Modelling in Natural Sciences: Design, Validation and Case Studies

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Springer Science & Business Media, Feb 14, 2003 - Science - 459 pages
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This book defines the wide application of the art of modelling. The main emphasis is on the imaging of dynamic processes which are analysed and subdivided into their atomic constituents by means of systems analysis. The cyclic structure and the stages of models’ set-up are explained. The evaluation of a model’s quality is regarded as a stochastic process. The aspects of grade used in different fields of sciences are brought into perspective. Thus, a quantitative concept of validity on the basis of conditional degrees of rational belief can be developed.

 

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Contents

Models
1
12 Etyma
31
13 Purposes
34
Systems
46
22 Characterizing Systems
49
23 Dynamic Systems
63
24 Systems Analysis
72
Mappings
97
Tolerance
228
82 The Quantitative Aspect
234
Tests
237
92 Terminology
239
93 Testing
242
Validity
249
101 Validation
250
102 The Scope
251

32 Structure Preservation
100
33 Chains and Invariants
107
34 Morphisms
111
Characterizing Models
120
41 Contents
121
42 Selection
127
43 Projection
134
The Art of Modelling
139
51 Creating a Model
142
52 Quality Criteria
159
Inferences
169
61 Deductive Inference
171
62 Inductive Inference
179
63 Personal Inference
191
Probabilities
195
72 Inductive Stochastic Inference
198
73 Certainty and Prior Probability
223
103 Epistemic Foundations
257
104 Quantifying the Validity of a Model
260
105 Evaluating a Model
265
Suggestions for Further Reading
267
References
269
Appendix
275
Modelling the Evolution of Galaxies
279
Model Environments for an Early Alkaline Ocean
309
Reconstructing the development of paleospecies
323
The Modau Case Study
335
Physical Modeling of a Glass Melter
357
Modelling of Complexation Equilibria
379
Weather Prediction by Numerical Modelling of Atmospheric Processes
413
Simulation of Hydrogen Behaviour During a Nuclear Power Plant Accident
435
List of Contributors
457
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