: To improve the design of surface structures built on underground structures for safety and earthquake resistance, it is necessary to study the effects of the underground structures on wave propagation scattering and surface ground acceleration. To this end, various parameters must be studied, including input motion, structure embedment, and dimensions of different subway stations. The present study focuses on these parameters by employing a nonlinear cyclic model called ARCS soil's shear modulus reduction and damping ratio increase corresponding to those given by the user. The variations in spectral ratio, affected period range, peak ground acceleration, and peak relative lateral displacement versus relative distance under near-fault and far-fault earthquakes are presented. The results indicate that different amplification or de-amplification effects at different surface positions were produced at each frequency by appearing a significant influence on the dynamic behavior of ground surface, soil layers, and the surface structure when a subway station is present. A 1.3 times increase in the surface ground acceleration when subjected to far-fault earthquakes and a 1.6 times increase in the relative displacement indicated that study parameters have significant influence on the amplification ratio and scattering of wave.

Numerical methods

Our goal was to make it as easy as possible to solve a large class of boundary value problems (BVPs) for ordinary differential equations in the Matlab problem solving environment (PSE). We present here theoretical and software developments resulting in bvp4c, a capable BVP solver that is exceptionally easy to use.

A BVP solver based on residual control and the Maltab PSE

Thermally stimulated discharge of electrets

PREFACE ACKNOWLEDGMENTS INTRODUCTION Discretization Conditioning Error On Methods of Computation INTERPOLATION OF FUNCTIONS. QUADRATURES ALGEBRAIC INTERPOLATION Existence and Uniqueness of Interpolating Polynomial Classical Piecewise Polynomial Interpolation Smooth Piecewise Polynomial Interpolation (Splines) Interpolation of Functions of Two Variables TRIGONOMETRIC INTERPOLATION Interpolation of Periodic Functions Interpolation of Functions on an Interval. Relation between Algebraic and Trigonometric Interpolation COMPUTATION OF DEFINITE INTEGRALS. QUADRATURES Trapezoidal Rule, Simpson's Formula, and the Like Quadrature Formulae with No Saturation. Gaussian Quadratures Improper Integrals. Combination of Numerical and Analytical Methods Multiple Integrals SYSTEMS OF SCALAR EQUATIONS SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS: DIRECT METHODS Different Forms of Consistent Linear Systems Linear Spaces, Norms, and Operators Conditioning of Linear Systems Gaussian Elimination and Its Tri-Diagonal Version Minimization of Quadratic Functions and Its Relation to Linear Systems The Method of Conjugate Gradients Finite Fourier Series ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS Richardson Iterations and the Like Chebyshev Iterations and Conjugate Gradients Krylov Subspace Iterations Multigrid Iterations OVERDETERMINED LINEAR SYSTEMS. THE METHOD OF LEAST SQUARES Examples of Problems that Result in Overdetermined Systems Weak Solutions of Full Rank Systems. QR Factorization Rank Deficient Systems. Singular Value Decomposition NUMERICAL SOLUTION OF NONLINEAR EQUATIONS AND SYSTEMS Commonly Used Methods of Rootfinding Fixed Point Iterations Newton's Method THE METHOD OF FINITE DIFFERENCES FOR THE NUMERICAL SOLUTION OF DIFFERENTIAL EQUATIONS NUMERCAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS Examples of Finite-Difference Schemes. Convergence Approximation of Continuous Problem by a Difference Scheme. Consistency Stability of Finite-Difference Schemes The Runge-Kutta Methods Solution of Boundary Value Problems Saturation of Finite-Difference Methods The Notion of Spectral Methods FINITE-DIFFERENCE SCHEMES FOR PARTIAL DIFFERENTIAL EQUATIONS Key Definitions and Illustrating Examples Construction of Consistent Difference Schemes Spectral Stability Criterion for Finite-Difference Cauchy Problems Stability for Problems with Variable Coefficients Stability for Initial Boundary Value Problems Explicit and Implicit Schemes for the Heat Equation DISCONTINUOUS SOLUTIONS AND METHODS OF THEIR COMPUTATION Differential Form of an Integral Conservation Law Construction of Difference Schemes DISCRETE METHODS FOR ELLIPTIC PROBLEMS A Simple Finite-Difference Scheme. The Maximum Principle The Notion of Finite Elements. Ritz and Galerkin Approximations THE METHODS OF BOUNDARY EQUATIONS FOR THE NUMERICAL SOLUTION OF BOUNDARY VALUE PROBLEMS BOUNDARY INTEGRAL EQUATIONS AND THE METHOD OF BOUNDARY ELEMENTS Reduction of Boundary Value Problems to Integral Equations Discretization of Integral Equations and Boundary Elements The Range of Applicability for Boundary Elements BOUNDARY EQUATIONS WITH PROJECTIONS AND THE METHOD OF DIFFERENCE POTENTIALS Formulation of Model Problems Difference Potentials Solution of Model Problems LIST OF FIGURES REFERENCED BOOKS REFERENCED JOURNAL ARTICLES INDEX

/pdf/a-theoretical-introduction-to-numerical-analysis-4qujywvl7l.pdf

A Theoretical Introduction to Numerical Analysis

In this paper we formalize the observation that filtering and interpolation induce complementary, or "dual," decompositions of the space of positive real rational functions of degree less than or equal to n. From this basic result about the geometry of the space of positive real functions, we are able to deduce two complementary sets of conclusions about positive rational extensions of a given partial covariance sequence. On the one hand, by viewing a certain fast filtering algorithm as a nonlinear dynamical system defined on this space, we are able to develop estimates on the asymptotic behavior of the Schur parameters (1918) of positive rational extensions. On the other hand we are also able to provide a characterization of all positive rational extensions of a given partial covariance sequence. Indeed, motivated by its application to signal processing, speech processing, and stochastic realization theory, this characterization is in terms of a complete parameterization using familiar objects from systems theory and proves a conjecture made by Georgiou (1983, 1987). Our basic result, however, also enables us to analyze the robustness of this parameterization with respect to variations in the problem data. The methodology employed is a combination of complex analysis, geometry, linear systems, and nonlinear dynamics. >

/pdf/a-complete-parameterization-of-all-positive-rational-2q8zvxbn4u.pdf

A complete parameterization of all positive rational extensions of a covariance sequence

Theoretical Numerical Analysis.

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Theoretical Numerical Analysis.