Table of Contents
Preface ix
Acknowledgements ix
1 Introduction 1
1.1 Background and Motivation . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Infrastructure Systems . . . . . . . . . . . . . . . . . . . . 1
1.1.2 The Dynamics in Infrastructure System Environments . . 2
1.1.3 FRAME Performance Indicators . . . . . . . . . . . . . . 2
1.2 Infrastructure Systems Design: Life Cycle Perspective . . . . . . 6
1.2.1 Infrastructure Systems Life Cycle Design . . . . . . . . . 7
1.2.2 FRAME Integration in Infrastructure Systems at the conceptual design stage . . . . . . . . . . . . . . . . . . . . . 8
1.3 Research Question and Objectives . . . . . . . . . . . . . . . . . 9
1.4 Outline of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2 FRAME in Systems Conceptual Design: A Review 15
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Flexibility Considerations in Systems Conceptual Design . . . . 16
2.2.1 Problem formulation approaches . . . . . . . . . . . . . . 16
2.2.2 Measures and Metrics for flexibility . . . . . . . . . . . . . 18
2.2.3 Application of analysis methods to specific processes /
systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3 Reliability, Availability and Maintainability Analysis Techniques 20
2.3.1 Analytical-assisted RAM investigation methods . . . . . 21
2.3.2 Reliability Block Diagram (RBD) . . . . . . . . . . . . . . 21
2.3.3 Markov model . . . . . . . . . . . . . . . . . . . . . . . . 23
2.3.4 Simulation-assisted RAM analysis methods . . . . . . . . 26
2.3.5 Multi-state RAM Concept . . . . . . . . . . . . . . . . . . 26
2.4 Reliability and maintenance optimization . . . . . . . . . . . . . 27
2.4.1 Reliability Allocation and Optimization . . . . . . . . . . 28
2.4.2 Maintenance Optimization in Design . . . . . . . . . . . . 29
2.4.3 RAM Modeling and Optimizations: Concurrent integration into Conceptual Designs . . . . . . . . . . . . . . . . 30
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2.5 Multi-objective Optimization . . . . . . . . . . . . . . . . . . . . 30
2.6 Chapter summary and leading problem description . . . . . . . . 34
3 Infrastructure Systems Conceptualization 43
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2 Infrastructure Systems . . . . . . . . . . . . . . . . . . . . . . . . 44
3.2.1 Infrastructure Systems Categorization . . . . . . . . . . . 47
3.2.2 Energy and industrial infrastructure systems . . . . . . . 48
3.3 Infrastructure and process systems: Comparative analysis . . . . 49
3.3.1 Spatial and Temporal Scale Comparison . . . . . . . . . . 55
3.4 Infrastructure as System-of-Systems . . . . . . . . . . . . . . . . 57
3.5 Infrastructure systems as Socio-Technical Systems (STS) . . . . . 59
3.6 Interaction of FRAME with infrastructure systems surroundings 61
3.7 Meta-model of Infrastructure Systems Design . . . . . . . . . . . 62
3.8 Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4 Integrating Flexibility in Infrastructure Systems Design 69
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2 Conceptualization of Infrastructure Systems Flexibility . . . . . . 70
4.2.1 Drivers of Infrastructure Systems Flexibility . . . . . . . . 70
4.2.2 Infrastructure Systems Flexibility: A Functional Definition 73
4.2.3 Incorporating Uncertainty Analysis in Infrastructure systems Design . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3 Framework for integrating flexibility in infrastructure system designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.4 Identifying system constraints and uncertainties . . . . . . . . . 83
4.5 Setting up flexibility measure and process models . . . . . . . . . 84
4.5.1 Flexibility measure model: Deterministic approach . . . . 84
4.5.2 Flexibility Measure: Extended Deterministic Approach . . 87
4.5.3 Procedure for triangulating the Flexibility space F . . . . 90
4.5.4 System-Wide Flexibility Index . . . . . . . . . . . . . . . 91
4.6 Illustrative Test Case . . . . . . . . . . . . . . . . . . . . . . . . 91
4.7 Analysis and Evaluation . . . . . . . . . . . . . . . . . . . . . . . 99
4.7.1 Deterministic approach . . . . . . . . . . . . . . . . . . . 99
4.7.2 Extended Deterministic Approach . . . . . . . . . . . . . 100
4.8 System-wide flexibility index for the deterministic and extended
deterministic cases . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.9 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5 RAM in Infrastructure Systems Design 109
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.2 InfraSystems Reliability: Hierarchical Markov Modeling Approach 111
5.2.1 Reliability modeling at the component level . . . . . . . . 111
5.2.2 Reliability modeling at the sub-system(unit) level . . . . . 114
5.2.3 Reliability modeling at the system level . . . . . . . . . . 114
5.2.4 Illustrative Case Study . . . . . . . . . . . . . . . . . . . . 115
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5.3 Infrastructure systems Availability: Multi-state UGF approach . 121
5.3.1 MSMP formulation . . . . . . . . . . . . . . . . . . . . . . 123
5.3.2 The UGF-based Multi-State Multi-Performance Model . . 123
5.3.3 Illustrative Case study . . . . . . . . . . . . . . . . . . . . 126
5.4 Maintainability incorporation in infrastructure systems design . . 133
5.4.1 Infrastructure Systems Maintainability (Innate) . . . . . . 134
5.4.2 Incorporation of Markov Maintenance Models in Infrastructure Systems Conceptual Design . . . . . . . . . . . . 140
5.4.3 Optimization of the infra-system availability wrt to maintenance crew allocation . . . . . . . . . . . . . . . . . . . 151
5.5 Illustrative Example: . . . . . . . . . . . . . . . . . . . . . . . . . 151
5.6 Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . 158
6 Extended Economic Model for IS Conceptual Design 163
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6.2 Markov RAM-based Economic Model . . . . . . . . . . . . . . . 165
6.2.1 Social (user) Cost Model . . . . . . . . . . . . . . . . . . . 167
6.2.2 Decommissioning Cost Model . . . . . . . . . . . . . . . . 169
6.2.3 Resource Cost Model . . . . . . . . . . . . . . . . . . . . . 172
6.2.4 Investment Costs Model . . . . . . . . . . . . . . . . . . . 173
6.2.5 Maintenance Costs Model . . . . . . . . . . . . . . . . . . 175
6.2.6 Revenue Model . . . . . . . . . . . . . . . . . . . . . . . . 177
6.2.7 Expected Cash Flow Model . . . . . . . . . . . . . . . . . 178
6.2.8 Expected Net Present Value Model . . . . . . . . . . . . . 179
6.3 Illustrative Case Study . . . . . . . . . . . . . . . . . . . . . . . . 181
6.3.1 Equipment and Investment Costs . . . . . . . . . . . . . . 181
6.3.2 Maintenance Costs . . . . . . . . . . . . . . . . . . . . . . 183
6.3.3 Social costs . . . . . . . . . . . . . . . . . . . . . . . . . . 185
6.3.4 Decommissioning Cost . . . . . . . . . . . . . . . . . . . . 186
6.3.5 Resource and Production costs . . . . . . . . . . . . . . . 187
6.3.6 Total production cost . . . . . . . . . . . . . . . . . . . . 188
6.3.7 Revenues . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
6.3.8 Cash Flow analysis . . . . . . . . . . . . . . . . . . . . . . 190
6.3.9 Net Present Value (NPV) Estimation . . . . . . . . . . . 191
6.4 Global Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . 192
6.4.1 Sensitivity of the economy of the DHN process to the
quantity of heat to be demanded . . . . . . . . . . . . . . 193
6.4.2 Sensitivity of the economy of the DHN process to discount
rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
6.4.3 Sensitivity of the economy of the DHN process to the
products being produced . . . . . . . . . . . . . . . . . . . 194
6.4.4 Sensitivity of the economy of the DHN process to higher
product prices . . . . . . . . . . . . . . . . . . . . . . . . 195
6.4.5 Sensitivity of the economy of the DHN process to resource
costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
6.4.6 Sensitivity to source and sink temperatures . . . . . . . . 195
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6.4.7 Sensitivity to intrinsic reliability of chosen pieces of equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
6.5 Chapter summary and reflections . . . . . . . . . . . . . . . . . . 196
7 FRAME in IS Design: Multi-objective Optimization Strategy 203
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
7.2 Multi-Objective Optimization Framework . . . . . . . . . . . . . 205
7.3 Design Model Overview . . . . . . . . . . . . . . . . . . . . . . . 206
7.3.1 Optimization of IS Cost(CAPEX/OPEX) vs RAM . . . . 208
7.3.2 Optimizing RAM/NPV Performances of Infrastructure systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
7.4 Illustrative Case Study Set-up . . . . . . . . . . . . . . . . . . . . 223
7.4.1 Process Description of Steam-Turbine CDHP (ST-CDHP)
System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
7.4.2 Parameters of Steam-Turbine CDHP (ST-CDHP) System 225
7.5 Results and Discussions of RAME Optimization of Illustrative
Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
7.5.1 Total cost vs [RM]inherent of the CDHP case study . . . 227
7.5.2 CAPEX vs [RM]inherent (with Redundancy) of the CDHP
case study . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
7.5.3 CAPEX vs OPEX Trade-off Analysis of the CDHP case
study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
7.5.4 NPV vs Level of Redundancy Allocation of the CDHP
case study . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
7.5.5 NPV vs [RM]inherent Performance Trade-Off of the CDHP
Case study . . . . . . . . . . . . . . . . . . . . . . . . . . 234
7.6 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . 235
8 Adaptive Updating Strategy for Infrasystems RAME 241
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
8.2 Model Development . . . . . . . . . . . . . . . . . . . . . . . . . 242
8.2.1 State-based RAM Performance Model: . . . . . . . . . . . 244
8.2.2 Observability of system states & data: . . . . . . . . . . . 246
8.2.3 Updating procedure: . . . . . . . . . . . . . . . . . . . . . 247
8.3 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
8.4 Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . 253
9 Conclusions, Recommendations & Outlook 255
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
9.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
9.3 Recommendations and Future work . . . . . . . . . . . . . . . . . 262
9.4 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
9.4.1 Implications for Process & Infrastructure Systems Engineering Education . . . . . . . . . . . . . . . . . . . . . . 266
9.4.2 Industries and FRAME data acquisition . . . . . . . . . . 266
9.4.3 Integrated Approach to Infrastructure systems designs . . 266
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Appendices: 269
A Derivation of the UGF model for Illustrative Example. 271
B Derivation of the UGF model for the DHN case study. 275
C [RM]inherent at Varying Bounded Zones. 283
Summary 285
Samenvatting 289
About the author 293
Abstract
The environment in which large-scale process and energy infrastructure systems operate is becoming more dynamic and subject to various uncertainties and disturbances. These challenge the engineers and designers to provide solutions and designs that are not only adaptive to a wide range of future conditions and requirements but are reliable.In addressing these challenges, the research methodologically explores how the key performance metrics- Flexibility, Reliability, Availability, Maintainability and Economics (FRAME) can be integrated early in the conceptual design phase of large-scale process and energy infrastructure systems. Novel, structured and systematic conceptual frameworks and mathematical models, for integrating these metrics early in the conceptual design process have been formulated. Solution methods for these mathematical models have been explored. And their applicability, utility and relevance have been demonstrated through thoughtfully designed contemporary process and energy infrastructure systems.
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