. Special emphasis is placed on the problem of determining correlations between simultaneous observations from a network of stations. A model suitable for covariance analyses is presented. Suggestions towards developing optimal observation schedules are included.

Bock, Y.↗
NASA NTRS1981

Applications of non-parametric statistics and analysis of variance on sample variances

Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

Myers, R. H.↗
NASA NTRS2010

Analysis of Variance in the Modern Design of Experiments

This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.

Deloach, Richard↗