Materials design using computational intelligence techniques

184 Pages·2017·15.652 MB·English

by  Datta, Shubhabrata

Materials Design
Using Computational
Intelligence Techniques

Materials Design
Using Computational
Intelligence Techniques
Shubhabrata Datta
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Dedicated to my parents and teachers

Contents
List of Figures .........................................................................................................xi
List of Software and Web Resources ...............................................................xvii
Preface ...................................................................................................................xix
Acknowledgements ..........................................................................................xxiii
Author ..................................................................................................................xxv
1. Introduction .....................................................................................................1
1.1 Computers and Design .........................................................................1
1.2 Computational Intelligence .................................................................5
1.3 Materials Design: Past, Present and Future ......................................9
References .......................................................................................................11
2. Conventional Approaches to Materials Design .....................................13
2.1 Density Functional Theory ................................................................14
2.2 Molecular Dynamics ..........................................................................15
2.3 Thermodynamic Modelling and the CALPHAD Approach ........16
2.4 Phase-Field Simulation .......................................................................18
2.5 Cellular Automata and Monte Carlo Simulations ..........................19
2.6 Finite Element and Other Similar Methods ....................................21
2.7 Multiscale Modelling and Integrated Computational
Materials Engineering ........................................................................21
References .......................................................................................................23
3. Statistics and Data Mining Concepts in Materials Design .................25
3.1 An Overview of Statistical Modelling in the Materials Field .......25
3.2 Concept of Data Mining .....................................................................27
3.3 Mining Materials Data and Informatics-Based Design ................29
3.3.1 Hot Rolled Steel Plate Classification ...................................29
3.3.2 High-Temperature Superconductors ...................................33
3.4 Problems and Prospects .....................................................................34
References .......................................................................................................36
4. Neural Networks and Genetic Programming for Materials
Modelling .......................................................................................................39
4.1 Artificial Neural Networks ................................................................39
4.2 Genetic Programming ........................................................................44
4.3 Applications in Materials Engineering ............................................45
4.3.1 In Situ Prediction of Porosity of Nanostructured
Porous Silicon .........................................................................45
4.3.2 Steel Plate Processing ............................................................48
vii
viii Contents
4.3.3 Strength of HSLA Steel Using a Customised Network ....50
4.3.4 An Example of Unsupervised Learning ............................52
4.3.5 Example of an Application of Genetic Programming ......53
4.4 Suitability as Materials Design Tools ...............................................54
References .......................................................................................................63
5. Knowledge Extraction Using Fuzzy and Rough Set Theories ............65
5.1 Fuzzy Logic ..........................................................................................66
5.1.1 Rule Extraction Using Clustering Methods .......................67
5.2 Rough Set Theory ................................................................................68
5.3 Case Studies of Successful Applications..........................................70
5.3.1 Friction Stir Welding of Al Alloys .......................................70
5.3.2 Ultrasonic Drilling of Ceramic Materials ...........................71
5.3.3 Mechanical Properties of Ti Alloys .....................................73
5.3.4 Mechanical Properties of TRIP Steel ...................................80
5.4 Potential Future Applications ...........................................................82
References .......................................................................................................83
6. Handling Imprecise Knowledge through Fuzzy Inference Systems ...85
6.1 Fuzzy Inference Systems ....................................................................86
6.2 Adaptive Neuro-FIS ............................................................................88
6.3 Case Studies .........................................................................................90
6.3.1 Modelling HSLA Steel...........................................................90
6.3.2 Modelling TRIP-Aided Steel ................................................94
6.3.3 Machining of Ti Alloy ...........................................................99
6.3.4 Ageing of Cu-Bearing Steel ................................................102
6.4 Uncertainty and Imprecision in Materials Systems .....................105
References .....................................................................................................106
7. Evolutionary Algorithms for Designing Materials .............................107
7.1 Optimisation for Designing New Materials .................................107

7.1.1 Multiobjective Optimisation ..............................................109
7.2 Evolutionary Optimisation Algorithms ........................................110
7.3 Case Studies of Optimisation-Based Materials Design ...............112
7.3.1 Optimisation of Cold Rolling Mills ..................................113
7.3.2 Gas Injection in Steelmaking .............................................114
7.3.3 Strength and Ductility Optimisation of Low-Carbon
Steel ........................................................................................114
7.3.4 Optimisation of the PET Reactor Using DE .....................117
7.4 Issues in the Optimisation Approach ............................................120
References .....................................................................................................121
Contents ix
8. Using Computational Intelligence Techniques in Tandem ...............123
8.1 Designing Materials with ANN Models as the Objective
Function ..............................................................................................123
8.1.1 Designing Steel with Custom-Made Properties ..............124
8.1.2 Designing Novel Age-Hardenable Aluminium Alloys ....129
8.1.3 Optimum Processing for Better Shape Memory
Effect of Nitinol ....................................................................135
8.2 Polymer Composite Design with Fuzzy Models
as the Objective Function .................................................................138
8.3 Other Possible Approaches ..............................................................142
References .....................................................................................................143
9. Concluding Remarks .................................................................................145
9.1 Conventional versus CI-Based Materials Design .........................145
9.2 Microstructure ...................................................................................146
9.3 Green Design .....................................................................................147
9.4 Handling Uncertainty ......................................................................147
9.5 Robust Solution .................................................................................148
9.6 DIKUW Hierarchy ............................................................................149
References .....................................................................................................150
Index .....................................................................................................................153