Transfer matrices and stiffness matrices for uniform beams
Transfer matrices and stiffness matrices for uniform beams in steady state vibration
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Transfer matrices and stiffness matrices for uniform beams in steady state vibration
Numerical technique increases the efficiencies of the numerical methods involving Toeplitz matrices by reducing the number of multiplications required by an N-order Toeplitz matrix from N-cubed to N-squared multiplications. Some efficient algorithms are given.
Toeplitz matrices occur in many mathematical, as well as, scientific and engineering investigations. This paper considers the spectra of banded Toeplitz and quasi-Toeplitz matrices with emphasis on non-normal matrices of arbitrarily large order and relatively small bandwidth. These are the type of matrices that appear in the investigation of stability and convergence of difference approximations to partial differential equations. Quasi-Toeplitz matrices are the result of non-Dirichlet boundary conditions for the difference approximations. The eigenvalue problem for a banded Toeplitz or quasi-Toeplitz matrix of large order is, in general, analytically intractable and (for non-normal matrices) numerically unreliable. An asymptotic (matrix order approaches infinity) approach partitions the eigenvalue analysis of a quasi-Toeplitz matrix into two parts, namely the analysis for the boundary condition independent spectrum and the analysis for the boundary condition dependent spectrum. The boundary condition independent spectrum is the same as the pure Toeplitz matrix spectrum. Algorithms for computing both parts of the spectrum are presented. Examples are used to demonstrate the utility of the algorithms, to present some interesting spectra, and to point out some of the numerical difficulties encountered when conventional matrix eigenvalue routines are employed for non-normal matrices of large order. The analysis for the Toeplitz spectrum also leads to a diagonal similarity transformation that improves conventional numerical eigenvalue computations. Finally, the algorithm for the asymptotic spectrum is extended to the Toeplitz generalized eigenvalue problem which occurs, for example, in the stability of Pade type difference approximations to differential equations.
The present research effort was undertaken to develop a new generation of SiC fiber-reinforced engineered ceramic matrix composites (E-CMCs). In contrast to traditional CMCs with a brittle SiC matrix, an E-CMC is designed to consist of a matrix engineered to possess sufficient high temperature plasticity to minimize crack propagation, relatively high fracture toughness, and self-healing capabilities to prevent oxygen ingress to the BN-coated fibers through surface-connected cracks. The present paper discusses the bend strength, isothermal oxidation, microstructures and self-healing properties of several silicide-behaved engineered matrices. Based on the oxidation tests, where it was observed that some of the matrices exhibited either catastrophic oxidation ("pesting") or spalling of the oxide scale, two engineered matrices, CrSi2/SiC/Si3N4 and CrMoSi/SiC/Si3N4, were down-selected for further investigation. Four-point bend tests were conducted on these two engineered matrices between room temperature and 1698 degrees Kelvin. Although these matrices were brittle at low temperatures, it was observed that the bend strengths and bend ductility increased at high temperatures as the silicide particles became more ductile, which was qualitatively consistent with the theoretically expected behavior that crack blunting at these particles should increase the matrix strength. Additional studies were conducted to study the effects of different additives on the self-healing properties of the engineered matrices, which helped to identify the most effective additives.
The theory of polynomial matrices plays a key role in the design and analysis of multi-input multi-output control and communications systems using frequency domain methods. Examples include coprime factorizations of transfer functions, cannonical realizations from matrix fraction descriptions, and the transfer function design of feedback compensators. Typically, such problems abstract in a natural way to the need to solve systems of Diophantine equations or systems of linear equations over polynomials. These and other problems involving polynomial matrices can in turn be reduced to polynomial matrix triangularization procedures, a result which is not surprising given the importance of matrix triangularization techniques in numerical linear algebra. Matrices with entries from a field and Gaussian elimination play a fundamental role in understanding the triangularization process. In the case of polynomial matrices, matrices with entries from a ring for which Gaussian elimination is not defined and triangularization is accomplished by what is quite properly called Euclidean elimination. Unfortunately, the numerical stability and sensitivity issues which accompany floating point approaches to Euclidean elimination are not very well understood. New algorithms are presented which circumvent entirely such numerical issues through the use of exact, symbolic methods in computer algebra. The use of such error-free algorithms guarantees that the results are accurate to within the precision of the model data--the best that can be hoped for. Care must be taken in the design of such algorithms due to the phenomenon of intermediate expressions swell.
The computation of divergence is studied. Covariance matrices to be analyzed admit a common diagonalization, or even triangulation. Sufficient conditions are given for such phenomena to take place, the arguments cover both real and complex matrices, and are not restricted to Hermotian or other special forms. Specifically, it is shown to be sufficient that the matrices in question commute in order to admit a common triangulation. Several results hold in the case that the matrices in question form a closed and bounded set, rather than only in the finite case.
Techniques are presented for determining the elements of the A, B, C, and D state variable matrices for systems simulated on an EAI Pacer 100 hybrid computer. An automated procedure systematically generates disturbance data necessary to linearize the simulation model and stores these data on a floppy disk. A separate digital program verifies this data, calculates the elements of the system matrices, and prints these matrices appropriately labeled. The partial derivatives forming the elements of the state variable matrices are approximated by finite difference calculations.
The paper defines higher dimensional Hadamard matrices and enumerates on some of the simplest three-, four-, and five-dimensional cases and procedures for generating them. Special emphasis is given to proper matrices that have a dimensional hierarchy of orthogonalities. It is determined that this property lends itself primarily to the application of higher dimensional Hadamard matrices to error-correcting codes. A list of derived statements for n-dimensional Hadamard matrices are given, as well as a definition of Hadamard matrix families, such as minimal, Petrie polygon, antipodal (n-2)-dimensional sections, and double proximity shells.
A method for computing exponential matrices, which often arise naturally in the solution of systems of linear differential equations, is developed. An exponential matrix is generated as a linear combination of a finite number (equal to the matrix order) of matrices, the coefficients of which are scalar infinite sums. The method can be generalized to apply to any formal power series of matrices. Attention is focused upon the exponential function, and the matrix exponent is assumed tri-diagonal in form. In such cases, the terms in the coefficient infinite sums can be extracted, as recursion relations, from the characteristic polynomial of the matrix exponent. Two numerical examples are presented in some detail: (1) the three dimensional infinitesimal rotation rate matrix, which is skew symmetric, and (2) an N-dimensional tri-diagonal and symmetric finite difference matrix which arises in the numerical solution of the heat conduction partial differential equation. In the second example, the known eigenvalues and eigenvectors of the finite difference matrix permit an analytical solution for the exponential matrix, through the theory of diagonalization and similarity transformations, which is used for independent verification. The convergence properties of the scalar infinite summations are investigated for finite difference matrices of various orders up to ten, and it is found that the number of terms required for convergence increases slowly with the order of the matrix.
Results are presented of an experimental program to determine the functional dependence of the microwave reflectivity of nonvegetated soil surfaces upon volumetric soil moisture and matric potential. A combination evaporation-drainage field experiment was conducted on a bare Captina slit loam with reflectivity, soil moisture content, and matric potential monitored for extended time periods. Results show that for a restricted pressure range (approximately -0.05 to -0.75 bar) there is excellent linear correlation between the log of bistatic reflectivity and both volumetric moisture content and matric potential. Layering effects due to steep moisture content (and matric potential) gradients in the profile are demonstrated to have two distinct and significant effects on the reflectivity response. At near saturation of rough surfaces a very thin dry surface layer appears to modify the effective roughness. This leads to a saturation of reflectivity at high moisture contents. As the surface proceeds to dry further, deeper layers produce coherent interference patterns in the reflectivity response, particularly at the higher frequencies.
Complex-valued symmetric matrices are studied. A simple expression for the spectral norm of such matrices is obtained, by utilizing a unitarily congruent invariant form. A sharp criterion is provided for identifying those symmetric matrices whose spectral norm is not exceeding one: such strongly stable matrices are usually sought in connection with convergent difference approximations to partial differential equations. As an example, the derived criterion is applied to conclude the strong stability of a Lax-Wendroff scheme.
Differentiating matrices allow the numerical differentiation of functions defined at points of a discrete grid. Previous derivations of these matrices have been restricted to grids with uniformly spaced points, and the resulting derivative approximations have lacked precision, especially at endpoints. The present work derives differentiating matrices on grids with arbitrarily spaced points. It is shown that high accuracy can be achieved through use of differentiating matrices on non-uniform grids through the expedient of including 'near boundary' points. Use of the differentiating matrix as an operator in the solution of problems involving ordinary differential equations is also considered.
Continuous silicon carbide (SiC) fiber was added to three types of silicon nitride (Si3N4) matrices. Efforts were aimed at producing a dense Si3N4 matrix from reaction-bonded silicon nitride (RBSN) by hot-isostatic-pressing (HIP) and pressureless sintering, and from Si3N4 powder by hot-pressing. The sintering additives utilized were chosen to allow for densification, while not causing severe degradation of the fiber. The ceramic microstructures were evaluated using scanning optical microscopy. Vickers indentation was used to determine the microhardness and fracture toughness values of the matrices. The RBSN matrices in this study did not reach more than 80 percent of theoretical density after sintering at various temperatures, pressures, and additive levels. Hot-pressing Si3N4 powder produced the highest density matrices; hardness and toughness values were within an order of magnitude of the best literature values. The best sintering aid composition chosen included Y2O3, SiO2, and Al2O3 or AlN. Photomicrographs demonstrate a significant reduction of fiber attack by this additive composition.
This article looks at the effect of different resin matrices on thermal and mechanical properties of graphite composites, and relates the thermal and flammability properties to the anaerobic char yield of the resins. The processing parameters of graphite composites utilizing graphite fabric and epoxy or other advanced resins as matrices are presented. Thermoset resin matrices studied were: aminecured polyfunctional glycidyl aminetype epoxy (baseline), phenolicnovolac resin based on condensation of dihydroxymethyl-xylene and phenol cured with hexamine, two types of polydismaleimide resins, phenolic resin, and benzyl resin. The thermoplastic matrices studied were polyethersulfone and polyphenylenesulfone. Properties evaluated in the study included anaerobic char yield, limiting oxygen index, smoke evolution, moisture absorption, and mechanical properties at elevated temperatures including tensile, compressive, and short-beam shear strengths. Generally, it was determined that graphite composites with the highest char yield exhibited optimum fire-resistant properties.
Utilizing element properties, structural stiffness and mass matrices are generated for as many as twenty harmonics and stored on magnetic tape. Matrices generated constitute input data to be used by other stiffness of revolution programs. Variety of boundary and loading conditions can be employed without having to create new mass and stiffness matrices for each case.
The sampled-data optimal linear regulator problem provides a means whereby a control designer can use an understanding of continuous optimal regulator design to produce a digital state variable feedback control law which satisfies continuous system performance specifications. A basic difficulty in applying the sampled-data regulator theory is the requirement that certain digital performance index weighting matrices, expressed as complicated functions of system matrices, be computed. Infinite series representations are presented for the weighting matrices of the time-invariant version of the optimal linear sampled-data regulator problem. Error bounds are given for estimating the effect of truncating the series expressions after a finite number of terms, and a method is described for their computer implementation. A numerical example is given to illustrate the results.
A method is presented for the determination of the representation matrices of the spin permutation group (symmetric group), a detailed knowledge of these matrices being required in the study of the electronic structure of atoms and molecules. The method is characterized by the use of two different coupling schemes. Unlike the Yamanouchi spin algebraic scheme, the method is not recursive. The matrices for the fundamental transpositions can be written down directly in one of the two bases. The method results in a computationally significant reduction in the number of matrix elements that have to be stored when compared with, say, the standard Young tableaux group theoretical approach.