Engineering Modelling and Analysis / Edition 1

Engineering Modelling and Analysis / Edition 1

ISBN-10:
0415469627
ISBN-13:
9780415469623
Pub. Date:
10/14/2008
Publisher:
Taylor & Francis
ISBN-10:
0415469627
ISBN-13:
9780415469623
Pub. Date:
10/14/2008
Publisher:
Taylor & Francis
Engineering Modelling and Analysis / Edition 1

Engineering Modelling and Analysis / Edition 1

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Overview

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.


Product Details

ISBN-13: 9780415469623
Publisher: Taylor & Francis
Publication date: 10/14/2008
Edition description: New Edition
Pages: 440
Product dimensions: 6.10(w) x 9.10(h) x 1.00(d)

About the Author

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.

Table of Contents

Part 1: Introduction Part 2: Roots of Equations Part 3: Numerical Integration Part 4: Numerical Interpolation Part 5: Systems of Equations Part 6: Ordinary Differential Equations Part 7: Finite Difference Modelling Part 8: Probability and Statistics Part 9: Probability Distributions Part 10: Monte Carlo Method Part 11: Stochastic Modelling Part 12: Optimisation Part 13: Linear Systems and Resonance Part 14: Spectral Analysis
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