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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Structure analysis of simulated molecular clouds with the Δ-variance

Here, we employ the Δ-variance analysis and study the turbulent gas dynamics of simulated molecular clouds (MCs). Our models account for a simplified treatment of time-dependent chemistry and the non-isothermal nature of the gas. We investigate simulations using three different initial mean number densities of n 0 = 30, 100 and 300 cm -3 that span the range of values typical for MCs in the solar neighbourhood. Furthermore, we model the CO line emission in a post-processing step using a radiative transfer code. We evaluate Δ-variance spectra for centroid velocity (CV) maps as well as for integrated intensity and column density maps for various chemical components: the total, H 2 and 12 CO number density and the integrated intensity of both the 12 CO and 13 CO (J = 1 → 0) lines. The spectral slopes of the Δ-variance computed on the CV maps for the total and H 2 number density are significantly steeper compared to the different CO tracers. We find slopes for the linewidth–size relation ranging from 0.4 to 0.7 for the total and H 2 density models, while the slopes for the various CO tracers range from 0.2 to 0.4 and underestimate the values for the total and H 2 density by a factor of 1.5–3.0. We demonstrate that optical depth effects can significantly alter the Δ-variance spectra. Furthermore, we report a critical density threshold of 100 cm -3 at which the Δ-variance slopes of the various CO tracers change sign. We thus conclude that carbon monoxide traces the total cloud structure well only if the average cloud density lies above this limit.

79 ASTRONOMY AND ASTROPHYSICS↗
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 NTRS1980

Stratum variance estimation for sample allocation in crop surveys

The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

Perry, C. R., Jr.↗
NASA NTRS1995

Variances of the components and magnitude of the polar heliospheric magnetic field

The heliolatitude dependences of the variances in the components and the magnitude of the heliospheric magnetic field have been analysed, using the Ulysses magnetic field observations from close to the ecliptic plane to 80 southern solar latitude. The normalized variances in the components of the field increased significantly (by a factor about 5) as Ulysses entered the purely polar flows from the southern coronal hole. At the same time, there was at most a small increase in the variance of the field magnitude. The analysis of the different components indicates that the power in the fluctuations is not isotropically distributed: most of the power is in the components of the field transverse to the radial direction. Examining the variances calculated over different time scales from minutes to hours shows that the anisotropy of the field variances is different on different scales, indicating the influence of the two distinct populations of fluctuations in the polar solar wind which have been previously identified. We discuss these results in terms of evolutionary, dynamic processes as a function of heliocentric distance and as a function of the large scale geometry of the magnetic field associated with the polar coronal hole.

Balogh, A.↗
DOE OSTI2013

Variance estimates for transport in stochastic media by means of the master equation

The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Discrete ordinates analysis of the forced-flight variance reduction technique in Monte Carlo neutral particle transport simulations

This paper presents mathematical formulations and methods to predict the effect of forced-flight variance reduction on Monte Carlo tally variance and calculation time. This includes deducing biasing operators that are then used to construct a history-score probability density function (HSPDF), which represents all possible Monte Carlo random walks and gives the probability of a Monte Carlo history scoring in a tally from a particular phase-space position. The history-score moment equations (HSMEs), the statistical moments of the HSPDF, are then derived to calculate the statistical behavior of the Monte Carlo tally when forced-flight variance reduction is applied. In addition, the future-time equation (FTE) is derived to predict the Monte Carlo computational time as a result of applying forced-flight variance reduction. The solutions of the HSMEs and FTE can be used to predict Monte Carlo computational cost. Furthermore, this work also describes a discrete ordinates method to solve the forced-flight HSMEs and FTE. Several 1-D and 2-D test problems verify that the derivations are performed and implemented correctly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient ( r ) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems

Motivated by the spurious variance loss encountered during covariance propagation in atmospheric and other large-scale data assimilation systems, we consider the problem for state dynamics governed by the continuity and related hyperbolic partial differential equations. This loss of variance has been attributed to reduced-rank representations of the covariance matrix, as in ensemble methods for example, or else to the use of dissipative numerical methods. Through a combination of analytical work and numerical experiments, we demonstrate that significant variance loss, as well as gain, typically occurs during covariance propagation, even at full rank. The cause of this unusual behavior is a discontinuous change in the continuum covariance dynamics as correlation lengths become small, for instance in the vicinity of sharp gradients in the velocity field. This discontinuity in the covariance dynamics arises from hyperbolicity: the diagonal of the kernel of the covariance operator is a characteristic surface for advective dynamics. Our numerical experiments demonstrate that standard numerical methods for evolving the state are not adequate for propagating the covariance, because16they do not capture the discontinuity in the continuum covariance dynamics as correlations lengths tend to zero. Our analytical and numerical results show that this leads to significant, spurious variance loss in certain regions, and gain in others. The results suggest that developing local covariance propagation methods designed specifically to capture covariance evolution near the diagonal may prove a useful alternative to current methods of covariance propagation.

covariance propagation↗
DOE OSTI2019

Investigation of the Window Variance Noise Component of Multicomponent Signals

Signal partitioning or signal segmentation allows to perform data classification, prediction of signals’ behavior, and profound interpretation of obtained data. In accordance with the signal model some distribution characteristics of the window variance noise component are investigated. It was shown that when all true underlying signal components remain unchanged, the window variance noise component is gamma distributed. Applying window variance to multicomponent signal (i.e., pharmacokinetic curve), it was shown that the window variance allows to split visually the signal record into phases due to prevalent processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Merging flux-variance with surface renewal methods in the roughness sublayer and the atmospheric surface layer

In this article, Two micrometeorological methods utilizing high-frequency sampled air temperature were tested against eddy covariance (EC) sensible heat flux (𝐻) measurements at three sites representing agricultural, agro-forestry, and forestry systems. The two methods cover conventional and newly proposed forms of the flux-variance (FV) and surface renewal (SR) schemes of differing complexities. The sites represent measurements in surface, roughness, and roughness to surface transitional layers. Regression analyzes against EC show that the most reliable FV and SR forms estimate 𝐻 with slopes within ±10% from unity and coefficient of determination 𝑅2 > 0.9 across all the three sites. The best performance of both FV and SR was found at the agricultural site with measurements well within the surface layer, while the worst was found for the tall forest with measurements within the roughness sublayer where its thickness needed to be additionally estimated. The main variable driving 𝐻 in FV is the temperature variance, whereas in SR, it is the geometry of ramp-like structures. Since these structures are also responsible for most of the temperature variance, a novel FV-SR approach emerging from combining the methods is proposed and evaluated against EC measurements and conventional FV and SR schemes. The proposed FV-SR approach requiring only a single fast response thermocouple is potentially independent of calibration and ameliorates some of the theoretical objections that arise when combining ramp statistics with similarity arguments. The combination of methods also provides new insights into the contribution of coherent structures to the temperature variance and its dependence on atmospheric stratification. Other potential utility of the new method is to include it in multi-tool assessments of surface energy fluxes, since a convergence or divergence of the results has a high diagnostic value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Decline in malaria incidence in a typical county of China: Role of climate variance and anti-malaria intervention measures

Highlights: • Malaria incidence shows a steeply interannual decline and an obvious seasonality. • Malaria incidence highly correlates to temperature, precipitation and humidity. • Two favorable climate conditions are determined for high incidence of malaria. • There is good agreement between a decreasing malaria incidence and slightly declined climate variance in epidemic months. • Malaria incidence is declined rapidly because of the persistent progress of anti-malaria interventions. Malaria is an important vector-borne disease which is widespread in tropical and subtropical areas worldwide as well as in south China. Previous research has separately focused on the association between malaria incidence and meteorological variables or between malaria incidence and anti-malaria intervention measures in China, especially in Yunnan Province. Therefore, a typical county, Tengchong County, in Yunnan Province with high malaria incidence was selected as the study area to investigate the integrated influence of climate variance and anti-malaria intervention measures. Malaria incidence and meteorological variables were analyzed with a 2-month lag. The variables include average monthly temperature, minimum temperature, maximum temperature, cumulative precipitation, wind speed, maximum wind speed, relative humidity and minimum relative humidity. First, the principal component analysis was introduced to investigate the relationship between malaria incidence and meteorological variables; classification and regression trees were used to clarify contributions of key meteorological variables to malaria incidence afterwards. Second, based on existing anti-malaria intervention measures and above results, the integrated impact of climate variance and anti-malaria interventions on interannual trends of malaria incidence was analyzed. High malaria incidence occurred under one of the two meteorological conditions: 1) high minimum temperature combined with high minimum relative humidity or both precipitation and minimum relative humidity above middle level; 2) middle minimum temperature combined with both precipitation and minimum relative humidity below middle levels. Moreover, the steep interannual decline of malaria incidence in Tengchong was determined by slight climate variance and persistent anti-malaria intervention measures during malaria epidemics, predominantly by the latter. These findings will provide evidence data for developing malaria surveillance strategies in China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Variance Reduction Factor of Nuclear Data for Integral Neutronics Parameters

We propose a new quantity, a variance reduction factor, to identify nuclear data for which further improvements are required to reduce uncertainties of target integral neutronics parameters. Important energy ranges can be also identified with this variance reduction factor. Variance reduction factors are calculated for several integral neutronics parameters. The usefulness of the variance reduction factors is demonstrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.

Geology↗
DOE OSTI2016

Quantum mechanical expansion of variance of a particle in a weakly non-uniform electric and magnetic field

We have solved the Heisenberg equation of motion for the time evolution of the position and momentum operators for a non-relativistic spinless charged particle in the presence of a weakly non-uniform electric and magnetic field. It is shown that the drift velocity operator obtained in this study agrees with the classical counterpart, and that, using the time dependent operators, the variances in position and momentum grow with time. The expansion rate of variance in position and momentum are dependent on the magnetic gradient scale length, however, independent of the electric gradient scale length. In the presence of a weakly non-uniform electric and magnetic field, the theoretical expansion rates of variance expansion are in good agreement with the numerical analysis. It is analytically shown that the variance in position reaches the square of the interparticle separation, which is the characteristic time much shorter than the proton collision time of plasma fusion. After this time, the wavefunctions of the neighboring particles would overlap, as a result, the conventional classical analysis may lose its validity. The broad distribution of individual particle in space means that their Coulomb interactions with other particles become weaker than that expected in classical mechanics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Constraining the local variance of H {sub 0} from directional analyses

We evaluate the local variance of the Hubble Constant H {sub 0} with low-z Type Ia Supernovae (SNe). Our analyses are performed using a hemispherical comparison method in order to test whether taking the bulk flow motion into account can reconcile the measurement of the Hubble Constant H {sub 0} from standard candles ( H {sub 0} = 73.8±2.4 km s{sup -1} Mpc {sup -1}) with that of the Planck's Cosmic Microwave Background data ( H {sub 0} = 67.8 ± 0.9km s{sup -1} Mpc{sup -1}). We obtain that H {sub 0} ranges from 68.9±0.5 km s{sup -1} Mpc{sup -1} to 71.2±0.7 km s{sup -1} Mpc{sup -1} through the celestial sphere (1 σ uncertainty), implying a Hubble Constant maximal variance of δ H {sub 0} = (2.30±0.86) km s{sup -1} Mpc{sup -1} towards the ( l,b ) = (315°,27°) direction. Interestingly, this result agrees with the bulk flow direction estimates found in the literature, as well as previous evaluations of the H {sub 0} variance due to the presence of nearby inhomogeneities. We assess the statistical significance of this result with different prescriptions of Monte Carlo simulations, obtaining moderate statistical significance, i.e., 68.7% confidence level (CL) for such variance. Furthermore, we test the hypothesis of a higher H {sub 0} value in the presence of a bulk flow velocity dipole, finding some evidence for this result which, however, cannot be claimed to be significant due to the current large uncertainty in the SNe distance modulus. Then, we conclude that the tension between different H {sub 0} determinations can plausibly be caused to the bulk flow motion of the local Universe, even though the current incompleteness of the SNe data set, both in terms of celestial coverage and distance uncertainties, does not allow a high statistical significance for these results or a definitive conclusion about this issue.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The variance of the locally measured Hubble parameter explained with different estimators

We study the expected variance of measurements of the Hubble constant, H {sub 0}, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N -body simulations. We compare the variance with that obtained by carrying out mock observations in the N-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H {sub 0} from CMB measurements and the value measured in the local universe, these considerations are important in light of the percent determination of the Hubble constant in the local universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The DESI N -body Simulation Project – II. Suppressing sample variance with fast simulations

ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\, h^{-3}\, \mathrm{Gpc}^{3}$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

cosmology: theory↗
DOE OSTI2023

What drives the variance of galaxy spectra?

We present a study aimed at understanding the physical phenomena underlying the formation and evolution of galaxies following a data-driven analysis of spectroscopic data based on the variance in a carefully selected sample. We apply principal component analysis (PCA) independently to three subsets of continuum-subtracted optical spectra, segregated into their nebular emission activity as quiescent, star-forming, and active galactic nuclei (AGNs). We emphasize that the variance of the input data in this work only relates to the absorption lines in the photospheres of the stellar populations. The sample is taken from the Sloan Digital Sky Survey (SDSS) in the stellar velocity dispersion range 100–150 km s −1 , to minimize the ‘blurring’ effect of the stellar motion. We restrict the analysis to the first three principal components (PCs) and find that PCA segregates the three types with the highest variance mapping SSP-equivalent age, along with an inextricable degeneracy with metallicity, even when all three PCs are included. Spectral fitting shows that stellar age dominates PC1, whereas PC2 and PC3 have a mixed dependence of age and metallicity. The trends support – independently of any model fitting – the hypothesis of an evolutionary sequence from star formation to AGN to quiescence. As a further test of the consistency of the analysis, we apply the same methodology in different spectral windows, finding similar trends, but the variance is maximal in the blue wavelength range, roughly around the 4000 Å break.

79 ASTRONOMY AND ASTROPHYSICS↗