1st Edition
Engineering Modelling and Analysis
Introducing engineering students to numerical analysis and computing, this book covers a range of topics suitable for the first three years of a four year undergraduate engineering degree. The teaching of computing to engineers is hampered by the lack of suitable problems for the students to tackle, so much effort has gone into making the problems in this book realistic and relevant, while at the same time solvable for undergraduates.
Taking a balanced approach to teaching computing and computer methods at the same time, this book satisfies the need to be able to use computers (using both formal languages such as Fortran and other applications such as Matlab and Microsoft Excel), and the need to be able to solve realistic engineering problems.
1 Introduction to Engineering Modelling and Analysis
2 Introduction to Computing Tools – Fortran, Pascal, Basic, and C
3 Introduction to Computing Tools – Spreadsheets
4 Introduction to Computing Tools – Matlab
5 Fortran 90/95 – Basic Concepts, Input and Output
6 Fortran 90/95 – Control Structures and Data Storage
7 Fortran 90/95 – Common Tasks
8 Roots of Equations – Introduction
9 Roots of Equations – Bracket Methods
10 Roots of Equations – Open Methods
11 Numerical Integration – Trapezoidal Rule
12 Numerical Integration – Simpson’s Rules
13 Numerical Interpolation – Newton’s Method
14 Numerical Interpolation – Polynomial Methods
15 Numerical Interpolation – Splines
16 Systems of Linear Equations – Introduction
17 Systems of Linear Equations – Gauss-Jordan and Gauss-Seidel Methods
18 Systems of Linear Equations – Thomas Algorithm
19 Numerical Solution of Ordinary Differential Equations – Introduction
20 Numerical Solution of Ordinary Differential Equations – Euler and Runge-Kutta Methods
21 Finite Difference Modelling – Introduction
22 Finite Difference Modelling – LaPlace’s Equation Solutions
23 Finite Difference Modelling – Solution of Pure Convection
24 Finite Difference Modelling – Solution of Pure Diffusion
25 Finite Difference Modelling – Solution of Transport Equation
26 Finite Difference Modelling – Alternate Schemes
27 Probability Distributions – Introduction
28 Probability Distributions – The Normal and Lognormal Distributions
29 Probability Distributions – The Binomial Distribution and Return Periods
30 Probability Distributions – The Poisson Distribution
31 Probability Distributions – Testing Distributions using Probability Paper
32 Probability Distributions – Testing Distributions using Chi2 Test
33 Random Numbers – Theory and Generation
34 Monte Carlo – Introduction
35 Monte Carlo – Applications
36 Resonance
37 Spectral Analysis – Basic Concepts
38 Spectral Analysis – Discrete Fourier Transform
39 Spectral Analysis – Application of the Fast Fourier Transform
40 Spectral Analysis – Practical Aspects of Data Collection and Analysis
41 Linear Regression and Correlation
42 Parameter Estimation
43 Assorted Topics – The Error Function
44 Assorted Topics – Taylor Series
45 Assorted Topics – Complex Representation of Periodic Functions
46 Solutions to Selected Problems
Biography
David Walker, Michael Leonard and Martin Lambert are in the School of Civil, Environmental and Mining Engineering, and Andrew Metcalfe is in the School of Mathematical Sciences, all at the University of Adelaide, Australia. They are all active in teaching and research and the content of the book reflects a strong belief that the one should complement the other.