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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A visual detection model for DCT coefficient quantization

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Ahumada, Albert J., Jr.↗
NASA NTRS1994

A new look at the simultaneous analysis and design of structures

The minimum weight optimization of structural systems, subject to strength and displacement constraints as well as size side constraints, was investigated by the Simultaneous ANalysis and Design (SAND) approach. As an optimizer, the code NPSOL was used which is based on a sequential quadratic programming (SQP) algorithm. The structures were modeled by the finite element method. The finite element related input to NPSOL was automatically generated from the input decks of such standard FEM/optimization codes as NASTRAN or ASTROS, with the stiffness matrices, at present, extracted from the FEM code ANALYZE. In order to avoid ill-conditioned matrices that can be encountered when the global stiffness equations are used as additional nonlinear equality constraints in the SAND approach (with the displacements as additional variables), the matrix displacement method was applied. In this approach, the element stiffness equations are used as constraints instead of the global stiffness equations, in conjunction with the nodal force equilibrium equations. This approach adds the element forces as variables to the system. Since, for complex structures and the associated large and very sparce matrices, the execution times of the optimization code became excessive due to the large number of required constraint gradient evaluations, the Kreisselmeier-Steinhauser function approach was used to decrease the computational effort by reducing the nonlinear equality constraint system to essentially a single combined constraint equation. As the linear equality and inequality constraints require much less computational effort to evaluate, they were kept in their previous form to limit the complexity of the KS function evaluation. To date, the standard three-bar, ten-bar, and 72-bar trusses have been tested. For the standard SAND approach, correct results were obtained for all three trusses although convergence became slower for the 72-bar truss. When the matrix displacement method was used, correct results were still obtained, but the execution times became excessive due to the large number of constraint gradient evaluations required. Using the KS function, the computational effort dropped, but the optimization seemed to become less robust. The investigation of this phenomenon is continuing. As an alternate approach, the code MINOS for the optimization of sparse matrices can be applied to the problem in lieu of the Kreisselmeier-Steinhauser function. This investigation is underway.

Striz, Alfred G.↗
NASA NTRS1995

Thermomechanical Fatigue Behavior of Three Cfcc's

The thermomechanical fatigue (TMF) behavior of three continuous-fiber ceramic composites (CFCC's) was examined. The three matrices consisted of two different glass-ceramics and silicon carbide, respectively. The matrices of some of the specimens with the silicon carbide matrix were enhanced to improve oxidation resistance. All three were reinforced with Nicalon fibers with various fiber architectures. The thermoelastic properties of the matrix relative to the fibers, the elastic moduli and coefficients of thermal expansion (CTE), were different in each composite, providing a comparison of the effects of these critical properties. The specimens were tested under in-phase (IP) and out-of-phase (OP) cyclic loadings with respect to thermal cycling between 600 C and 1100 C. One of the glass-ceramic composites had greatly increased TMF lives compared to the other glass-ceramic matrix composites. This was probably caused by the reversal of the CTE mismatch between the fibers and the matrices and caused by the different oxidation resistances of the composites. For the same TMF lives a cross-ply reinforced composite had a maximum cyclic stress half as great, as that of unidirectionally reinforced composite. This indicated that the (0 deg) ply fibers had a strong influence of TMF life. Both the glass ceramic matrix composites had shallow-slope stress-life plots that indicated sensitivity to damage and therefore low damage tolerance. The composites with an unenhanced silicon carbide matrix experienced the shortest TMF lives of all the CFCC's tested. However, the enhanced composite had the longest. Also, the enhanced composite demonstrated the best damage tolerance as evidenced by a stress-life curve that curves sharply upward to the left. In all the composites, out-of-phase cyclic loading was worse than in-phase cyclic loadings despite the CTE mismatch between fiber and matrix. A damage investigation and a preliminary analysis of the stresses in the fibers and matrices taking into account their respective thermoelastic properties provided insight into the relative behavior of the glass-ceramic matrix composites under IP and OP TMF.

Worthem, Dennis W.↗
NASA NTRS1996

Wavelet Sparse Approximate Inverse Preconditioners

There is an increasing interest in using sparse approximate inverses as preconditioners for Krylov subspace iterative methods. Recent studies of Grote and Huckle and Chow and Saad also show that sparse approximate inverse preconditioner can be effective for a variety of matrices, e.g. Harwell-Boeing collections. Nonetheless a drawback is that it requires rapid decay of the inverse entries so that sparse approximate inverse is possible. However, for the class of matrices that, come from elliptic PDE problems, this assumption may not necessarily hold. Our main idea is to look for a basis, other than the standard one, such that a sparse representation of the inverse is feasible. A crucial observation is that the kind of matrices we are interested in typically have a piecewise smooth inverse. We exploit this fact, by applying wavelet techniques to construct a better sparse approximate inverse in the wavelet basis. We shall justify theoretically and numerically that our approach is effective for matrices with smooth inverse. We emphasize that in this paper we have only presented the idea of wavelet approximate inverses and demonstrated its potential but have not yet developed a highly refined and efficient algorithm.

Chan, Tony F.↗
NASA NTRS1986

An improved approach to the analysis of drug-protein binding by distance geometry

The calculation of side chain centers of coordinates and the subsequent generation of side chain-side chain and side chain-backbone distance matrices is suggested as an improved method for viewing interactions inside proteins and for the comparison of protein structures. The use of side chain distance matrices is demonstrated with free PTI, and the use of difference distance matrices for side chains is shown for free and trypsin-bound PTI as well as for the X-ray structures of trypsin complexes with PTI and with benzamidine. It is found that conformational variations are reflected in the side chain distance matrices much more than in the standard C-C distance representations.

NASA Discipline Exobiology↗
NASA NTRS2005

The Mid-Infrared Absorption Spectra of Neutral PAHs in Dense Interstellar Clouds

Polycyclic aromatic hydrocarbons (PAHs) are common throughout the universe and are expected to be present in dense interstellar clouds. In these environments, some P.4Hs may be present in the gas phase, but most should be frozen into ice mantles or adsorbed onto dust grains and their spectral features are expected to be seen in absorption. Here we extend our previous work on the infrared spectral properties of the small PAH naphthalene (C10H8) in several media to include the full mid-infrared laboratory spectra of 11 other PAHs and related aromatic species frozen in H2O ices. These include the molecules 1,2-dihydronaphthalene, anthracene, 9,1O-dihydroanthracene, phenanthrene, pyrene, benzo[e]pyrene, perylene, benzo(k)fluoranthene, pentacene, benzo[ghi]perylene, and coronene. These results demonstrate that PAHs and related molecules, as a class, show the same spectral behaviors as naphthalene when incorporated into H2O-rich matrices. When compared to the spectra of these same molecules isolated in inert matrices (e.g., Ar or N2), the absorption bands produced when they are frozen in H2O matrices are broader (factors of 3-10), show small position shifts in either direction (usually < 4/cm, always < 10/cm), and show variable changes in relative band strengths (typically factors of 1-3). There is no evidence of systematic increases or decreases in the absolute strengths of the bands of these molecules when they are incorporated in H2O matrices. In H2O-rich ices, their absorption bands are relatively insensitive to concentration over the range of 10 < H2O/PAH < 200): The absorption bands of these molecules are also insensitive to temperature over the 10 K < T < 125 K range, although the spectra can show dramatic changes as the ices are warmed through the temperature range in which amorphous H2O ice converts to its cubic and hexagonal crystalline forms (T > 125 Kj. Given the small observed band shifts cause by H2O, the current database of spectra from Ar matrix-isolated neutral PAHs and related molecules should be useful for the search for these species in dense clouds on the basis of observed absorption band positions. Furthermore, these data permit determination of column densities to better than a factor of 3 for PAHs in dense clouds. Column density determination of detected aromatics to better than a factor of 3 will, however, require good knowledge about the nature of the matrix in which the PAH is embedded and laboratory studies of relevant samples.

Bernstein, M. P.↗
NASA NTRS2012

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗
NASA NTRS2013

Evidence for Extended Aqueous Alteration in CR Carbonaceous Chondrites

We are currently studying the chemical interrelationships between the main rockforming components of carbonaceous chondrites (hereafter CC), e.g. silicate chondrules, refractory inclusions and metal grains, and the surrounding meteorite matrices. It is thought that the fine-grained materials that form CC matrices are representing samples of relatively unprocessed protoplanetary disk materials [1-3]. In fact, modern non-destructive analytical techniques have shown that CC matrices host a large diversity of stellar grains from many distinguishable stellar sources [4]. Aqueous alteration has played a role in homogeneizing the isotopic content that allows the identification of presolar grains [5]. On the other hand, detailed analytical techniques have found that the aqueously-altered CR, CM and CI chondrite groups contain matrices in which the organic matter has experienced significant processing concomitant to the formation of clays and other minerals. In this sense, clays have been found to be directly associated with complex organics [6, 7]. CR chondrites are particularly relevant in this context as this chondrite group contains abundant metal grains in the interstitial matrix, and inside glassy silicate chondrules. It is important because CR are known for exhibiting a large complexity of organic compounds [8-10], and only metallic Fe is considered essential in Fischer-Tropsch catalysis of organics [11-13]. Therefore, CR chondrites can be considered primitive materials capable to provide clues on the role played by aqueous alteration in the chemical evolution of their parent asteroids.

Trigo-Rodriquez, J. M.↗
NASA NTRS2019

Observations on the Computation of Eigenvalue and Eigenvector Jacobians

Many scientific and engineering problems benefit from analytic expressions for eigenvalue and eigenvector derivatives with respect to the elements of the parent matrix. While there exists extensive literature on the calculation of these derivatives, which take the form of Jacobian matrices, there are a variety of deficiencies that have yet to be addressed — including the need for both left and right eigenvectors, limitations on the matrix structure, and issues with complex eigenvalues and eigenvectors. This work addresses these deficiencies by proposing a new analytic solution for the eigenvalue and eigenvector derivatives. The resulting analytic Jacobian matrices are numerically efficient to compute and are valid for the general complex case. It is further shown that this new general result collapses to previously known relations for the special cases of real symmetric matrices and real diagonal matrices. Finally, the new Jacobian expressions are validated using forward finite differencing and performance is compared with another technique.

Jacobian↗
DOE OSTI2020

Nanocomposite Ionogel Electrolytes for Solid‐State Rechargeable Batteries

Abstract Ionogels composed of ionic liquids and gelling solid matrices offer several advantages as solid‐state electrolytes for rechargeable batteries, including safety under diverse operating conditions, favorable electrochemical and thermal properties, and wide processing compatibility. Among gelling solid matrices, nanoscale materials have shown particular promise due to their ability to concurrently enhance ionogel mechanical properties, thermal stability, ionic conductivity, and electrochemical stability. These beneficial attributes suggest that ionogel electrolytes are not only of interest for incumbent lithium‐ion batteries but also for next‐generation rechargeable battery technologies. Herein, recent advances in nanocomposite ionogel electrolytes are discussed to highlight their advantages as solid‐state electrolytes for rechargeable batteries. By exploring a range of different nanoscale gelling solid matrices, relationships between nanoscale material structure and ionogel properties are developed. Furthermore, key research challenges are delineated to help guide and accelerate the incorporation of nanocomposite ionogel electrolytes in high‐performance solid‐state rechargeable batteries.

Hyun, Woo Jin↗
DOE OSTI2024

Flavor in SU(5)$SU(5)$ Finite Grand Unified Models

Abstract Four supersymmetric models which exhibit and/or symmetries are studied, that are finite to two or all loops, and their corresponding mass matrices. The first is an all‐loop finite model based on an flavor symmetry, which leads to phenomenologically nonviable mass matrices. The remaining models, based on cyclic symmetries, show various mass textures, some of which are phenomenologically promising. For the two‐loop finite models, the parametric solutions to the finiteness conditions determine completely some of the Yukawa couplings, and lead to a restricted range of values for other ones at the GUT scale, with a considerable reduction in the number of free parameters. One particular solution of the two‐loop models shows an enhanced symmetry, leading to an all‐loop finite model, which has a significant parameter reduction and could in principle reproduce the observed quark masses and mixing pattern. In this case the finiteness conditions determine the absolute value of all the Yukawa couplings at the unification scale. Finally, the minimum number of phases in the mass matrices and their position are determined, a task not previously done in Finite Unified Theories, which contributes towards the reduction of parameters and a better understanding of the Yukawa couplings.

Estrada Ramos, Luis Odín↗
DOE OSTI2024

e RPCA : Robust Principal Component Analysis for Exponential Family Distributions

Abstract Robust principal component analysis (RPCA) is a widely used method for recovering low‐rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low‐rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non‐Gaussian. We thus propose a new method called RPCA for exponential family distributions (), which can perform the desired decomposition into low‐rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient decomposition, under either its natural or canonical parametrization. The effectiveness of is then demonstrated in two applications: the first for steel sheet defect detection and the second for crime activity monitoring in the Atlanta metropolitan area.

Zheng, Xiaojun↗
DOE OSTI2020

The O(N) S-matrix monolith

We consider the scattering matrices of massive quantum field theories with no bound states and a global O(N) symmetry in two spacetime dimensions. In particular we explore the space of two-to-two S-matrices of particles of mass m transforming in the vector representation as restricted by the general conditions of unitarity, crossing, analyticity and O(N) symmetry. We found a rich structure in that space by using convex maximization and in particular its convex dual minimization problem. At the boundary of the allowed space special geometric points such as vertices were found to correspond to integrable models. The dual convex minimization problem provides a novel and useful approach to the problem allowing, for example, to prove that generically the S-matrices so obtained saturate unitarity and, insome cases, that they are at vertices of the allowed space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Dirac traces and the Tutte polynomial

Perturbative calculations involving fermion loops in quantum field theories require tracing over Dirac matrices. A simple way to regulate the divergences that generically appear in these calculations is dimensional regularisation, which has the consequence of replacing 4-dimensional Dirac matrices with d-dimensional counterparts for arbitrary complex values of d. In this work, a connection between traces of d-dimensional Dirac matrices and computations of the Tutte polynomial of associated graphs is proven. The time complexity of computing Dirac traces is analysed by this connection, and improvements to algorithms for computing Dirac traces are proposed.

Renormalization and Regularization↗
DOE OSTI2024

Separation of gold from irradiated actinide material utilizing a 2- thenoyltrifluoroacetone extraction resin

Post-detonation nuclear forensics capabilities depend on the ability to rapidly isolate radionuclides to improve measurement quality. In this work an extraction chromatography resin was developed utilizing the extractants thenoyltrifluoroacetone and 1-octanol supported on Eichrom prefilter resin. Here the resin was tested in nitric and hydrochloric acid matrices. In nitric acid matrices the resin is able to extract zirconium, while in hydrochloric acid matrices it is possible to extract iron and gallium. In all acid conditions tested gold is retained but can be removed from the column with a 10% thiourea rinse.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction

Traditional low-rank approximation is a powerful tool for compressing large data matrices that arise in simulations of partial differential equations (PDEs), but suffers from high computational cost and requires several passes over the PDE data. The compressed data may also lack interpretability thus making it difficult to identify feature patterns from the original data. Here, to address these issues, we present an online randomized algorithm to compute the interpolative decomposition (ID) of large-scale data matrices in situ. Compared to previous randomized IDs that used the QR decomposition to determine the column basis, we adopt a streaming ridge leverage score-based column subset selection algorithm that dynamically selects proper basis columns from the data and thus avoids an extra pass over the data to compute the coefficient matrix of the ID. In particular, we adopt a single-pass error estimator based on the non-adaptive Hutch++ algorithm to provide real-time error approximation for determining the best coefficients. As a result, our approach only needs a single pass over the original data and thus is suitable for large and high-dimensional matrices stored outside of core memory or generated in PDE simulations. A strategy to improve the accuracy of the reconstructed data gradient, when desired, within the ID framework is also presented. We provide numerical experiments on turbulent channel flow and ignition simulations, and on the NSTX Gas Puff Image dataset, comparing our algorithm with the offline ID algorithm to demonstrate its utility in real-world applications.

Column subset selection↗
DOE OSTI2020

Towards the scale-up production of cellulose nanocomposites using melt processing: A critical review on structure-processing-property relationships

Cellulose nanomaterials (CNMs) naturally exist in plant biomass. The success of extraction of CNMs opened up a new era of using plant biomass for innovative industrial applications. Because CNMs are abundant, renewable, biodegradable, transparent, light weight and low in cost, they are ideal materials for large volume applications such as packaging, automotive, building and infrastructure. In many potential application areas, CNM-enable products appear in a composite form, mostly polymer composites. Additionally, the industrial-scale manufacturing of CNM/thermoplastic composites remains as a set of unsolved problems for academia and industry. A prime challenge in applications is the nanoscale dispersion of CNMs in thermoplastic matrices during melt processing. Both bench-scale and pilot-scale studies have been conducted to solve the dispersion issue of CNMs. In this article, research related to the dispersion of CNMs in thermoplastic matrices during melt processing were critically reviewed. All research papers were classified into three groups: chemically-aided dispersion, physically-aided dispersion and mechanically-aided dispersion. Numerous factors affect the CNM dispersion and the mechanical performance of its nanocomposites. There are material-related factors, including CNM types and forms, polymer matrices, surface modification, coupling agents, etc. Furthermore, extrusion processing parameters also play a significant role, covering screw rotation speed, extrusion barrel temperature settings and screw design. In addition, the material-related factors interact with the processing-related factors. Understanding all factors and their interactions are important for moving CNM nanocomposites research a step further towards industrial-relevant production, which is the final ambitious goal of this manuscript.

42 ENGINEERING↗
DOE OSTI2021

A genome-scale phylogeny of the kingdom Fungi

Phylogenomic studies using genome-scale amounts of data have greatly improved understanding of the tree of life. Despite the diversity, ecological significance, and biomedical and industrial importance of fungi, evolutionary relationships among several major lineages remain poorly resolved, especially those near the base of the fungal phylogeny. To examine poorly resolved relationships and assess progress toward a genome-scale phylogeny of the fungal kingdom, we compiled a phylogenomic data matrix of 290 genes from the genomes of 1,644 species that includes representatives from most major fungal lineages. We also compiled 11 data matrices by subsampling genes or taxa from the full data matrix based on filtering criteria previously shown to improve phylogenomic inference. Analyses of these 12 data matrices using concatenation- and coalescent-based approaches yielded a robust phylogeny of the fungal kingdom, in which ~85% of internal branches were congruent across data matrices and approaches used. We found support for several historically poorly resolved relationships as well as evidence for polytomies likely stemming from episodes of ancient diversification. By examining the relative evolutionary divergence of taxonomic groups of equivalent rank, we found that fungal taxonomy is broadly aligned with both genome sequence divergence and divergence time but also identified lineages where current taxonomic circumscription does not reflect their levels of evolutionary divergence. Finally, our results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution and offer directions for future fungal phylogenetic and taxonomic studies.

59 BASIC BIOLOGICAL SCIENCES↗