Integrating Safety and Security Management to Protect Chemical Industrial Areas from Domino Effects

This book provides insight into domino effects in industrial chemical sites and process industries. It is about the integration of safety and security resources to prevent and mitigate domino effects in the process industries. It explains how chemical industrial areas, comprised of various hazardous installations, are susceptible to a chain of undesired events, or domino effects, triggered by accidental events or intentional attacks and then presents solutions to prevent them. Firstly, the book provides a dynamic graph approach to model the domino effects induced by accidental fire or intentional fire, considering the spatial-temporal evolution of fires. Then, a dynamic risk assessment method based on a discrete dynamic event tree is proposed to assess the likelihood of VCEs and the vulnerability of installations, addressing the time dependencies in vapor cloud dispersion and the uncertainty of delayed ignitions. A dynamic methodology based on dynamic graphs and Monte Carlo is provided to assess the vulnerability of individuals and installations exposed to multi-hazards, such as fire, explosion and toxic release during escalation events. Based on these domino effect models, an economic approach is developed to integrate safe and security resources, obtaining the most cost–benefit protection strategy for preventing domino effects. Finally, a resilience-based approach is provided to find out the most cost-resilient way to protect chemical industrial areas, addressing possible domino effects. This integrated approach will be of interest to researchers, industrial engineers, chemical engineers and safety managers and will help professionals to new solutions in the area of safety and security. Preface 6 Contents 8 List of Figures 12 List of Tables 15 1 Safety and Security of Domino Effects in the Process Industry: The State of the Art 17 1.1 Introduction 17 1.2 Method and Materials 18 1.3 Characterization of Selected Publications 19 1.4 An Overview of Domino Effect Definitions, Characteristics and Classifications 25 1.4.1 Domino Effect Definitions 25 1.4.2 Domino Effect Characteristics 27 1.4.3 Domino Effect Classifications 30 1.5 Vulnerability Assessment of Installations 31 1.5.1 Deterministic Methods 31 1.5.2 Probabilistic Methods 34 1.5.3 CFD/FEM Methods 36 1.6 Risk Assessment of Domino Effects 37 1.6.1 Analytical Methods 37 1.6.2 Graphical Methods 39 1.6.3 Simulation Methods 42 1.7 Safety and Security Management of Domino Effects 43 1.7.1 Inherent Safety 43 1.7.2 Management of Safety Barriers 45 1.7.3 Cooperative Prevention 49 1.7.4 Security of Intentional Domino Effects 50 1.8 Research Trends and Future Needs 52 1.8.1 A Summarization of Current Research 52 1.8.2 Comparison of Different Modeling Approaches and Protection Strategies 54 1.8.3 Research Gaps 56 1.9 Conclusions 58 References 58 2 Dynamic Risk Assessment of Fire-Induced Domino Effects 65 2.1 Introduction 65 2.2 Fire Escalation 66 2.2.1 Spatial Escalation 67 2.2.2 Temporal Escalation 68 2.3 Graph Theory 69 2.3.1 Static Graphs 69 2.3.2 Dynamic Graphs 70 2.4 Domino Evolution Graph Model 71 2.4.1 Dynamic Graph Definition 71 2.4.2 Dynamic Graph Update 73 2.5 Algorithm 77 2.6 Case Study 78 2.6.1 The Application of Graph Metric Approach 79 2.6.2 The Application of Dynamic Graph Approach 80 2.7 Discussion 81 2.8 Conclusions 82 References 82 3 Dynamic Assessment of VCE-Induced Domino Effects 85 3.1 Introduction 85 3.2 VCE-Induced Escalations 86 3.2.1 Past VCE Accidents 87 3.2.2 Explosion Mechanism 89 3.2.3 Impact Assessment of Vapor Cloud Explosions 90 3.2.4 Frequency Assessment of Vapor Cloud Explosions 91 3.3 Dynamic Vulnerability Assessment Methodology 91 3.3.1 Step 1: Identification and Characterization of LOC Scenarios 92 3.3.2 Step 2: Analysis of Vapor Cloud Dispersion 93 3.3.3 Step 3: Identification and Characterization of Ignition Sources 95 3.3.4 Step 4: Explosion Frequency and Delayed Time Assessment 97 3.3.5 Step 5: Overpressure Calculation 99 3.3.6 Step 6: Escalation Assessment 101 3.4 Case Study 102 3.5 Discussion 105 3.6 Conclusions 106 References 107 4 Risk Assessment of Coupled Hazardous Scenarios 110 4.1 Introduction 110 4.2 Modeling 111 4.2.1 Graph Nodes 112 4.2.2 Graph Edges 113 4.2.3 Evolution Time 116 4.3 Graph Update Rules and Simulation Algorithm 117 4.3.1 Graph Update Rules 117 4.3.2 Simulation Algorithm 118 4.4 Case Study 121 4.5 Conclusions 123 References 124 5 Integrated Safety and Security Management to Tackle Domino Effects 126 5.1 Introduction 126 5.2 Safety and Security Management Principles 127 5.2.1 Inherent Safety and Security 127 5.2.2 Layers/Rings of Protection 129 5.3 Integrated Safety and Security Management 130 5.3.1 Motivations for Integrating Safety and Security 130 5.3.2 Classification of Protection Measures 132 5.4 An Integrated Approach to Manage Domino Effects 134 5.4.1 Chemical Plant Description 135 5.4.2 Threat and Hazard Analysis 135 5.4.3 Vulnerability Assessment of Installations Against Direct and Threats 138 5.4.4 Assessment of the Evolution of Domino Effects 138 5.4.5 Consequence Analysis 139 5.4.6 Risk Evaluation 140 5.4.7 Risk Treatment 142 5.5 Conclusions 144 References 144 6 An Economic Approach for Domino Effect Management 147 6.1 Introduction 147 6.2 Safety Economics 148 6.2.1 Risk-Based Optimization 149 6.2.2 Minimum Total Cost Approach 151 6.2.3 Cost–Benefit Analysis 153 6.2.4 Cost-Effectiveness Analysis 155 6.2.5 Multi-objective Optimization 156 6.2.6 Game Theoretical Approach 157 6.3 A Cost–Benefit Analysis of Domino Effect Management 159 6.3.1 Protection Strategy Cost 159 6.3.2 The Costs of Domino Effects 160 6.3.3 Net Benefits Analysis 162 6.4 Optimization Algorithm 164 6.5 Conclusions 164 References 166 7 A Resilience-Based Approach for the Prevention and Mitigation of Domino Effects 169 7.1 Introduction 169 7.2 Chemical Plant Resilience 170 7.2.1 Resilience Concept 170 7.2.2 A Definition of Chemical Plant Resilience 171 7.2.3 Resilience Metrics 173 7.2.4 Capabilities of Chemical Plant Resilience 174 7.3 A Quantification Framework of Chemical Plant Resilience 176 7.3.1 Resistance Modeling 176 7.3.2 Mitigation Modeling 177 7.3.3 Adaptation Modeling 178 7.3.4 Restoration Modeling 179 7.4 Simulation Algorithm 179 7.5 Case Study 181 7.5.1 Resistance Analysis 182 7.5.2 Mitigation Analysis 183 7.5.3 Adaptation Analysis 185 7.5.4 Restoration Analysis 185 7.5.5 Resilience Measure Performance 186 7.6 Conclusions 186 References 187 8 Conclusions and Future Research 191 8.1 Main Conclusions 192 8.2 Recommendations for Future Research 196 References 198