Engineering Informatics

Benny Raphael, National University of Singapore, Singapore
Benny Raphael is an Assistant Professor in the School of Design and Environment at the National University of Singapore. His main areas of research include Computer-aided engineering, Optimization and Machine learning. Ian Smith, EPFL, Lausanne, Switzerland
Ian Smith is Professor and Head of the Applied Computing and Mechanics Laboratory within the Civil Engineering Institute in the School of Architecture, Civil and Environmental Engineering at EPFL. He has also been active in consulting related to monitoring structures, applications of information technology, structural design, evaluation and repair of existing structures and accident analysis in Europe, North America and Japan. He was elected to the Swiss Academy of Engineering Sciences in 2004 and received the Computing in Civil Engineering Award from the Amercian Society of Civil Engineers in 2005. HE is Editor of the"Journal of Advanced Engineering Informatics", and Associate Editor of "Journal of Artificial Intelligence for Engineering Design Analysis and Manufacturing".

• Foreword to the First Edition xiii Preface to the First Edition xviiPreface to the Second Edition xxi1 Fundamental Logic and the Definition of Engineering Tasks 11.1 Three Types of Inference 11.2 Engineering Tasks 31.3 A Model of Information and Tasks 51.4 Another Task Definition 81.5 The Five Orders of Ignorance 91.6 Summary 9Exercises 10References 102 Algorithms and Complexity 112.1 Algorithms and Execution Time of Programs 122.1.1 Program Execution Time versus Task Size 122.2 ‘Big Oh’ Notation 142.2.1 Definition of the Big Oh Notation 152.2.2 Big Oh and Tightness of Bound 162.2.3 Classification of Functions 202.2.4 Examples 212.2.5 Tractability and Algorithm Optimality 302.3 Practical Methods for Determining the Complexity of Algorithms 302.4 P, NP and NP-Completeness 342.4.1 Zero–One Integer Programming (ZOIP) Problem 352.4.2 Classes of NP-Complete Problems 362.5 Summary 37Exercises 37Reference 40Further Reading 403 Data Structures 413.1 Introduction 413.2 Definitions 423.3 Derived Data Types 423.3.1 Examples of Derived Data Types 433.3.2 User-Defined Data Types 453.4 Abstract Data Types 463.4.1 Linked Lists 473.4.2 Graphs 503.4.3 Trees 523.4.4 Stacks 563.4.5 Queues 603.5 An Example: Conceptual Structural Design of Buildings 633.6 Network Science 703.6.1 Types of Networks 713.7 Hashing 733.8 Summary 74Exercises 74Further Reading 794 Object Representation and Reasoning 814.1 Introduction 814.2 Grouping Data and Methods 824.3 Definitions and Basic Concepts 834.3.1 Classes and Objects 834.3.2 Object-Oriented Programming (OOP) 844.3.3 Messages 844.4 Important Characteristics of Objects 844.4.1 Encapsulation of Data and Methods 844.4.2 Message-Passing Mechanism 854.4.3 Abstraction Hierarchy 864.4.4 Secondary Features of Object Representation 884.4.5 Decomposition versus Abstraction 894.5 Applications Outside Programming 904.5.1 Knowledge Representation 914.5.2 User Interfaces 914.5.3 Off-the-Shelf Components 914.5.4 Product Models 914.6 An Object-Oriented Design Methodology 934.6.1 Single versus Multiple Inheritance 934.6.2 Message-Passing Architecture 944.7 Summary 95Exercises 95References 101Further Reading 1015 Database Concepts 1035.1 Introduction 1035.2 Basic Concepts 1045.2.1 Initial Definitions 1045.2.2 Evolution of Types of Databases 1045.2.3 The Three-Level Architecture 1065.3 Relational Database Systems 1065.3.1 The Relational Model 1075.3.2 Limitations of Relational Databases 1115.3.3 Accessing Data in Relational Databases 1125.4 Relational Database Design 1145.4.1 First Normal Form 1145.4.2 Second Normal Form 1155.4.3 Third Normal Form 1185.4.4 Boyce-Codd and Higher Normal Forms 1195.4.5 Importance of Database Design 1205.5 Transaction Processing 1205.5.1 Definition of Transaction 1215.5.2 Implementing Transactions 1225.5.3 Properties of Transactions 1245.6 Other Types of Database 1245.6.1 Object-Oriented Databases 1245.6.2 Geographical Databases 1245.6.3 Multimedia Database Systems 1255.6.4 Distributed Databases 1255.7 Summary 126Exercises 127Transaction A 131Transaction B 131Reference 131Further Reading 1316 Computational Mechanics 1336.1 Introduction 1336.1.1 Challenges of Computational Mechanics 1346.2 From Physical Principles to Practical Systems 1356.3 Methods for Finding Solutions 1376.3.1 Galerkin Method 1376.3.2 Remarks 1396.4 Issues in Computer-Aided Engineering 1396.4.1 Accuracy 1406.4.2 Speed 1416.4.3 User Interaction 1426.5 Summary 142References 142Further Reading 1427 Constraint-Based Reasoning 1437.1 Introduction 1437.2 Terminology 1457.3 Constraint-Solving Methods 1467.3.1 Levels of Consistency for Label Propagation 1477.3.2 Global Consistency in Label Propagation 1487.3.3 Constraint Propagation 1497.4 Reasoning with Constraints on Discrete Variables 1497.4.1 CSP Complexity for Discrete Variables 1517.5 Reasoning with Constraints on Continuous Variables 1517.5.1 Constraint-Based Support for Collaborative Work 1527.6 Summary 156References 1568 Optimization and Search 1578.1 Introduction 1578.2 Basic Concepts 1588.2.1 Types of Optimization Problem 1608.2.2 Formulating Optimization Tasks 1618.2.3 Representing Search Spaces 1638.2.4 Representing Constraints 1648.2.5 Some Optimization Problems 1658.3 Classification of Methods 1678.4 Deterministic Optimization and Search 1698.4.1 Special Cases 1698.4.2 Deterministic Methods 1748.5 Stochastic Methods 1798.5.1 Pure Global Random Search 1828.5.2 Local Search with Multiple Random Starts 1828.5.3 Simulated Annealing 1828.5.4 Genetic Algorithms 1848.5.5 Controlled Random Search 1848.5.6 PGSL 1858.6 A Closer Look at Genetic Algorithms 1888.6.1 Representation: Genetic Encoding 1888.6.2 Evaluating an Individual 1898.6.3 Creating the Initial Population 1898.6.4 The Fitness Function 1908.6.5 Reproduction 1908.6.6 Mutation 1928.7 Summary of Methods 192Exercises 193References 198Further Reading 1989 Knowledge Systems for Decision Support 1999.1 Introduction 1999.2 Important Characteristics of Knowledge Systems 2009.3 Representation of Knowledge 2029.3.1 Representation of Knowledge in Knowledge Systems 2049.4 Reasoning with Knowledge 2059.4.1 Rule Selection and Conflict Resolution 2079.5 Importance of the User Interface 2079.6 Maintenance of Knowledge 2089.7 Model-based Reasoning 2099.8 Case-Based Reasoning 2099.8.1 Stages of Case-Based Reasoning 2109.9 Summary 215Reference 215Further Reading 21510 Machine Learning 21710.1 Introduction 21710.2 Improving Performance with Experience 21810.3 Formalizing the Learning Task 22010.3.1 Searching Hypothesis Spaces 22410.4 Learning Algorithms 22410.4.1 Rote Learning 22510.4.2 Statistical Learning Techniques 22610.4.3 Deductive Learning 23010.4.4 Exploration and Discovery 23110.5 A Closer Look at Artificial Neural Networks 23110.5.1 Types of Neural Network 23510.5.2 Learning in Neural Networks 23610.5.3 Summary of Neural Networks 23710.6 Support Vector Machines 23710.6.1 Support Vector Classification 23710.6.2 Support Vector Regression 24010.7 Summary 240Exercises 241References 242Further Reading 24211 Geometric Modelling 24311.1 Introduction 24311.2 Engineering Applications 24411.2.1 Criteria for Evaluating Representations 24411.3 Mathematical Models for Representing Geometry 24511.3.1 Two-Dimensional Representation of Simple Shapes 24511.3.2 Curves Without Simple Mathematical Representations 24711.3.3 B´ezier Curves 24811.3.4 Mathematical Representation of Simple Surfaces 24911.3.5 B´ezier Patches 25011.3.6 Mathematical Representation of Regular-Shaped Solids 25111.4 Representing Complex Solids 25211.4.1 Primitive Instancing 25211.4.2 Mesh Representations 25311.4.3 Sweep Representations 25511.4.4 Boundary Representations 25711.4.5 Decomposition Models 25811.4.6 Constructive Solid Geometry (CSG) 26011.5 Applications 26311.5.1 Estimation of Volume 26311.5.2 Finite Element Mesh for a Spread Footing 26411.5.3 3D Graphical View of a Structure 26611.6 Summary 267Further Reading 26712 Computer Graphics 26912.1 Introduction 26912.2 Tasks of Computer Graphics 27012.3 Display Devices 27012.3.1 Types of Display Device 27112.3.2 From Geometric Representations to Graphical Displays 27212.4 Representing Graphics 27212.4.1 Representing Colours 27312.4.2 Coordinate System 27312.4.3 Bitmap Representations 27412.4.4 Higher-Level Representations 27512.5 The Graphics Pipeline 27612.5.1 Modelling Transformations 27612.5.2 Viewing Transformations 28012.5.3 Scan Conversion 28512.6 Interactive Graphics 28712.7 Graphical User Interfaces (GUI) and Human–Computer Interaction (HCI) 28812.7.1 Engineer–Computer Interaction 28812.8 Applications 28912.8.1 4D Simulations 28912.8.2 Navigating Multidimensional Solution Spaces 28912.8.3 Computer Vision and Image Processing 29012.8.4 Laser Scanning 29012.9 Summary 292References 292Further Reading 29213 Distributed Applications and the Web 29313.1 Introduction 29313.1.1 A Simple Example of a Client–Server System 29413.1.2 Definitions 29513.1.3 Trends Driving C/S Architecture 29613.2 Examples of Client–Server Applications 29713.2.1 File Servers 29713.2.2 FTP Servers 29813.2.3 Database Servers 29813.2.4 Groupware Servers 29813.2.5 Object Servers 29813.2.6 Operating System Servers 29913.2.7 Display Servers 29913.2.8 Web Servers 30013.2.9 Application Servers 30013.3 Distinctive Features of C/S Systems 30013.3.1 Asymmetrical Protocol 30013.3.2 Message-Based Mechanism 30113.3.3 Why are Protocols Important? 30413.4 Client–server System Design 30413.4.1 Three-Tier Architecture 30513.4.2 Application Partitioning 30613.5 Advantages of Client–Server Systems 30713.6 Developing Client–Server Applications 30713.6.1 TCP/IP Sockets 30813.6.2 Other Middleware Options 30913.7 The World Wide Web 30913.7.1 Limitations of Exchanging Only Static Information 31013.7.2 Common Gateway Interface 31013.7.3 Engineering Applications on the Web 31113.7.4 Other Models for Dynamic Information Exchange 31113.8 Peer-to-Peer Networks 31213.8.1 Information Interchange Through P2P Networks 31413.8.2 P2P Networks for Engineering Applications 31413.8.3 Advantages of Peer-to-Peer Networks 31513.8.4 Issues and Challenges 31513.9 Agent Technology 31613.9.1 Issues in Multi-Agent Systems 31713.10 Cloud Computing 31813.11 Complexity 31913.12 Summary 319Reference 320Further Reading 320Index 321