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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 1,261 records · Page 70

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NASA NTRS1981

Deconvolution of wide field-of-view radiometer measurements of earth-emitted radiation. II - Analysis of first year of Nimbus 6 ERB data

The theory of deconvolution considered by Smith and Green (1981) is applied to Nimbus 6 data in order to interpret the data with the maximum obtainable resolution. Attention is given to the data sample, sun-contaminated measurements, the measurement model, the deconvolution, the degree variance, the spherical harmonic coefficients, the geographical distribution of longwave radiation, time histories of zonal coefficients, and the effect of a grid system. Degree variance plots for 12 months of longwave radiation data show that the limit for a spherical harmonic representation of the Nimbus 6 wide field-of-view longwave data is 12th degree. The degree variance plots also reveal that most of the power is in the lower degree terms. Contour maps of the radiation field show the geographical distribution of earth emitted radiant exitance for each month.

Bess, T. D.↗

DOE OSTI2015

Acoustic detection of cracks in the anvil of a large-volume cubic high-pressure apparatus

A large-volume cubic high-pressure apparatus with three pairs of tungsten carbide anvils is the most popular device for synthetic diamond production. Currently, the consumption of anvils is one of the important costs for the diamond production industry. If one of the anvils is fractured during the production process, the other five anvils in the apparatus may be endangered as a result of a sudden loss of pressure. It is of critical importance to detect and replace cracked anvils before they fracture for reduction of the cost of diamond production and safety. An acoustic detection method is studied in this paper. Two new features, nested power spectrum centroid and modified power spectrum variance, are proposed and combined with linear prediction coefficients to construct a feature vector. A support vector machine model is trained for classification. A sliding time window is proposed for decision-level information fusion. The experiments and analysis show that the recognition rate of anvil cracks is 95%, while the false-alarm rate is as low as 5.8 × 10{sup −4} during a time window; this false-alarm rate indicates that at most one false alarm occurs every 2 months at a confidence level of 90%. An instrument to monitor anvil cracking was designed based on a digital signal processor and has been running for more than eight months in a diamond production field. In this time, two anvil-crack incidents occurred and were detected by the instrument correctly. In addition, no false alarms occurred.

42 ENGINEERING↗

DOE OSTI2013

Isotropic three-dimensional MRI-Fricke-infused gel dosimetry

Purpose: Fricke-infused gel has been shown to be a simple and attainable method for the conformal measurement of absorbed radiation dose. Nevertheless, its accuracy is seriously hindered by the irreversible ferric ion diffusion during magnetic resonance imaging, particularly when three-dimensional (3D) dose measurement in radiosurgery is considered. In this study, the authors developed a fast three-dimensional spin-echo based Fricke gel dosimetry technique to reduce the adverse effects of ferric ion diffusion and to obtain an accurate isotropic 3D dose measurement. Methods: A skull shaped phantom containing Fricke-infused gel was irradiated using Leksell Gamma Knife. The rapid image-based dosimetry technique was applied with the use of a 3D fast spin-echo magnetic resonance imaging sequence. The authors mathematically derived and experimentally validated the correlations between dose-response characteristics and parameters of the 3D fast spin-echo MR imaging sequence. Absorbed dose profiles were assessed and compared to the calculated profiles given by the Gamma Knife treatment planning system. Coefficient of variance (CV%) and coefficient of determination (R{sup 2}) were used to evaluate the precision of dose-response curve estimation. The agreement between the measured and the planned 3D dose distributions was quantified by gamma-index analysis of two acceptance criteria. Results: Proper magnetic resonance imaging parameters were explored to render an accurate three-dimensional absorbed dose mapping with a 1 mm{sup 3} isotropic image resolution. The efficacy of the dose-response estimation was approved by an R{sup 2} > 0.99 and an average CV% of 1.6%. Average gamma pass-rate between the experimentally measured and GammaPlan calculated dose distributions were 83.8% and 99.7% for 2%/2 and 3%/3 mm criteria, respectively. Conclusions: With the designed MR imaging sequence and parameters, total 3D MR acquisition time was confined to within 20 min postirradiation, during which time ferric ion diffusion effects were negligible, thus enabling an accurate 3D radiation dose measurement.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-QI-14: Quantitative Variogram Detection of Mild, Unilateral Disease in Elastase-Treated Rats

Purpose: Determining the presence of mild or early disease in the lungs can be challenging and subjective. We present a rapid and objective method for evaluating lung damage in a rat model of unilateral mild emphysema based on a new approach to heterogeneity assessment. We combined octree decomposition (used in three-dimensional (3D) computer graphics) with variograms (used in geostatistics to assess spatial relationships) to evaluate 3D computed tomography (CT) lung images for disease. Methods: Male, Sprague-Dawley rats (232 ± 7 g) were intratracheally dosed with 50 U/kg of elastase dissolved in 200 μL of saline to a single lobe (n=6) or with saline only (n=5). After four weeks, 3D micro-CT images were acquired at end expiration on mechanically ventilated rats using prospective gating. Images were masked, and lungs were decomposed to homogeneous blocks of 2×2×2, 4×4×4, and 8×8×8 voxels using octree decomposition. The spatial variance – the square of the difference of signal intensity – between all pairs of the 8×8×8 blocks was calculated. Variograms – graphs of distance vs. variance - were made, and data were fit to a power law and the exponent determined. The mean HU values, coefficient of variation (CoV), and the emphysema index (EI) were calculated and compared to the variograms. Results: The variogram analysis showed that significant differences between groups existed (p<0.01), whereas the mean HU (p=0.07), CoV (p=0.24), and EI (p=0.08) did not. Calculation time for the variogram for a typical 1000 block decomposition was ∼6 seconds, and octree decomposition took ∼2 minutes. Decomposing the images prior to variogram calculation resulted in a ∼700x decrease in time as compared to other published approaches. Conclusions: Our results suggest that the approach combining octree decomposition and variogram analysis may be a rapid, non-subjective, and sensitive imaging-based biomarker for quantitative characterization of lung disease.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

PAO

PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters.

Hart, William↗

NASA NTRS1972

A simple Fourier analysis technique for measuring the dynamic response of manual control systems.

From a practical standpoint most dynamic response analysis techniques are complicated, expensive, and time consuming to mechanize and operate. Adaptive parameter tracking techniques partially overcome these faults, but they have prescribed forms which is an undesirable restriction for basic research. To overcome these drawbacks, an on-line Fourier analysis technique has been developed which deals only with the input and error signals in a manual feedback control system. Several sine waves are used for the input, and the on-line data measurement includes the error variance and a simple means for obtaining the sine and cosine transforms of the error signal at each of the input frequencies. From this relatively small amount of data, we show simple ways to compute the open- and closed-loop dynamic response at input frequencies and the relative amount of linearly correlated power in the error signal.

Allen, R. W.↗

NASA NTRS1984

Doppler lidar results from the San Gorgonio Pass experiments

During FY-84, the Doppler Lidar data from the San Gorgonio Pass experiments were analyzed, evaluated, and interpreted with regard to signal strength, signal width, magnitude and direction of velocity component and a goodness parameter associated with the expected noise level of the signal. From these parameters, a screening criteria was developed to eliminate questionable data. For the most part analysis supports the validity of Doppler Lidar data obtained at San Gorgonio Pass with respect to the mean velocity magnitude and direction. The question as to whether the Doppler width could be interpreted as a measure of the variance of the turbulence within the Doppler Lidar System (DLS) focal volume was not resolved. The stochastic nature of the Doppler broadening from finite residence time of the particles in the beam as well as other Doppler broadening phenomenon tend to mask the Doppler spread associated with small scale turbulence. Future tests with longer pulses may assist in better understanding.

Cliff, W. C.↗

NASA NTRS1986

Real-time flutter identification with close mode resolution

Real-time flutter prediction including close modes can be effectively estimated from turbulence or on-board excitation with an Extended Kalman Filter (EKF) approach. A physically based model form enables prediction of the damping rate as well as damping, giving a time to instability estimate with its variance. The approach is recursive and can operate asynchronously to drop data outliers and hence is quite robust. Its speed is reasonable for on-line application but can also be used effectively as an off-line analysis tool for application to any modal testing situation.

Roy, R. H.↗

NASA NTRS2008

Stochastic Analysis of Orbital Lifetimes of Spacecraft

A document discusses (1) a Monte-Carlo-based methodology for probabilistic prediction and analysis of orbital lifetimes of spacecraft and (2) Orbital Lifetime Monte Carlo (OLMC)--a Fortran computer program, consisting of a previously developed long-term orbit-propagator integrated with a Monte Carlo engine. OLMC enables modeling of variances of key physical parameters that affect orbital lifetimes through the use of probability distributions. These parameters include altitude, speed, and flight-path angle at insertion into orbit; solar flux; and launch delays. The products of OLMC are predicted lifetimes (durations above specified minimum altitudes) for the number of user-specified cases. Histograms generated from such predictions can be used to determine the probabilities that spacecraft will satisfy lifetime requirements. The document discusses uncertainties that affect modeling of orbital lifetimes. Issues of repeatability, smoothness of distributions, and code run time are considered for the purpose of establishing values of code-specific parameters and number of Monte Carlo runs. Results from test cases are interpreted as demonstrating that solar-flux predictions are primary sources of variations in predicted lifetimes. Therefore, it is concluded, multiple sets of predictions should be utilized to fully characterize the lifetime range of a spacecraft.

Sasamoto, Washito↗

DOE OSTI2017

Fitting of Failure Rate Data to a Closed Form Solution using Gamma-Poisson Method of Moments

Due to the responsibility and gravity of estimation of nuclear power plant failure rates, it is required that there be consistent and accurate methodology for describing the likelihood of an event occurring. However, the methodology currently employed can vary dependent on the data, as well as subjective conjecture from the expert performing the analysis. The current implementation of the empirical Bayes method to a Gamma-Poisson (GaP) distribution utilizes algorithms to solve for the parameters that do not provide consistent answers. Additionally, to achieve a distribution of the likelihood, the variance of each parameter of the GaP must be determined. There does not exist an exact solution to one of the parameters variance and is typically estimated using techniques like the Kass-Steffey adjustment. Thus a new approach to the problem is proposed, built upon the method of moments for a negative binomial, based upon the work of Bradlow. Using the method of moments approach, we are able to achieve a closed form estimation of the mean and variance for each parameter in the negative binomial distribution. Due to the relationship between the negative binominal and GaP distribution, results can be made between the distributions. The hyper-priors defined assume beta prime distribution which is appropriately informed; the results of this application translate back to the Gamma distribution for easy utilization in SAPHIRE. Additionally several cases are explored using publically available NRC data that considers zero inflated, over dispersed, and Poisson data.

Failure Rate↗

DOE OSTI2022

HIDRA-MAT liquid metal droplet injector for liquid metal applications in HIDRA

A liquid metal droplet injector was explicitly designed for the Hybrid Illinois Device for Research and Applications Material Analysis Test-stand (HIDRA-MAT) at the University of Illinois Urbana-Champaign to prepare liquid metal plasma-facing components (PFCs) for plasma exposure. The design goals were to create a compact, reliable, and robust design that could apply liquid metal droplets in-vacuo to a variety of samples. The injector was designed for liquid metal use, and results discussed pertain to lithium. The injector can produce lithium droplets of consistent size by utilizing programmable piston movement. Here, droplet formation data is presented for four different piston step sizes (0.125 mm, 0.25 mm, 0.5 mm, and 1 mm) at three different nozzle temperatures (185 °C, 230 °C, and 270 °C). Droplets are formed on the injector nozzle tip and a linear shift mechanism vertically translates the droplet to the substrate for application. This design prevents the droplet from inadvertently detaching off the nozzle and falling to the sample. Application of the liquid metal droplet ensures placement consistency on the substrate and helps avoid damage to components in HIDRA-MAT that should not interact with liquid metals. A description of the liquid lithium droplet creation and application results is given and provides additional insight into the cooling and oxidation of lithium droplets under vacuum conditions. A second nozzle was fabricated and demonstrated repeatability in droplet diameter creation having a variance of ±0.14 mm for droplets created from the same number of piston steps. The end-use for the injector on HIDRA-MAT is to apply liquid metals to PFCs and expose them to HIDRA's plasma with subsequent intershot in-vacuo surface analysis in HIDRA-MAT for plasma-material interaction studies.

42 ENGINEERING↗

DOE OSTI2018

A study of appliance ownership and electricity consumption determinants in urban Ghanaian households

The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. Here this study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

O’Hare Airport Short-Term Ground Transportation Modal Demand Forecast Using Gaussian Processes

Here, the principal objective of this study is to analyze the spatial and temporal variation of ground transportation airport demand and provide demand forecast to inform planning capability and explore alternatives for investments to accommodate airport growth. Because of its good adaptability and strong generalization ability for dealing with high-dimensional input, small-sample, and nonlinear spatial data, Gaussian process (GP) regression is used to provide forecast estimates using data from transportation network company (TNC) trips and urban rail passengers at Chicago's O'Hare International Airport. TNC airport trips differ significantly, with three times more distance, more than twice the travel time, and half of the share requests compared with nonairport trips. This highlights the need for separate demand models. Hourly analysis of the rail service indicates that this is likely heavily used by airport workers, whereas TNC services focus on travelers because of variations in the peak demand hours. Heteroscedastic GP regression is implemented because of differences in trip variance between night and day hours. Estimates are given for weekdays and weekend trips, and the 95% confidence intervals are calculated. The introduction of flight schedule information into the models shows marginal improvements in their performance. However, fitting a GP regression becomes computationally expensive with increased sample size and the introduction of spatial components. Transportation planners and policymakers can use the results and methods implemented in this study to optimize transportation assets and provide long-range simulations of the current and future conditions in the area.

42 ENGINEERING↗

DOE OSTI2015

Performance of internal covariance estimators for cosmic shear correlation functions

Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\Omega_m$-$\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\gtrsim 85\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\Sigma_8 \sim \sigma_8 \Omega_m^{0.5}$ derived from internally estimated covariances is $\sim 90\%$ of the true uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Visual Instance-aware Prompt Tuning

Visual Prompt Tuning (VPT) has emerged as a parameter-efficient fine-tuning paradigm for vision transformers, with conventional approaches utilizing dataset-level prompts that remain the same across all input instances. We observe that this strategy results in sub-optimal performance due to high variance in downstream datasets. To address this challenge, we propose Visual Instance-aware Prompt Tuning (ViaPT), which generates instance-aware prompts based on each individual input and fuses them with dataset-level prompts, leveraging Principal Component Analysis (PCA) to retain important prompting information. Moreover, we reveal that VPT-Deep and VPT-Shallow represent two corner cases based on a conceptual understanding, in which they fail to effectively capture instance-specific information, while random dimension reduction on prompts only yields performance between the two extremes. Instead, ViaPT overcomes these limitations by balancing dataset-level and instance-level knowledge, while reducing the amount of learnable parameters compared to VPT-Deep. Extensive experiments across 34 diverse datasets demonstrate that our method consistently outperforms state-of-the-art baselines, establishing a new paradigm for analyzing and optimizing visual prompts for vision transformers.

Xiao, Xi [ORNL] (ORCID:0009000009316982)↗

DOE OSTI2014

Sensitivity Analysis and Data Assimilation in a Subcritical Plutonium Metal Benchmark

Here, this work presents the application of first-order adjoint sensitivity analysis, uncertainty quantification, and data assimilation to a subcritical plutonium benchmark experiment using a modified version of the discrete ordinates radiation transport code Denovo. Previous Monte Carlo simulations of this benchmark saw a consistent overprediction of the mean and variance of the measured neutron multiplicity distribution. It was observed that a small scalar reduction in the value of the 239 Pu-induced fission neutron multiplicity was capable of significantly reducing the discrepancies. This work extends those results by computing first-order sensitivities to each nuclide, reaction type, energy, and material region in the benchmark. The sensitivities are then used in a data assimilationmethodology to simultaneously calibrate all responses and multigroup nuclear data. The resulting best-estimate values for the energy group differential multiplicity $\bar{v}$(E g ) are 1σ to 2σ less than the nominal values found in ENDF/B-VII for energies less than 1.5 MeV.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2001

The AutoBayes Program Synthesis System: System Description

AUTOBAYES is a fully automatic program synthesis system for the statistical data analysis domain. Its input is a concise description of a data analysis problem in the form of a statistical model; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. AUTOBAYES synthesizes code by a schema-guided deductive process. Schemas (i.e., code templates with associated semantic constraints) are applied to the original problem and recursively to emerging subproblems. AUTOBAYES complements this approach by symbolic computation to derive closed-form solutions whenever possible. In this paper, we concentrate on the interaction between the symbolic computations and the deductive synthesis process. A statistical model specifies for each problem variable (i.e., data or parameter) its properties and dependencies in the form of a probability distribution, A typical data analysis task is to estimate the best possible parameter values from the given observations or measurements. The following example models normal-distributed data but takes prior information (e.g., from previous experiments) on the data's mean value and variance into account.

Fischer, Bernd↗

NASA NTRS2015

The Use of Absolute-Value Terms in Regression Modeling of Multi-Piece Force Balances

Different aspects of the use of absolute-value terms in regression models of the electrical outputs of multi-piece force balance calibration data are discussed. First, characteristics of a variety of regression model term combinations with absolute-value terms are reviewed that are currently used in the aerospace testing community to fit the gage outputs of a balance. Then, a semi-empirical test is presented that quantifies bidirectional characteristics of the balance bridge outputs. Several diagnostic methods are discussed to assess the severity of near-linear dependencies between regressors of models with absolute-value terms. In particular, connections between the linear, absolute-value, quadratic, signed quadratic, and cubic terms are studied in greater detail. Data from an automated calibration of NASAs MK29B force balance are used to illustrate the most important observations and results. Rules of thumb that variance-inflation factors be less than 10 must be relaxed when using absolute-value terms to describe bidirectional balances.

calibration analysis↗