This
note introduces elementary programming concepts including variable types, data
structures, and flow control. After an introduction to linear algebra and
probability, it covers numerical methods relevant to mechanical engineering,
including approximation, integration, solution of linear and nonlinear equations, ordinary
differential equations, and deterministic and probabilistic approaches.
Author(s): Prof.
Anthony T. Patera, Prof. Daniel Frey and Prof. Nicholas Hadjiconstantinou
This
note introduces elementary programming concepts including variable types, data
structures, and flow control. After an introduction to linear algebra and
probability, it covers numerical methods relevant to mechanical engineering,
including approximation, integration, solution of linear and nonlinear equations, ordinary
differential equations, and deterministic and probabilistic approaches.
Author(s): Prof.
Anthony T. Patera, Prof. Daniel Frey and Prof. Nicholas Hadjiconstantinou
The
resource described here is an overview of numerical methods important in the
study of computational science and engineering. The text starts off with
Computing with Matrices and Vectors, foundational elements in many algorithms.
The note moves forward and explains Direct Methods for Linear Systems of
Equations and Direct Methods for Linear Least Squares Problems, important
problem-solving aspects in linear algebra. The Filtering Algorithms for data
processing are reviewed, while Data Interpolation and Data Fitting in 1D discuss
ways of approximating onedimensional data. Approximation of Functions in 1D and
Numerical Quadrature introduce the techniques on function approximation and
integration. It also discusses Iterative Methods for Non-Linear Systems of
Equations and Eigenvalues-a critical topic needed for solving complex systems.
It finally includes Numerical Integration and Structure Preserving Integration,
fundamental to perform numerical calculations with appropriate accuracy in
scientific computing.
It gives an explanation
of all the different numerical methods of scientific computing. It starts with
the basics, which is Root Finding and Orthogonal Functions, solving equations
and analyzing functions. Finite Differences and Divided Differences included for
the needs in the process of numerical differentiation and interpolation.
Interpolation and Curve Fitting are given to outline estimation and modeling. It
also includes Z-Transforms and Summation Formulas for signal processing and
numerical summation. Quadrature Formulas and Ordinary Differential Equations are
explained for integration and the solution of differential equations. Partial
Differential Equations, Integral Equations, and Stability and Error Analysis
form the advanced topics for numerical methods coverage. Further, Monte Carlo
Techniques, Message Passing Interface, and Simulation Modeling are included to
point out methods for probabilistic simulations and parallel computing.
This
lecture series provides comprehensive foundational knowledge in the field of
numerical computational analysis. Numerical Linear Algebra covers basic matrix
operations and solutions of linear systems. The book further goes into the
Solution of Nonlinear Equations that shows methods for solving equations which
are not linear in form. Finally, it discusses Approximation Theory, showing how
functions and data may be approximated. The lectures also cover Numerical
Solution of ODEs and PDEs, giving ways to solve these two basic kinds of
equations. This resource is intended for students and professionals looking to
gain a solid understanding of basic and applied numerical analysis techniques.