A Hetero-functional Graph Theory for Modeling Interdependent Smart City Infrastructure (eBook)

Wester C.H. Schoonenberg is a Doctoral Research Assistant in the Laboratory for Intelligent Integrated Networks of Engineering Systems (LIINES), at the Thayer School of Engineering at Dartmouth.  His research interests include Integrated Smart City Infrastructure Modeling, and Industrial Energy Management & Demand Response.  Wester received his B.Sc. in 2014 from the department of Systems Engineering and Policy Analysis Management at Delft University of Technology, and joined the LIINES directly thereafter.  Inas Khayal, Ph.D. is an Assistant Professor at the Dartmouth Institute of Health Policy & Clinical Practice at the Geisel School of Medicine and Adjunct Assistant Professor at the Department of Computer Science at Dartmouth College.  Dr. Khayal is a highly interdisciplinary researcher focused on translational research towards improving chronic disease health outcomes. This began with her biomedical research within the clinic, focused on biological sensing in NeuroOncology and MR Imaging.  Her work expanded to include Social and Environmental Sensing using Internet-of-Things enabled sensors outside the clinic and within ‘real-world’ living labs.  Her work acts at the intersection of engineering, medicine, computer science and innovation to address the reality of the multi-level interconnected systems we live in.  Her most recent work seeks to develop systems solutions that curb the growth of chronic disease by modeling, measuring, designing and implementing systems.  Dr. Khayal earned her PhD in Bioengineering from both the University of California, Berkeley and the University of California, San Francisco, a BS in Biomedical Engineering from Boston University and completed the Management of Technology Program from the University of California, Berkeley, Haas School of Business.  She holds several US, European, and International patents and is featured in the book Medicine by Design:  The Practice and Promise of Biomedical Engineering by Fen Montaigne.  She has also been selected as a 2017 Systems Science Scholar by AcademyHealth.  She has served on the faculty in the departments of Medicine, Engineering and Computer Science.   Prof. Amro M. Farid is currently an Associate Professor of Engineering at the Thayer School of Engineering at Dartmouth and Adjunct Associate Professor of computer science at the Department of Computer Science. He leads the Laboratory for Intelligent Integrated Networks of Engineering Systems  (LIINES).  The laboratory maintains an active research program in Smart Power Grids Energy-Water Nexus Energy-Transportation Nexus Industrial Energy Management & Demand Response Integrated Smart City Infrastructures  He received his Sc. B. in 2000 and his Sc. M. 2002 from the MIT Mechanical Engineering Department. He went onto complete his Ph.D. degree at the Institute for Manufacturing within the University of Cambridge (UK) Engineering Department in 2007. He has varied industrial experiences from the automotive, semiconductor, defense, chemical, and manufacturing sectors. In 2010, he began his academic career as a visiting scholar at the MIT Technology Development Program. He is also a Research Affiliate at the MIT Mechanical Engineering Department and the U. of Massachusetts Transportation Research Center. He has made active contributions to the MIT-Masdar Institute Collaborative Initiative, the MIT Future of the Electricity Grid Study, and the IEEE Vision for Smart Grid Controls. He currently serves on the Executive Committee for the Council of Engineering Systems Universities (CESUN). He is a senior member of the IEEE and holds leadership positions in the IEEE Control Systems Society (CSS) Technical Committee on Smart Grids, and the IEEE Systems, Man & Cybernetics (SMC) Technical Committee on Intelligent Industrial Systems. He is also a member of the IEEE SMC Technical Committee on Distributed Intelligent Systems, the IEEE Industrial Electronics Society Technical Committee on Industrial Agents, and the ASME Dynamics Systems & Control Division. 

Preface 6
Why This Book? 6
Where Did Hetero-functional Graph Theory Come from? 8
The Goal of This Book 9
What Is in This Book? 9
Contents 11
List of Figures 14
List of Tables 21
Nomenclature 22
1 Introduction 26
1.1 Book Contribution 28
1.2 Book Outline 30
References 30
2 The Need for Hetero-functional Graph Theory 38
References 42
3 Hetero-functional Graph Theory Preliminaries 47
3.1 Ontological Foundation for Hetero-functional Graph Theory 47
3.2 Systems Engineering Foundations 51
References 58
4 Hetero-functional Graph Theory 60
4.1 System Concept 61
4.1.1 System Form 63
4.1.2 System Function 66
4.1.3 Allocation of System Function onto System Form 71
4.2 Hetero-functional Adjacency Matrix 78
4.3 Controller Agency Matrix 83
4.4 Controller Adjacency Matrix 87
4.5 Service as Operand Behavior 91
4.5.1 Service Delivery as Service Net 93
4.5.2 Service Delivery as Service Graph 96
4.6 Service Feasibility Matrix 96
4.6.1 Service Feasibility Matrix Definitions 97
4.6.2 Service Degrees of Freedom 102
4.7 The System Adjacency Matrix: An Integrated View of Hetero-functional Graph Theory 105
4.8 Conclusion 112
References 114
5 Modeling Interdependent Smart City Infrastructure Systems with HFGT 117
5.1 The Role of Test Cases in Smart City Development 117
5.2 Smart City Test Case: Trimetrica 118
5.3 System Concept 123
5.3.1 Smart City Resources 123
5.3.2 Smart City Processes 131
5.3.3 Smart City Knowledge Base 136
5.3.4 Visualizing Degrees of Freedom 140
5.4 Hetero-functional Adjacency Matrix 147
5.4.1 Calculating System Sequence 147
5.4.2 Visualizing System Sequence 149
5.5 Controller Agency Matrix 153
5.5.1 Expansion of System Resources 156
5.5.2 Smart City Controller Agency Matrix 157
5.5.3 The Relation Between the Controller Agency Matrix and the Hetero-functional Adjacency Matrix 157
5.6 Controller Adjacency Matrix 158
5.7 Service as Operand Behavior 161
5.7.1 Service Delivery in SysML 161
5.7.2 Service Delivery Using Petri Nets 164
5.7.3 Service Delivery as Service Graph 167
5.8 Service Feasibility Matrix 168
5.8.1 Deliver Potable Water 170
5.8.2 Deliver Electric Power 171
5.8.3 Deliver Electric Vehicle 172
5.8.4 Visualizing the Service Feasibility Matrix 172
5.9 System Adjacency Matrix 174
5.9.1 Trimetrica's System Adjacency Matrix 174
5.9.2 Hetero-functional Graph Visualization 176
5.10 Discussion 177
5.10.1 Ontological Analysis of Hetero-functionalGraph Theory 178
5.10.2 Comparison with Multi-layer Networks 180
References 182
6 Applications of Hetero-functional Graph Theory 184
6.1 Mass-Customized Production Systems 184
6.2 Multi-Modal Transportation Systems 186
6.3 Electric Power Systems 186
6.4 Multi-Modal Electrified Transportation Systems 187
6.5 Microgrid-Enabled Production Systems 188
6.6 Personalized Healthcare Delivery Systems 188
References 189
7 Conclusion and Future Work 192
7.1 Conclusion 192
7.2 Future Work 194
A Representing a Four-Layer Network in Hetero-functional Graph Theory 195
A.1 System Concept 197
A.2 Hetero-functional Adjacency Matrix 202
A.3 Controller Agency Matrix 202
A.4 Controller Adjacency Matrix 202
A.5 Service as Operand Behavior 204
A.6 Service Feasibility Matrix 206
A.7 System Adjacency Matrix 206
List of Definitions 209
Index 211