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At least 361 records · Page 20

Model Refinement Using Eigensystem Assignment

IA novel approach for the refinement of finite-element-based analytical models of flexible structures is presented. The proposed approach models the possible refinements in the mass, damping, and stiffness matrices of the finite element model in the form of a constant gain feedback with acceleration, velocity, and displacement measurements, respectively. Once the free elements of the structural matrices have been defined, the problem of model refinement reduces to obtaining position, velocity, and acceleration gain matrices with appropriate sparsity that reassign a desired subset of the eigenvalues of the model, along with partial mode shapes, from their baseline values to those obtained from system identification test data. A sequential procedure is used to assign one conjugate pair of eigenvalues at each step using symmetric output feedback gain matrices, and the eigenvectors are partially assigned, while ensuring that the eigenvalues assigned in the previous steps are not disturbed. The procedure can also impose that gain matrices be dissipative to guarantee the stability of the refined model. A numerical example, involving finite element model refinement for a structural testbed at NASA Langley Research Center (Controls-Structures-Interaction Evolutionary model) is presented to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

Model Refinement Using Eigensystem Assignment

This paper presented a novel approach for the refinement of finite-element-based analytical models of flexible structures is presented. The proposed approach models the possible refinements in the mass, damping, and stiffness matrices of the finite element model in the form of a constant gain feedback with acceleration, velocity, and displacement measurements, respectively. Once, the free elements of the structural matrices have been defined, the problem of model refinement reduces to obtaining position, velocity, and acceleration gain matrices, which reassign a desired subset of the eigenvalues of the model, along with partial mode shapes, from their baseline values to those obtained from system identification test data. A sequential procedure is used to assign one self-conjugate pair of closed-loop eigenvalues at each step using symmetric output feedback gain matrices, and the closed-loop eigenvectors are partially assigned, while ensuring that the eigenvalues assigned in the previous steps are not disturbed. The procedure can also impose that gain matrices be dissipative in order to guarantee the stability of the refined model. A numerical example, involving finite element model refinement for a structural testbed at NASA Langley (CSI Evolutionary Model) is presented to demonstrate the feasibility of the proposed approach.

Maghami, Pieman G.↗

Graph Theory Roots of Spatial Operators for Kinematics and Dynamics

Spatial operators have been used to analyze the dynamics of robotic multibody systems and to develop novel computational dynamics algorithms. Mass matrix factorization, inversion, diagonalization, and linearization are among several new insights obtained using such operators. While initially developed for serial rigid body manipulators, the spatial operators and the related mathematical analysis have been shown to extend very broadly including to tree and closed topology systems, to systems with flexible joints, links, etc. This work uses concepts from graph theory to explore the mathematical foundations of spatial operators. The goal is to study and characterize the properties of the spatial operators at an abstract level so that they can be applied to a broader range of dynamics problems. The rich mathematical properties of the kinematics and dynamics of robotic multibody systems has been an area of strong research interest for several decades. These properties are important to understand the inherent physical behavior of systems, for stability and control analysis, for the development of computational algorithms, and for model development of faithful models. Recurring patterns in spatial operators leads one to ask the more abstract question about the properties and characteristics of spatial operators that make them so broadly applicable. The idea is to step back from the specific application systems, and understand more deeply the generic requirements and properties of spatial operators, so that the insights and techniques are readily available across different kinematics and dynamics problems. In this work, techniques from graph theory were used to explore the abstract basis for the spatial operators. The close relationship between the mathematical properties of adjacency matrices for graphs and those of spatial operators and their kernels were established. The connections hold across very basic requirements on the system topology, the nature of the component bodies, the indexing schemes, etc. The relationship of the underlying structure is intimately connected with efficient, recursive computational algorithms. The results provide the foundational groundwork for a much broader look at the key problems in kinematics and dynamics. The properties of general graphs and trees of nodes and edge were examined, as well as the properties of adjacency matrices that are used to describe graph connectivity. The nilpotency property of such matrices for directed trees was reviewed, and the adjacency matrices were generalized to the notion of block weighted adjacency matrices that support block matrix elements. This leads us to the development of the notion of Spatial Kernel Operator SKO kernels. These kernels provide the basis for the development of SKO resolvent operators.

Jain, Abhinandan↗

Solar system applications of Mie theory and of radiative transfer of polarized light

A theory of the multiple scattering of polarized light is discussed using the doubling method of van de Hulst. The concept of the Stokes parameters is derived and used to develop the form of the scattering phase matrix of a single particle. The diffuse reflection and transmission matrices of a single scattering plane parallel atmosphere are expressed as a function of the phase matrix, and the symmetry properties of these matrices are examined. Four matrices are required to describe scattering and transmission. The scattering matrix that results from the addition of two identical layers is derived. Using the doubling method, the scattering and transmission matrices of layers of arbitrary optical thickness can be derived. The doubling equations are then rewritten in terms of their Fourier components. Computation time is reduced since each Fourier component doubles independently. Computation time is also reduced through the use of symmetry properties.

Whitehill, L. P.↗

Elimination on sparse symmetric systems of a special structure.

Consideration of the problem of finding a permutation of rows and columns and an algorithm for solving ordered systems of linear algebraic equations with sparse matrices having a certain regular structure. Two approaches to the solution of this problem, in which the sparsity is used to some extent, are outlined. One of them is a very general approach where optimal (or nearly optimal) ordering is sought and the algorithm for solving the ordered system treats the matrix element by element to perform only necessary operations. The other approach involves the use of band matrices. After comparing these two approaches, a third approach is then suggested which involves the use of pipe matrices, and a means of ordering the rows and columns to obtain this type of matrix is presented. Examples of matrices reordered by the proposed procedure are cited.

Segethova, J.↗

A combined integrating and differentiating matrix formulation for boundary value problems on rectangular domains

Integrating and differentiating matrices allow the numerical integration and differential of functions whose values are known at points of a discrete grid. Previous derivations of these matrices were restricted to one dimensional grids or to rectangular grids with uniform spacing in at least one direction. Integrating and differentiating matrices were developed for grids with nonuniform spacing in both directions. The use of these matrices as operators to reformulate boundary value problems on rectangular domains as matrix problems for a finite dimensional solution vector is considered. The method requires nonuniform grids which include near boundary points. An eigenvalue problem for the transverse vibrations of a simply supported rectangular plate is solved to illustrate the method.

Lakin, W. D.↗

A combined integrating- and differentiating-matrix formulation for boundary-value problems on rectangular domains

Integrating and differentiating matrices allow the numerical integration and differential of functions whose values are known at points of a discrete grid. Previous derivations of these matrices were restricted to one dimensional grids or to rectangular grids with uniform spacing in at least one direction. Integrating and differentiating matrices were developed for grids with nonuniform spacing in both directions. The use of these matrices as operators to reformulate boundary value problems on rectangular domains as matrix problems for a finite dimensional solution vector is considered. The method requires nonuniform grids which include near boundary points. An eigenvalue problem for the transverse vibrations of a simply supported rectangular plate is solved to illustrate the method.

Lakin, W. D.↗

Compression Of Data In Imaging Radar Polarimetry

Algorithms developed to reduce number of radar polarimetric data processed to synthesize image of arbitrary combination of transmitting and receiving polarizations. Brings image-processing requirements within computing capabilities of typical users, without degrading images excessively. In scattering-matrix approach to reduction of image data, four adjacent picture elements combined into one by synthesizing new scattering matrix from scattering matrices of four elements. In phase-matrix approach, phase matrices generated from scattering matrices of four adjacent picture elements, and four phase matrices added to combine four picture elements into one.

Zebker, H. A.↗

Large-scale sparse singular value computations

Four numerical methods for computing the singular value decomposition (SVD) of large sparse matrices on a multiprocessor architecture are presented. Lanczos and subspace iteration-based methods for determining several of the largest singular triplets (singular values and corresponding left and right-singular vectors) for sparse matrices arising from two practical applications: information retrieval and seismic reflection tomography are emphasized. The target architectures for implementations are the CRAY-2S/4-128 and Alliant FX/80. The sparse SVD problem is well motivated by recent information-retrieval techniques in which dominant singular values and their corresponding singular vectors of large sparse term-document matrices are desired, and by nonlinear inverse problems from seismic tomography applications which require approximate pseudo-inverses of large sparse Jacobian matrices.

Berry, Michael W.↗

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.↗

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.↗

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.↗

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.↗

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↗

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.↗

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.↗

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.↗

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↗