Engineering modelling and analysis:
Gespeichert in:
Format: | Buch |
---|---|
Sprache: | English |
Veröffentlicht: |
London [u.a.]
Taylor & Francis
2009
|
Ausgabe: | 1. publ. |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Includes bibliographical references and index |
Beschreibung: | XVI, 424 S. |
ISBN: | 9780415469616 9780415469623 |
Internformat
MARC
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010 | |a 2008022437 | ||
020 | |a 9780415469616 |c hardback : alk. paper |9 978-0-415-46961-6 | ||
020 | |a 9780415469623 |c pbk. : alk. paper |9 978-0-415-46962-3 | ||
035 | |a (OCoLC)213446275 | ||
035 | |a (DE-599)BVBBV035313030 | ||
040 | |a DE-604 |b ger |e aacr | ||
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245 | 1 | 0 | |a Engineering modelling and analysis |c David Walker ... |
250 | |a 1. publ. | ||
264 | 1 | |a London [u.a.] |b Taylor & Francis |c 2009 | |
300 | |a XVI, 424 S. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
500 | |a Includes bibliographical references and index | ||
650 | 4 | |a Ingenieurwissenschaften | |
650 | 4 | |a Mathematisches Modell | |
650 | 4 | |a Engineering models | |
650 | 4 | |a Engineering |x Mathematical models | |
700 | 1 | |a Walker, David |e Sonstige |4 oth | |
776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-0-203-89454-5 |
856 | 4 | 2 | |m Digitalisierung UB Bayreuth |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017117741&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
999 | |a oai:aleph.bib-bvb.de:BVB01-017117741 |
Datensatz im Suchindex
_version_ | 1804138618112966656 |
---|---|
adam_text | Contents
Preface
xv
1
Introduction (Engineering
Modelling
and Analysis)
1
1.1
Introduction
1
1.2
Engineering models
5
1.3
Engineering modelling
6
1.4
Physical models
7
1.5
Modern engineering computing
8
1.6
A word of warning
9
Problems
10
2
Introduction (Accuracy, Speed and Algorithms)
11
2.1
Introduction
11
2.2
A brief history of computers and computing
12
2.3
Topics and their focus
14
2.4
Topics and their connections
15
2.5
Developing computing skills
17
2.6
Numerical recipes
18
Problems
18
3
Roots of Equations (Introduction)
19
3.1
Introduction
19
3.2
What are roots?
20
3.3
Engineering problems requiring root finding
21
3.4
Worked example
23
3.5
Goal Seek in Excel
24
Problems
25
4
Roots of Equations (Bracket Methods)
27
4.1
Introduction
27
4.2
Bracket methods in general
27
4.3
Bisection method
28
4.4
Method of false position
(regula
falsi)
30
4.5
Convergence criteria
32
4.6
Application of bisection method in Excel
32
4.7
Determining start values for bracket methods
33
Problems
35
ví
Contents
5
Roots
of Equations (Open Methods)
5.1
Introduction
5.2
Simple one-point iteration
5.3
Newton-Raphson method
5.4
Secant method
5.5
Multiple roots
5.6
Other problems and general considerations
5.7
Case study: pollutant transport in a river
5.8
Case study: wet detention treatment basins
Problems
37
37
37
38
39
40
41
42
42
43
Numerical Integration (Trapezoidal Rule)
45
6.1
Introduction
45
6.2
Trapezoidal rule
48
6.3
Worked example: cumulative normal probability
49
6.4
Sources of error with the trapezoidal rule
50
Problems
51
Numerical Integration (Simpson s Rule)
53
7.1
Introduction
53
7.2
Simpson s
3/8
rule
55
7.3
Ал
efficient Simpson s rale
55
7.4
Integration in
Matlab
56
Problems
58
Numerical Interpolation (Newton s Method)
61
8.1
Introduction
61
8.2
Polynomial equations
62
8.3
Newton s linear interpolation
63
8.4
Newton s quadratic interpolation
64
8.5
General form of Newton s polynomials
65
8.6
Lagrange s interpolating polynomials
67
8.7
Polynomial interpolation in practice
68
8.8
Polynomial interpolation in Excel
69
8.9
Polynomial interpolation in
Matlab
70
Problems
70
Numerical Interpolation (Cubic Splines and Other Methods)
73
9.1
Introduction
73
9.2
Cubic splines
73
9.3
Trigonometric interpolation
77
9.4
Other methods of interpolation
79
9.5
Extrapolation
80
Problems
80
Contents
vii
10 Systems
of
Linear
Equations (Introduction)
83
10.1
Introduction
83
10.2
The basic equations
84
10.3
Graphical methods
85
10.4
Cramer s rule
85
10.5
Elimination of unknowns
86
10.6
Gauss elimination
87
10.7
Problems and their solution for Gauss elimination
89
Problems
90
11
Systems of Equations (Gauss-Seidel Method)
93
11.1
Gauss-Seidel method
93
11.2
Convergence
96
11.3
Relaxation
97
Problems
97
12
Systems of Equations
(LU
Decomposition and Thomas
99
Algorithm)
12.1
LU
decomposition
99
12.2
Crout decomposition
100
12.3
Banded matrices and the Thomas algorithm
103
12.4
Example of a banded matrix
104
Problems
105
13
Ordinary Differential Equations (Euler s Method)
107
13.1
Introduction
107
13.2
Ordinary differential equations in engineering
108
13.3
Pre-computer methods of solving ODEs
111
13.4
One-step methods
112
13.5
Euler s method
112
13.6
Chaotic behaviour in solutions
114
13.7
Modified
Euler
method
115
Problems
115
14
Ordinary Differential Equations (Heun and Runge-Kutta
117
Methods)
14.1
Introduction
117
14.2
Heun s method
117
14.3
Runge-Kutta methods
119
14.4
Computational effort
120
14.5
Adaptive step methods
120
14.6
Integration using ODE techniques
122
Problems
122
viii Contents
15
Finite
Difference Modelling (Introduction)
123
15.1
Introduction
123
15.2
First-order finite difference approximations
125
15.3
Higher-order finite difference approximations
126
15.4
Second derivative approximations
128
15.5
Application of finite difference method
128
15.6
Selecting the space step
129
15.7
Selecting the time step
129
Problems
130
16
Finite Difference Modelling (Laplace s Hot Plate)
133
16.1
Introduction
133
16.2
Elliptic finite difference techniques
134
16.3
Worked example
136
16.4
Coding Liebmann s method in Fortran
138
Problems
139
17
Finite Difference Modelling (Solution of Pure Convection
141
Equation)
17.1
Introduction
141
17.2
Selecting the space step size
141
17.3
Deriving the finite difference approximation
142
17.4
Worked example in Excel
143
17.5
Stability, accuracy and other issues
145
Problems
148
18
Finite Difference Modelling (Solution of Pure Diffusion
149
Equation)
18.1
Introduction
149
18.2
Selecting the space step size
149
18.3
Deriving the finite difference approximation
150
18.4
Boundary conditions
152
18.5
Coding the heat equation in Fortran
154
18.6
Heated bar simulation
154
Problems
156
19
Finite Difference Modelling (Solution of Full Transport
159
Equation)
19.1
Introduction
159
19.2
Deriving the finite difference approximation
159
19.3
Verification of finite difference approximation
160
19.4
Case study: thermal river pollution
162
Problems
162
Contents ix
20
Finite
Difference Modelling (Alternate Schemes)
163
20.1
Introduction
163
20.2
Advanced explicit methods
163
20.3
Implicit schemes
164
20.4
Solving implicit methods
164
20.5
Accuracy and the finite difference
166
20.6
Lewis Fry Richardson
168
Problems
168
21
Probability and Statistics (Descriptive Statistics)
169
21.1
Introduction
169
21.2
Data exploration
169
21.3
Summary statistics
173
Problems
176
22
Probability and Statistics (Population and Sample)
177
22.1
Introduction
177
22.2
Probability
177
22.3
Estimation
180
22.4
Bayes
rule and total probability
181
Problems
183
23
Probability and Statistics (Linear Combination of Random
185
Variables)
23.1
Introduction
185
23.2
Mathematical model
185
23.3
Distribution of the sample mean
187
Problems
188
24
Probability and Statistics (Correlation and Regression)
189
24.1
Introduction
189
24.2
Correlation
189
24.3
Correlation and time series
192
24.4
Testing a random number generator
193
24.5
Simple linear regression
195
24.6
Regression towards the mean
198
Problems
199
25
Probability and Statistics (Multiple Regression)
201
25.1
Introduction
201
25.2
Multiple regression model
201
25.3
Worked example
203
25.4
Regression in Excel
205
25.5
Fitting quadratic surfaces
208
25.6
Indicator variables
210
Problems
212
χ
Contents
26
27
28
29
ЗО
Probability and Statistics (Non-Linear Regression)
215
26.1
Introduction
215
26.2
Non-linear regression example
215
Problems
217
Probability Distributions (Introduction)
219
27.1
Introduction
219
27.2
Discrete variables
219
27.3
Continuous variables
220
27.4
Probability mass and probability density functions
222
27.5
Cumulative probability distributions
224
27.6
Common distributions in engineering
224
27.7
Uniform distribution
225
Problems
226
Probability Distributions (Bernoulli, Binomial, Geometric)
227
28.1
Introduction
227
28.2
Properties of the Bernoulli distribution
228
28.3
Geometric distribution
230
28.4
Return period
230
28.5
Negative binomial distribution
231
Problems
231
Probability Distributions
(Poisson,
Exponential, Gamma)
233
29.1
Introduction
233
29.2
Poisson
process and
Poisson
distribution
234
29.3
Prussian army horses
235
29.4
Return periods and probability
236
29.5
Exponential distribution
237
29.6
Gamma distribution
237
29.7
Worked example
238
Problems
239
Probability Distributions (Normal and Log-Normal)
241
30.1
Introduction
241
30.2
Normal distribution
242
30.3
Excel example
244
30.4
Application of normal distribution to diffusion
244
30.5
Log-normal distribution
245
30.6
A word of warning
246
Problems
247
Contents xi
31
Probability Distributions (Extreme Values)
249
31.1
Introduction
249
31.2
Genesis of an extreme value distribution
249
31.3
The Gumbel distribution
250
31.4
Modelling cyclones
251
31.5
Pareto distribution
252
31.6
Generalised Pareto distribution
254
Problems
256
32
Probability Distributions (Chi-Square and Rayleigh)
257
32.1
Introduction
257
32.2
Chi-square distribution
257
32.3
Rayleigh distribution
258
Problems
258
33
Probability Distributions (Multivariate)
259
33.1
Introduction
259
33.2
Discrete bivariate distributions
259
33.3
Bivariate normal distribution
260
33.4
Multivariate normal distribution
263
33.5
Continuous multivariate distributions
266
Problems
268
34
Monte Carlo Method (Introduction)
269
34.1
Introduction
269
34.2
Illustrative example of Monte Carlo simulation
270
34.3
Basic procedure for Monte Carlo simulation
272
Problems
275
35
Monte Carlo Method (Generation of Random Numbers)
277
35.1
Introduction
277
35.2
Distributions of random numbers
278
35.3
Uniform distribution
279
35.4
Exponential distribution
280
35.5
Normal distribution
281
35.6
Log-Normal distribution
281
35.7
Central limit theorem
282
35.8
Solution of pollutant dispersion
283
Problems
285
36
Monte Carlo Method (Acceptance/Rejection)
287
36.1
Introduction
287
36.2
The Metropolis algorithm
288
Problems
290
xii Contents
37 Monte
Carlo
Method
(Metropolis Applications)
37.1
Introduction
37.2
The Ising model
37.3
The Strauss model
37.4
Parameter
uncertainty
37.5
Conclusion
Problems
291
291
291
294
296
299
299
38
Stochastic Modelling (Goodness of Fit and
Model
Calibration)
301
38.1
Introduction
301
38.2
The method of moments
301
38.3
Probability plots
302
38.4
Statistical tests
306
38.5
Least squares
306
Problems
308
39
Stochastic Modelling (Likelihood and Uncertainty)
309
39.1
Introduction
309
39.2
Bayes
rule
309
39.3
Maximum likelihood
311
39.4
Uncertainty
314
Problems
317
40
Stochastic Modelling (Markov Chains)
319
40.1
Introduction
319
40.2
Regular Markov chains
319
40.3
Absorbing Markov chains
322
40.4
Regular Markov processes
323
Problems
325
41
Stochastic Modelling (Time Series)
327
41.1
Introduction
327
41.2
Environmental time series applications
328
41.3
Concepts of time series
330
41.4
Modelling trends and seasonal effects
331
41.5
Autoregressive
processes
334
41.6
Simulation
335
41.7
Forecasting
336
41.8
Summary
337
Problems
338
42
Optimisation (Local Optimisation)
339
42.1
Introduction
339
42.2
The Simplex method
340
Problems
344
Contents xiii
43
Optimisation
(Global
Optimisation)
345
43.1
Introduction
345
43.2
Combinatorial
optimisation
345
43.3
Simulated annealing
348
Problems
352
44
Linear Systems and Resonance
353
44.1
Introduction
353
44.2
Mathematical description of linear systems
356
44.3
Resonance in the coastal environment
359
44.4
Resonance in structural engineering
360
Problems
361
45
Spectral Analysis (Introduction)
363
45.1
Introduction
363
45.2
Frequency and time domains
364
45.3
History
-
Fourier
365
45.4
The Fourier transform
366
45.5
Case study
#1:
earthquake analysis
368
45.6
Case study
#2:
pink noise
368
45.7
Case study
#3:
red noise
369
45.8
Worked example
370
Problems
371
46
Spectral Analysis (Discrete Fourier Transform)
373
46.1
Introduction
373
46.2
The Fourier transform of discrete data
374
46.3
Worked example
375
46.4
The fast Fourier transform in
Matlab
377
46.5
The fast Fourier transform and Excel
378
46.6
Discrete Fourier transform summary
379
46.7
The sampling theorem
379
46.8
Examples from data collection studies
381
Problems
382
47
Spectral Analysis (Practical Aspects I)
383
47.1
Introduction
383
47.2
Data pre-processing
383
47.3
Worked example: water temperature series
386
47.4
Spectral energy
387
47.5
Frequency resolution
388
47.6
Spectral confidence
388
Problems
390
xiv Contents
48
Spectral
Analysis (Practical Aspects II)
391
48.1
Introduction
391
48.2
Excel example
392
48.3
Practical aspects of spectral analysis
394
48.4
Data collection for spectral analysis
395
Problems
396
Appendix A: Taylor Series
399
A.I Introduction
399
A.2 Fundamental Taylor (Maclaurin) series
401
A.3 Geometric series and convergence
401
A.4 Coding in Fortran
403
A.
5
Coding in Excel
403
A.6 Finite difference approximation
404
A.7 Matrix exponential
404
Appendix B: Error Function and Gamma Function
407
B.I Error function
407
B.2 Gamma function
408
Appendix C: Complex Sinusoid
409
C.I Complex exponential
409
C.2 Coding in Excel and
Matlab
409
C.3 Single mode of vibration
410
Appendix
Đ:
Open-Source Software
411
D.I Introduction
411
D.2 Open-source numerical software
411
D.3 Freely available compilers
412
References
413
Index
421
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language | English |
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spelling | Engineering modelling and analysis David Walker ... 1. publ. London [u.a.] Taylor & Francis 2009 XVI, 424 S. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Ingenieurwissenschaften Mathematisches Modell Engineering models Engineering Mathematical models Walker, David Sonstige oth Erscheint auch als Online-Ausgabe 978-0-203-89454-5 Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017117741&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Engineering modelling and analysis Ingenieurwissenschaften Mathematisches Modell Engineering models Engineering Mathematical models |
title | Engineering modelling and analysis |
title_auth | Engineering modelling and analysis |
title_exact_search | Engineering modelling and analysis |
title_full | Engineering modelling and analysis David Walker ... |
title_fullStr | Engineering modelling and analysis David Walker ... |
title_full_unstemmed | Engineering modelling and analysis David Walker ... |
title_short | Engineering modelling and analysis |
title_sort | engineering modelling and analysis |
topic | Ingenieurwissenschaften Mathematisches Modell Engineering models Engineering Mathematical models |
topic_facet | Ingenieurwissenschaften Mathematisches Modell Engineering models Engineering Mathematical models |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017117741&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT walkerdavid engineeringmodellingandanalysis |