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Results for “Analysis of Variance”

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 1,045 records · Page 58

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NASA NTRS1997

Attitudinal Responses to Changes in Noise Exposure in Residential Communities

The purpose of this study is (1) to investigate the current body of knowledge encompassing two related topics: (a) to what extent can we reliably predict the change in people's attitudes in response to an abrupt change in noise exposure, and (b) after the change, is there a decay in the abrupt-change effect whereby people's attitudes slowly shift from their initial reaction to a steady-state value? and (2) to provide recommendations for any future work that may be needed. The literature search located 23 studies relating to one or both of the above topics. These prior studies shed considerable light on the current ability to predict initial reaction and decay effects. The literature makes one point very clear: Great care in both experimental design and data analysis is necessary to produce credible, convincing findings, both in the reanalysis of existing data and for planning future data acquisition and analysis studies. New airport studies must be designed to minimize nuisance variables and avoid past design features that may have introduced sufficient unexplained variance to mask sought after effects. Additionally, the study must be designed to tie in with previous investigations by incorporating similar survey questions and techniques.

Horonjeff, Richard D.↗

NASA NTRS2012

Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling

Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

Koster, Randal↗

DOE OSTI2023

MOOSE Optimization Module Overview: Application to Residual Stress Inversion in Nuclear Fuel Plates

Manufacturing methods, material selections and unique plate geometries used in low enriched uranium plate fuels for the High Performance Research Reactor (HPRR) have led to concerns about the residual stresses effect on bond strength of the fuel/cladding interfaces and overall fuel performance under irradiation. The current HPRR plate fuel test program performed residual stress calculations using the contour method with experimental displacement data obtained by incrementally cutting the plate fuel. In this work, we use a gradient based inverse optimization module developed within the MOOSE framework to estimate normal and shear residual stresses within the plate fuels using displacement data taken from a cut placed in the HPRR fuel plate. These results are verified against residual stress calculations obtained from the contour method. The inversion protocol used in this work utilizes two meshes to separately discretize the physics and parameter space. This allows a fine mesh to be used to fully resolve the physics and geometry of the forward problem. A coarser mesh is used to resolve the parameter space with spatially varying mesh density determined from a sensitivity analysis. The adaptive resolution of the parameter space essentially has the effect of regularization as it is designed to achieve the bias-variance tradeoff.

42 ENGINEERING↗

NASA NTRS1975

Canonical analysis and transformation of Skylab multispectral scanner data

The author has identified the following significant results. The original transformation matrix, C, had sixteen axes. However, the first three axes contained 98.83% of the variance contained within the transformation. The values for axes one, two, and three were 83.61%, 14.49%, and 0.72%, respectively. The result was an 81.25% reduction in data bulk. It is expected that using transformed data for classification will result in significant reductions in computer cost.

Mcmurtry, G. J.↗

NASA NTRS1992

Analysis of satellite-derived ozone and water vapor measurements

Research under this grant has involved analyses of satellite-derived measurements of water vapor and total ozone. Upper tropospheric water vapor data from the Nimbus 7 temperature-humidity infrared radiometer (THIR) 6.7 micron channel were analyzed by Fourier transformation to provide wavenumber spectra for a case of an upper level system over Europe. The power law spectrum for horizontal scales from 60 to several hundred km suggests that when convective cloud energy sources are not present, the enstrophy-cascading process (with variance proportional to the minus three power of wavenumber) may hold to much smaller scales than previously thought. Several investigations of the middle atmosphere (stratosphere and mesosphere) were also conducted. Slow atmospheric oscillations with periods of 1-2 months were investigated in total ozone measurements and in ionospheric data. Using one-point correlation maps and total ozone mapping spectrometer (TOMS) data, strong statistical evidence was found for the planetary-scale oscillations at these periods. A dipole-like pattern in the tropical equatorial Indian ocean-western Pacific region was documented, along with wavetrain-like patterns emanating into the extratropics. While attempting to follow the oscillations upward above stratosphere, oscillations were studied in ionospheric data (D-region radio wave absorption, in the upper mesosphere, around 80-90 km altitude). Cross-spectral analyses with solar flux data revealed that much of the observed 1-2 month variance in the ionospheric D-region was well correlated to solar variations. Further research has involved investigations of the photochemical lifetime of greenhouse gases methane and nitrous oxide. Using Nimbus 7 satellite data, a new analysis technique was employed to determine the lifetime of these gases in situ in the upper stratosphere. The lifetimes are found to be in good agreement with theoretical estimates.

Stanford, John L.↗

DOE OSTI2023

Utilizing the maximum likelihood estimator for flow analysis

We explore the possibility of evaluating flow harmonics by employing the maximum likelihood estimator (MLE). For a given finite multiplicity, the MLE simultaneously furnishes estimations for all the parameters of the underlying distribution function while efficiently suppressing the variance of measures. Also, the method provides a means to assess a specific class of mixed harmonics, which is not straightforwardly feasible by the approaches primarily based on particle correlations. The results are analyzed using the Wald, likelihood ratio, and score tests of hypotheses. Besides, the resultant flow harmonics obtained using MLE are compared with those derived using particle correlations and event plane methods. Here, the dependencies of extracted flow harmonics on the multiplicity of individual events and the total number of events are analyzed. It is shown that the proposed approach works efficiently to deal with the deficiency in detector acceptability. Moreover, we elaborate on a fictitious scenario where the event plane is not a well-defined quantity in the distribution function. For the latter case, the MLE is shown to largely perform better than the two-particle correlation estimator. In this regard, one concludes that the MLE furnishes a meaningful alternative to the existing approaches for flow analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1994

Linking boundary-layer circulations and surface processes during FIFE89. Part 1: Observational analysis

Surface, aircraft, and satellite observations are analyzed for the 21-day 1989 intensive field campaign of the First ISLSCP Field Experiment (FIFE) to determine the effect of precipitation, vegetation, and soil moisture distributions on the thermal properties of the surface including the heat and moisture fluxes, and the corresponding response in the boundary-layer circulation. Mean and variance properties of the surface variables are first documented at various time and space scales. These calculations are designed to set the stage for Part 2, a modeling study that will focus on how time-space dependent rainfall distribution influences the intensity of the feedback between a vegetated surface and the atmospheric boundary layer. Further analysis shows strongly demarked vegetation and soil moisture gradients extending across the FIFE experimental site that were developed and maintained by the antecedent and ongoing spatial distribution of rainfall over the region. These gradients are shown to have a pronounced influence on the thermodynamic properties of the surface. Furthermore, perturbation surface wind analysis suggests for both short-term steady-state conditions and long-term averaged conditions that the gradient pattern maintained a diurnally oscillating local direct circulation with perturbation vertical velocities of the same order as developing cumulus clouds. Dynamical and scaling considerations suggest that the embedded perturbation circulation is driven by surface heating/cooling gradients and terrain ef fects rather than the manifestation of an inertial oscillation. The implication is that at even relatively small scales (less than 30 km), the differential evolution in vegetation density and soil moisture distribution over a relatively homogenous ecotone can give rise to preferential boundary-layer circulations capable of modifying local-scale horizontal and vertical motions.

Smith, Eric A.↗

DOE OSTI2017

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.

correlation↗

DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗

DOE OSTI2018

Identifying structural changes with unsupervised machine learning methods

In this work, unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

42 ENGINEERING↗

DOE OSTI2018

Characterization of Aspergillus niger Isolated from the International Space Station

The initial characterization of the Aspergillus niger isolate JSC-093350089, collected from U.S. segment surfaces of the International Space Station (ISS), is reported, along with a comparison to the extensively studied strain ATCC 1015. Whole-genome sequencing of the ISS isolate enabled its phylogenetic placement within the A. niger/welwitschiae/lacticoffeatus clade and revealed that the genome of JSC-093350089 is within the observed genetic variance of other sequenced A. niger strains. The ISS isolate exhibited an increased rate of growth and pigment distribution compared to a terrestrial strain. Analysis of the isolate’s proteome revealed significant differences in the molecular phenotype of JSC-093350089, including increased abundance of proteins involved in the A. niger starvation response, oxidative stress resistance, cell wall modulation, and nutrient acquisition. Together, these data reveal the existence of a distinct strain of A. niger on board the ISS and provide insight into the characteristics of melanized fungal species inhabiting spacecraft environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method

The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysis that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Computational Evaluation of Neutron Multiplicity Measurements of Polyethylene-Reflected Plutonium Metal

Simulations of neutron multiplicity measurements of a highly multiplicative plutonium sphere measured with a moderated array of 3 He proportional counters have consistently overpredicted the mean and variance of the measured multiplicity distribution. In contrast, identical experiments using a 252 Cf source have been accurately simulated. This paper outlines a sensitivity analysis of several key parameters that could account for the overprediction in the simulation of the plutonium sphere. Parameters that were analyzed include source-detector distance, detector dead time, variations in density and volume of the plutonium, and the value of v for 239 Pu-induced fission. Of these parameters, the only factor that accounted for the overprediction within reasonable bounds was a change in the value of the 239 Pu $\bar{v}$ . The sensitivity analysis showed that a small change (1.14% reduction) in the value of $\bar{v}$ dramatically improved the simulated results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Achievable Accuracy and Precision of Timing with Dynasen Piezo Electric Pins

Piezo electric pins from Dynasen are often used in the shock and detonation community for triggering or timing purposes. The purpose of this memorandum is to document factors that affect the accuracy and precision that can be reasonably expected from using the pins. Three different pin types were used and repetition of ablative laser pulses were used to measure the time variation both for the same pin and similar pins from a lot. It was established that the standard deviation for a common shock between all pins was 190 ps and that the maximum variance between any two similar pins was 960 ps. Thus it is clear that uncertainty in the pin location, cable lengths and electrical signal analysis are likely to affect accuracy and precision from piezo pin-based measurements far more than inherent pin-to-pin variation. However, these measurements also demonstrate that with suffcient experimental care, these off-the-shelf piezo pins are capable of nanosecond accuracy and precision.

42 ENGINEERING↗

NASA NTRS1974

Threshold detection in an on-off binary communications channel with atmospheric scintillation

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Webb, W. E.↗

NASA NTRS1975

Threshold detection in an on-off binary communications channel with atmospheric scintillation

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Webb, W. E.↗

NASA NTRS1982

Synthesis of a modern/classical controller for large space structures

The paper is concerned with wide-sense stationary random vibrations of a representative large space structure subject to nonwhite excitations, and with synthesis of its controller amid modeling uncertainties due to truncated modes. Dynamics is analyzed by residue calculus in frequency domain. Steady state variance of a modal coordinate is shown to depend on, among other things, power spectral density of excitation at the modal frequency. Modal cost analysis is performed for an order reduction with a performance objective of attitude, attitude rate and energy control. Optimal and suboptimal output feedback controllers are compared. By treating deleted modes as an additive and a multiplicative perturbation in an idealized transfer function, the low frequency modes omitted according to modal cost analysis are found to cause instability. Finally, the size of the idealized model is shown to be governed by light damping and stringency in performance and stability specifications.

Hablani, H. B.↗

NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗