Sustainable and Resilient Critical Infrastructure Systems (eBook)

Title Page 2
Preface 5
Contents 8
Synthesis of Modeling and Simulation Methods on Critical Infrastructure Interdependencies Research 10
Introduction 11
Brief History of Research on Infrastructure Interdependencies 13
Literature Review Model Description and Category Definitions 18
Hierarchical Decomposition of Existing Literature 19
Definition of Categories and Attributes 21
Appraisal of Research Literature 36
Opportunities and Future Work 41
Summary and Conclusions 43
Appendix 45
References 51
Interdependencies between Energy and Transportation Systems for National Long Term Planning* 61
Introduction 62
Modeling Approach 62
Energy Systems Modeling 63
Transportation Systems Modeling 64
Interdependencies 65
Multiple Objectives 67
Cost 67
Sustainability 68
Resiliency 68
State-of-the-Art and Model Attributes 69
General Formulation 70
Formulation Description 71
Numerical Example 72
Description 73
Parameters 74
Base Case Results 75
Multiobjective Results 77
Discussion 80
References 81
A Framework for Assessing the Resilience of Infrastructure and Economic Systems 85
Introduction 86
Protecting the Nation’s Critical Infrastructure 86
Resilience as a Homeland Security Mandate 89
A Framework for Assessing Infrastructure and Economic Resilience 90
Purpose and Scope 91
A Survey of Resilience Definitions and Frameworks 92
Existing Definitions of Resilience 92
Resilience Assessment Frameworks 95
The System Resilience Framework 100
A Definition of System Resilience for Infrastructure and Economic Systems 100
A Quantitative Approach to Measuring Resilience 102
System Capacities That Determine System Resilience 107
Framework Summary 111
A Qualitative Resilience Assessment for an Earthquake Scenario 112
The Earthquake Scenario 112
Approach 113
Sample Results 114
Summary and Future Work 115
Summary 115
Future Work 116
References 122
Regional Infrastructure Investment Allocation for Sustainability 125
Introduction 125
The Dynamics of Capital Formation 126
Population Dynamics 128
Technological Change 130
Pollution Dynamics 131
Criterion Functional and Final Form of the Model 132
Numerical Examples 133
The Case without Sustainability Constraints 134
The Case with Sustainability Constraints 140
Conclusion 144
References 144
A Framework for the Manifestation of Tacit Critical Infrastructure Knowledge 146
Introduction 146
Risk Analysis for Critical Infrastructure Systems 149
Astrolabe Key Concepts 152
Astrolabe Process Overview 152
Critical Infrastructure Systems Behavior Analysis 154
AIMS Metamodel 158
AIMS Suite Structure 159
Profiling Critical Infrastructure Systems 160
High-Level Critical Infrastructure Models 162
Concluding Remarks 164
References 164
Intelligent Transportation Infrastructure Technologies for Condition Assessment and Structural Health Monitoring of Highway Bridges 166
Introduction 167
Sensor Networks for Highway Bridges 169
Health Indicators and Condition Assessment 172
Functional Performance-Based Diagnostics 173
Modal Analysis and Systems Modeling 178
Span Vibration Monitoring and Analysis: A Case Study 185
References 190
Maintenance Optimization for Heterogeneous Infrastructure Systems: Evolutionary Algorithms for Bottom-Up Methods 192
Introduction 192
Literature Review 194
Methodologies 195
Facility-Level Optimization 197
System-Level Optimization 198
Numerical Examples 202
Test System Creation 202
Algorithm Evaluation 204
Conclusions 205
References 205
A Swarm Intelligence Approach for Emergency Infrastructure Inspection Scheduling 207
Introduction 207
Notation and Symbols 209
Optimization (Generally) 209
Optimum Assignment Problem Definition 209
Particle Swarm Optimization 209
Ant Colony Optimization 210
Problem Formulation 211
Step 1: Optimum Assignment Problem 211
Step 2: Inspection Prioritization Problem 212
Solving the Optimization Problems 212
Particle Swarm Optimization Algorithm 212
Ant Colony Optimization 219
Case Studies 222
Academic Case Study 223
Real World Case Study 225
Conclusions 233
References 234
Optimal Highway Infrastructure Maintenance Scheduling Considering Deterministic and Stochastic Aspects of Deterioration 237
Introduction 237
Markov Decision Process 238
Model Formulation 239
Routine Maintenance (Deterministic Approach) 239
Reactive Maintenance (Stochastic Approach) 240
Solution Algorithm 241
Genetic Algorithms 241
An Example Using BDOT’s Highway Infrastructure 242
Pavement 243
Bridges 243
Mathematical Representation of the Deterioration Function 245
Numerical Example 248
Results, Discussion, and Future Works 250
References 252
Sustainable Rehabilitation of Deteriorated Concrete Highways: Condition Assessment Using Shuffled Complex Evolution (SCE) Global Optimization Approach 255
Introduction 255
Deflection Basin Parameters (DBPs) as Structural Condition Indicators for Sustainable Pavements 257
Deflection Basin Parameters (DBPs) 257
Case Study with Deflection Basin Parameters (DBPs) 259
Hybrid SCE- ANN Approach for Backcalucation of in Situ Stiffness for Sustainable Pavements 262
Shuffled Complex Evolution (SCE) Methodology 262
Artificial Neural Networks (ANNs) 264
Hybrid SCE- ANN Backcalculation Tool 266
Case Study with Hybrid SCE- ANN Backcalculation Tool 267
Concluding Remarks 270
References 270
Author Index 272

"A Framework for the Manifestation of Tacit Critical Infrastructure Knowledge (p. 139-140)

Ebrahim Bagheri * and Ali A. Ghorbani

Abstract. Critical infrastructure systems are tightly-coupled socio-technical systems with complicated behavior. They have emerged as an important focal point of research due to both their vital role in the normal conduct of societal activities as well as their inherent appealing complications for researchers. In this chapter, we will report on our experience in developing techniques, tools and algorithms for revealing and interpreting the hidden intricacies of such systems.

The chapter will include the description of several of our technologies that allow for the guided understanding of the current status quo of infrastructure systems through the Astrolabe methodology, the formal profiling of infrastructure systems using the UML-CI meta-modeling mechanism, and also observing the emergent behavior of these complex systems through the application of the agent-based AIMS simulation suite.

1 Introduction

Critical infrastructures are among the most significant technical systems that influence the ordinary life of any person or the normal operation of any industrial sector. Their importance is mainly due to the type of facilities/utilities that they provide. These facilities (either in the form of asset supply or service provisioning) serve as the building block for any other simple or complex functionality of the society. The outputs of the infrastructures although complex in nature, can be thought of as the essential atomic inputs to other more complex systems.

Apparently, without the proper operation of infrastructure systems, the function of other dependant systems would be disrupted. The very interesting fact is that throughout the years, infrastructure systems themselves have become dependent on each others’ outputs, turning the vertically integrated systems with only a few points of communication, into horizontally integrated systems with various points of interaction in many of their dimensions [1].

Analogous to the dependency of other systems on infrastructures, it can be observed that infrastructure systems themselves are inter-reliant or in other words tightly coupled. As has been extensively studied in the field of fault tolerant computing, a complex system built from interacting components is exposed to a high risk of failure derived from the possibility of mal-function in any of its components. The degree of effectiveness of the failing component in the overall architecture (e.g. in a digital circuit it can be thought of as the number of input/output connections of a specific component), suggests an estimate of the degree of damage or harm that its failure will cause."