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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms

Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeated on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.

58 GEOSCIENCES↗
DOE OSTI2016

Design of low surface roughness-low residual stress-high optoelectronic merit a-IZO thin films for flexible OLEDs

The development of efficient and reliable large-area flexible optoelectronic devices demands low surface roughness-low residual stress-high optoelectronic merit transparent conducting oxide (TCO) thin films. Here, we correlate surface roughness-residual stress-optoelectronic properties of sputtered amorphous indium zinc oxide (a-IZO) thin films using a statistical design of experiment (DOE) approach and find a common growth space to achieve a smooth surface in a stress-free and high optoelectronic merit a-IZO thin film. The sputtering power, growth pressure, oxygen partial pressure, and RF/(RF+DC) are varied in a two-level system with a full factorial design, and results are used to deconvolve the complex growth space, identifying significant control growth parameters and their possible interactions. The surface roughness of a-IZO thin film varies over 0.19 nm to 3.97 nm, which is not in line with the general assumption of low surface roughness in a-IZO thin films. The initial regression model and analysis of variance reveal no single optimum growth sub-space to achieve low surface roughness (≤0.5 nm), low residual stress (−1 to 0 GPa), and industrially acceptable electrical conductivity (>1000 S/cm) for a-IZO thin films. The extrapolation of growth parameters in light of the current results and previous knowledge leads to a new sub-space, resulting in a low residual stress of −0.52±0.04 GPa, a low surface roughness of 0.55±0.03 nm, and moderate electrical conductivity of 1962±3.84 S/cm in a-IZO thin films. These results demonstrate the utility of the DOE approach to multi-parameter optimization, which provides an important tool for the development of flexible TCOs for the next-generation flexible organic light emitting diodes applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1988

Initial blood storage experiment

The design of the Initial Blood Storage Experiment (IBSE) was based upon a carefully controlled comparison between identical sets of human blood cell suspensions - red cells, white cell, and platelets - one set of which was transported aboard the Columbia on a 6 day 11 hour mission, and the other held on the ground. Both sets were carried inside stainless steel dewars within specially fabricated flight hardware. Individual bags of cell suspensions were randomly assigned with respect to ground vs orbit status, dewar chamber, and specific location within the dewar. To foster optimal preservation, each cell type was held under specific optimal conditions of pH, ionic strength, solute concentration, gas tension, and temperature. An added variable in this initial experiment was provided by the use of three different polymer/plasticizer formulations for the sealed bags which held the blood cells. At termination of the experiment, aliquots of the suspensions, identified only by code, were distributed to be assayed. Assays were selected to constitute a broad survey of cellular properties and thereby maximize the chances of detection of gravitational effects. A total of 74 different outcome measurements were reported for statistical analysis. When the measurements were completed, the results were entered into the IBSE data base, at which time the data were matched with the original blood bag numbers to determine their status with respect to polymer/plasticizer type, orbit status (orbit or ground), and storage position within the experimental hardware. The data were studied by analysis of variance. Initially, type of bag and orbital status were main factors; later more detailed analyses were made on specific issues such as position in the hardware and specific plastic. If the analysis of variance indicated a statistical significance at the 5 percent level the corresponding p-value was reported.

Surgenor, Douglas MACN.↗
NASA NTRS1983

Repeated-Measures Analysis of Image Data

It is suggested that using a modified analysis of variance procedure on data sampled systematically from a rectangular array of image data can provide a measure of homogeneity of means over that array in single directions and how variation in perpendicular directions interact. The modification of analysis of variance required to account for spatial correlation is described theoretically and numerically on simulated data.

Newton, H. J.↗
NASA NTRS1991

Display format, highlight validity, and highlight method: Their effects on search performance

Display format and highlight validity were shown to affect visual display search performance; however, these studies were conducted on small, artificial displays of alphanumeric stimuli. A study manipulating these variables was conducted using realistic, complex Space Shuttle information displays. A 2x2x3 within-subjects analysis of variance found that search times were faster for items in reformatted displays than for current displays. Responses to valid applications of highlight were significantly faster than responses to non or invalidly highlighted applications. The significant format by highlight validity interaction showed that there was little difference in response time to both current and reformatted displays when the highlight validity was applied; however, under the non or invalid highlight conditions, search times were faster with reformatted displays. A separate within-subject analysis of variance of display format, highlight validity, and several highlight methods did not reveal a main effect of highlight method. In addition, observed display search times were compared to search time predicted by Tullis' Display Analysis Program. Benefits of highlighting and reformatting displays to enhance search and the necessity to consider highlight validity and format characteristics in tandem for predicting search performance are discussed.

Donner, Kimberly A.↗
DOE OSTI2015

A surface layer variance heat budget for ENSO

Abstract Characteristics of the El Niño–Southern Oscillation (ENSO), such as frequency, propagation, spatial extent, and amplitude, strongly depend on the climatological background state of the tropical Pacific. Multidecadal changes in the ocean mean state are hence likely to modulate ENSO properties. To better link background state variations with low‐frequency amplitude changes of ENSO, we develop a diagnostic framework that determines locally the contributions of different physical feedback terms on the ocean surface temperature variance. Our analysis shows that multidecadal changes of ENSO variance originate from the delicate balance between the background‐state‐dependent positive thermocline feedback and the atmospheric damping of sea surface temperatures anomalies. The role of higher‐order processes and atmospheric and oceanic nonlinearities is also discussed. The diagnostic tool developed here can be easily applied to other tropical ocean areas and climate phenomena.

Boucharel, Julien↗
NASA NTRS2010

Impact of Damping Uncertainty on SEA Model Response Variance

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Schiller, Noah↗
DOE OSTI2013

Uncertainty quantification for evaluating impacts of caprock and reservoir properties on pressure buildup and ground surface displacement during geological CO2 sequestration

A series of numerical test cases reflecting broad and realistic ranges of geological formation properties was developed to systematically evaluate and compare the impacts of those properties on geomechanical responses to CO2 injection. A coupled hydro-geomechanical subsurface transport simulator, STOMP (Subsurface Transport over Multiple Phases), was adopted to simulate the CO2 migration process and geomechanical behaviors of the surrounding geological formations. A quasi-Monte Carlo sampling method was applied to efficiently sample a high-dimensional parameter space consisting of injection rate and 14 subsurface formation properties, including porosity, permeability, entry pressure, irreducible gas and aqueous saturation, Young’s modulus, and Poisson’s ratio for both reservoir and caprock. Generalized cross-validation and analysis of variance methods were used to quantitatively measure the significance of the 15 input parameters. Reservoir porosity, permeability, and injection rate were found to be among the most significant factors affecting the geomechanical responses to the CO2 injection. We used a quadrature generalized linear model to build a reduced-order model that can estimate the geomechanical response instantly instead of running computationally expensive numerical simulations.

CO2 geological sequestration↗
DOE OSTI2026

Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice

We present a description of the Antarctic Ice Sheet model configuration submitted to the ISMIP6-Antarctica-2300 experiment using the MPAS-Albany Land Ice model, along with three new sets of simulations: (1) a set of extended simulations to 2500 for three forced experiments and to 2775 for the control experiment; (2) a sensitivity analysis of our model configuration to parameters controlling basal sliding and sub-shelf melt, and to model structural choices including the choice of the energy and stress balances; and (3) a 72-member ensemble run on graphics processing units (GPUs) and analysis of variance to determine the primary sources of uncertainty in our ice-sheet model projections. Our extended simulations predict rapid retreat beginning after 2300 for SSP1-2.6 forcing and after 2500 for present-day (control) forcing, primarily in the Amundsen Sea Embayment. We find that varying the sub-shelf melt parameter between the 5th to 95th percentile values for a mean-Antarctic calibration target results in an up to ∼ ± 40 % change in sea-level contribution relative to our baseline simulations that used the median value. Using a linear basal sliding law reduces sea-level contribution by 51 %–73 % relative to our baseline nonlinear sliding law with an exponent of 1/5. When using basal sliding law exponents of 1/3 and 1/10, the overall difference from our baseline simulations at 2300 is on the order of 10 %. The Amundsen Sea Embayment region displays a strongly non-linear dependence of mass loss on the sliding law exponent, with no discernible relationship between the sliding law exponent and the mass loss by 2300, while the sectors feeding the Ross and Filchner-Ronne ice shelves exhibit more mass loss with a more-plastic sliding law. Our model fidelity sensitivity experiments reveal a 9 %–31 % increase in sea-level contribution when using a depth-integrated stress balance approximation relative to our three-dimensional solver, while using a fixed-in-time temperature field increases sea-level contribution by 14 %–88 % relative to two thermomechanically coupled configurations. Our 72-member ensemble and analysis of variance show that the uncertainty in long-term projections is dominated by the choice of Earth system model forcing and the presence or absence of hydrofracture forcing, rather than uncertainty in sliding and sub-shelf melt parameters.

58 GEOSCIENCES↗
DOE OSTI2014

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect—except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated great effectiveness in comparison with non-adaptive PCKF and EnKF algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

A further analysis for the minimum-variance deconvolution filter performance

Chi and Mendel (1984) analyzed the performance of minimum-variance deconvolution (MVD). In this correspondence, a further analysis of the performance of the MVD filter is presented. It is shown that the MVD filter performs like an inverse filter and a whitening filter as SNR goes to infinity, and like a matched filter as SNR goes to zero. The estimation error of the MVD filter is colored noise, but it becomes white when SNR goes to zero. This analysis also conects the error power-spectral density of the MVD filter with the spectrum of the causal-prediction error filter.

Chi, Chong-Yung↗
DOE OSTI2014

Parameters’ Covariance in Neutron Time of Flight Analysis – Explicit Formulae

We present here a method that estimates the parameters’ variance in a parametric model for neutron time of flight (NToF). The analytical formulae for parameter variances, obtained independently of calculation of parameter values from measured data, express the variances in terms of the choice, settings, and placement of the detector and the oscilloscope. Consequently, the method can serve as a tool in planning a measurement setup.

fusion↗
NASA NTRS2010

Finite Element Model Calibration Approach for Area I-X

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of non-conventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pretest predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Horta, Lucas G.↗
NASA NTRS2010

Finite Element Model Calibration Approach for Ares I-X

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of nonconventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pre-test predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Horta, Lucas G.↗
DOE OSTI2016

Variance components in confocal scanning laser tomography measurements of neuro‐retinal rim area and the effect of repeated measurements on the power to detect loss over time

Abstract Purpose To estimate the variation in measurements of neuro‐retinal rim area (NRA) determined by confocal scanning laser tomography and consequences for clinical follow‐up. Methods Altogether, 24 healthy subjects were randomized on –320 μ m, Moorfields and Standard NRA plane strategies. Additionally, NRA was measured in 32 glaucoma subjects. Variance components for subjects, visits and measurements were estimated with analysis of variance. Sample sizes required to detect a 6.0 × 10 −2 mm 2 NRA change were estimated assuming a significance level of 0.05 and a power of 0.8. Consequences for independent group, and paired comparison design, respectively, were analysed. Further, precision in estimates within subjects over time was investigated. Results The variation of NRA among subjects was considerably larger than the variation among visits and measurements. For glaucoma subjects, the variation among visits and measurements were of the same order but larger than in healthy subjects. It was found that independent group comparisons require inconveniently large sample sizes. Within‐subject paired comparisons over time require sample sizes of below 15 subjects. The estimated variations for glaucoma subjects imply that 54 months of follow‐up is required for detection of change from baseline. Conclusions The variance for subjects is substantial in relation to those for visits and measurements. Cross‐sectional independent group comparisons of levels of NRA are unsuitable, due to considerable subject variation. Levels of NRA differences within subjects between visits can be estimated with acceptable precision. Neuro‐retinal rim area (NRA) measurement can be used for long‐term follow‐up of glaucoma progression.

Sandberg Melin, Camilla↗