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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Temporal Ni K-Edge X-ray Absorption Spectroscopy Study Reveals the Kinetics of the Ni Redox Behavior of the Iron-Nickel Oxide Bimetallic OER Catalyst

Operando X-ray absorption spectroscopy (XAS) can be utilized to probe the phase and structural changes of FeNiOx and similar transition metal oxide electrocatalysts during electrocatalytic reactions. However, capturing the temporal changes occurring in the operando chemistry of electrocatalysts has been little studied. Here, in this work, we successfully capture the time-resolved changes at the Ni K-edge for both the X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) regions of an aqueous phase synthesized FeNiO x bimetallic nanoparticle electrocatalyst. During a stepped voltage experiment, the temporal change in the Ni K-edge was observed as the applied voltage was stepped from 0.7 to 0.8 V versus the silver/silver chloride reference electrode, and the change observed is associated with the Ni redox transition from the 2+ to 3+/4+ oxidation state. Individual XAS spectra were obtained in 90 s, and a total of 9 scans post voltage step showed a unique transition from a hydroxide to an oxyhydroxide phase. The shift in absorption edge energy position and the changes in spectral shape for individual scans explain the typically observed broadening of the Ni K-edge XANES spectrum during time-averaged operando XAS, and a kinetic analysis revealed a first-order observed rate constant, |k obs |, of 0.00426 s –1 and a half-life (t 1/2 ) of 163 s. Multivariate curve resolution-alternating least squares analysis followed by linear combination fitting analysis for time-averaged versus time-resolved Ni K-edge changes upon voltage step show distinct differences in estimated contributions from Ni 2+ oxide/hydroxide phases. Detailed EXAFS modeling shows the phase transition from hydroxide to oxyhydroxide on top of the unchanged metallic core.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multivariate Linear Models for In Situ Monitoring of Low-Activity Nuclear Waste Using Infrared and Raman Spectroscopy - 20218

This paper presents the use of in situ monitoring tools for molecular analysis of non-radioactive species found in the supernatant liquid and dissolvable salt cake of nuclear waste at Hanford. We have selected two in situ spectroscopic techniques that do not require any sample preparation or consumables: infrared (in the form of attenuated total reflectance Fourier transform infrared or ATR-FTIR) and Raman spectroscopy. This work aims to evaluate their performance for liquid waste simulants representative of the Hanford DFLAW (Direct Feed Low-Activity Waste) feed. In addition, we have evaluated the performance of four multivariate linear models that extract concentrations from spectral measurements for a data set that was designed to include key molecular species found in liquid low-activity waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1993

Polytopic vector analysis in igneous petrology: Application to lunar petrogenesis

Lunar samples represent a heterogeneous assemblage of rocks with complex inter-relationships that are difficult to decipher using standard petrogenetic approaches. These inter-relationships reflect several distinct petrogenetic trends as well as thermomechanical mixing of distinct components. Additional complications arise from the unequal quality of chemical analyses and from the fact that many samples (e.g., breccia clasts) are too small to be representative of the system from which they derived. Polytopic vector analysis (PVA) is a multi-variate procedure used as a tool for exploratory data analysis. PVA allows the analyst to classify samples and clarifies relationships among heterogenous samples with complex petrogenetic histories. It differs from orthogonal factor analysis in that it uses non-orthogonal multivariate sample vectors to extract sample endmember compositions. The output from a Q-mode (sample based) factor analysis is the initial step in PVA. The Q-mode analysis, using criteria established by Miesch and Klovan and Miesch, is used to determine the number of endmembers in the data system. The second step involves determination of endmembers and mixing proportions with all output expressed in the same geochemical variable as the input. The composition of endmembers is derived by analysis of the variability of the data set. Endmembers need not be present in the data set, nor is it necessary for their composition to be known a priori. A set of any endmembers defines a 'polytope' or classification figure (triangle for a three component system, tetrahedron for a four component system, a 'five-tope' in four dimensions for five component system, et cetera).

Shervais, John W.↗
DOE OSTI2021

Survey on stochastic distribution systems: A full probability density function control theory with potential applications

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.

42 ENGINEERING↗
NASA NTRS1980

Sensor failure and multivariable control for airbreathing propulsion systems

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Behbehani, K.↗
NASA NTRS1991

Progress in multirate digital control system design

A new methodology for multirate sampled-data control design based on a new generalized control law structure, two new parameter-optimization-based control law synthesis methods, and a new singular-value-based robustness analysis method are described. The control law structure can represent multirate sampled-data control laws of arbitrary structure and dynamic order, with arbitrarily prescribed sampling rates for all sensors and update rates for all processor states and actuators. The two control law synthesis methods employ numerical optimization to determine values for the control law parameters. The robustness analysis method is based on the multivariable Nyquist criterion applied to the loop transfer function for the sampling period equal to the period of repetition of the system's complete sampling/update schedule. The complete methodology is demonstrated by application to the design of a combination yaw damper and modal suppression system for a commercial aircraft.

Berg, Martin C.↗
NASA NTRS1990

Determination of washout performance of various monochrome displays under simulated flight ambient and solar lighting conditions

The aircraft cockpit ambient lighting simulation system (ACALSS) has been developed to study display readability and associated pilot/vehicle performance effects in a part-task simulator cockpit. In the study reported here, the ACALSS was used to determine the illumination levels at which subjects lose the ability to maintain aircraft states when using three display technologies as display media for primary flight displays: a standard monochrome EL (electroluminescent) flat-panel, a laboratory-class monochrome CRT, and an enhanced-brightness EL flat-panel. The multivariate statistical technique of modified profile analysis was used to test for performance differences between display devices as functions of illumination levels. The standard monochrome EL flat-panel display began to washout after the 2500 foot-candle level of illumination. The monochrome CRT began to washout after the 5500 foot-candle level of illumination. No performance decrements by increased illumination up to the 12,000 foot-candle level were found for the enhanced-brightness EL flat-panel display. What was not anticipated was that half the subjects would subjectively prefer the CRT over the enhanced-brightness EL, even though their performance errors would have indicated the opposite.

Batson, Vernon M.↗
NASA NTRS1994

Regional climates in the GISS general circulation model: Surface air temperature

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Hewitson, Bruce↗
NASA NTRS1997

An Assessment of the Regional Distribution of the Oxygen-Isotope Ratio in Northeastern Canada

A compilation of mean values of the oxygen-isotope ratio relative to standard mean ocean Water for 22 sites representative of conditions in north-eastern Canada is complemented with data on mean annual surface temperature, latitude, surface elevation, and mean annual shortest distance to open ocean denoted by the 10% sea-ice concentration boundary. Stepwise regression analysis is used to develop a multivariate model suitable to infer the distribution of 6 1"0 in an area of complex topography and possibly mixed source of advected water vapor. The best model is produced by a run in the backward mode at the 95% confidence level in which only temperature, latitude and distance to the open ocean remain in the model (the correlation coefficient is 0.915, the adjusted coefficient of determination is 0.809, the root mean square residual is 1.62). This model is similar to the best 6180 predictive model derived elsewhere for Greenland, suggesting a common principal source of advected moisture.

Giovinetto, Mario B.↗
NASA NTRS1999

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Tripp, John S.↗
DOE OSTI2020

Non-Gaussianity in the weak lensing correlation function likelihood – implications for cosmological parameter biases

ABSTRACT We study the significance of non-Gaussianity in the likelihood of weak lensing shear two-point correlation functions, detecting significantly non-zero skewness and kurtosis in 1D marginal distributions of shear two-point correlation functions in simulated weak lensing data. We examine the implications in the context of future surveys, in particular LSST, with derivations of how the non-Gaussianity scales with survey area. We show that there is no significant bias in 1D posteriors of Ωm and σ8 due to the non-Gaussian likelihood distributions of shear correlations functions using the mock data (100 deg2). We also present a systematic approach to constructing approximate multivariate likelihoods with 1D parametric functions by assuming independence or more flexible non-parametric multivariate methods after decorrelating the data points using principal component analysis (PCA). While the use of PCA does not modify the non-Gaussianity of the multivariate likelihood, we find empirically that the 1D marginal sampling distributions of the PCA components exhibit less skewness and kurtosis than the original shear correlation functions. Modelling the likelihood with marginal parametric functions based on the assumption of independence between PCA components thus gives a lower limit for the biases. We further demonstrate that the difference in cosmological parameter constraints between the multivariate Gaussian likelihood model and more complex non-Gaussian likelihood models would be even smaller for an LSST-like survey. In addition, the PCA approach automatically serves as a data compression method, enabling the retention of the majority of the cosmological information while reducing the dimensionality of the data vector by a factor of ∼5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The controlling role of atmosphere in dawsonite versus gibbsite precipitation from tetrahedral aluminate species

In highly alkaline solution, aluminum speciates as the tetrahedrally coordinated aluminate monomer, Al(OH)4- and/or dimer Al2O(OH)62-, yet precipitates as octahedrally coordinated gibbsite (Al(OH)3). This tetrahedral to octahedral transformation governs Al precipitation, which is crucial to worldwide Al production, and to the processing of caustic high-level radioactive wastes. Despite its significance, the transformation pathway remains unknown. Here we explore the roles of atmospheric water and carbon dioxide in mediating the transformation of the tetrahedrally coordinated potassium aluminate dimer salt (K2Al2O(OH)6) to gibbsite versus potassium dawsonite (KAl(CO3)(OH)2). A combination of in-situ attenuated total reflection infrared spectroscopy, ex-situ micro X-ray diffraction, and multivariate curve resolution-alternating least squares chemometrics analysis reveals that humidity plays a key role in the transformation by limiting the amount of alkalinity neutralization by dissolved CO2. Lower humidity favors higher alkalinity and incorporation of carbonate species in the final Al product to form KAl(CO3)(OH)2. Higher humidity enables more acid generation that destabilizes dawsonite and favors gibbsite as the solubility limiting phase. Because the transformation was restricted to occur in thin water films, the results suggest that transition from tetra- to octahedrally coordinated Al does not have to occur in bulk solution, as has often been hypothesized, but may instead appear on the source mineral surface.

Dembowski, Mateusz↗
NASA NTRS1985

Sensitivity analysis of automatic flight control systems using singular value concepts

A sensitivity analysis is presented that can be used to judge the impact of vehicle dynamic model variations on the relative stability of multivariable continuous closed-loop control systems. The sensitivity analysis uses and extends the singular-value concept by developing expressions for the gradients of the singular value with respect to variations in the vehicle dynamic model and the controller design. Combined with a priori estimates of the accuracy of the model, the gradients are used to identify the elements in the vehicle dynamic model and controller that could severely impact the system's relative stability. The technique is demonstrated for a yaw/roll damper stability augmentation designed for a business jet.

Herrera-Vaillard, A.↗
NASA NTRS2005

Self-Organizing-Map Program for Analyzing Multivariate Data

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Li, P. Peggy↗
NASA NTRS1993

Linear, multivariable robust control with a mu perspective

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

Packard, Andy↗
NASA NTRS1994

Robustness of reduced-order multivariable state-space self-tuning controller

In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

Yuan, Zhuzhi↗