Front Cover; DYNAMIC RISKANALYSIS IN THECHEMICAL AND PETROLEUM INDUSTRY; DYNAMIC RISKANALYSIS IN THECHEMICAL AND PETROLEUM INDUSTRY: Evolution and Interaction with Parallel Disciplines in the Perspective of Industrial Application; Copyright; CONTENTS; CONTRIBUTORS; PREFACE; I
A Short Overview of Risk Analysis Background and Recent Developments ; 1. INTRODUCTION; 2. FUNDAMENTALS OF RISK ANALYSIS; 2.1 Quantitative Risk Analysis; 2.2 Applications, Accomplishments, and Limitations of QRA in the Chemical Process Industry; 3. WAY FORWARD: DYNAMIC RISK ASSESSMENT APPROACHES.
3.1 Potential Improvements and Limitations4. CONCLUSIONS; REFERENCES; 2
New Definitions of Old Issues and Need for Continuous Improvement ; 1. INTRODUCTION; 2. ATYPICAL ACCIDENT SCENARIOS; 3. BLACK SWANS; 4. DRAGON KINGS; 5. SMALL THINGS; 6. CONCLUSIONS; REFERENCES; ll
Dynamic Risk Analysis; 2.1
Advanced Technique for Dynamic Hazard Identification ; 1. INTRODUCTION; 2. A FRAMEWORK FOR THE IDENTIFICATION OF ATYPICAL SCENARIOS; 3. STATE OF THE ART; 4. DYNAMIC PROCEDURE FOR ATYPICAL SCENARIOS IDENTIFICATION.
4.1 Hazard Identification Deficiencies Tackled by DyPASI4.1.1 Completeness; 4.1.2 Reproducibility; 4.1.3 Inscrutability; 4.1.4 Relevance of Experience; 4.1.5 Subjectivity; 4.2 Limitations and Integration With Other Techniques; 5. CONCLUSIONS; REFERENCES; 4
Dynamic Hazard Identification: Tutorial and Examples ; 1. INTRODUCTION; 2. METHODOLOGY TUTORIAL; 2.1 Step 0: Preliminary Activity; 2.2 Step 1: Retrieval of Risk Notions; 2.3 Step 2: Prioritization; 2.4 Step 3: Atypical Scenarios Identification; 2.5 Step 4: Definition of Safety Barriers; 2.6 Follow-up; 3. APPLICATION OF THE APPROACH.
3.1 Bow-Tie Analysis3.2 DyPASI Application; 4. CONCLUSIONS; REFERENCES; 2.2
Analysis of Initiating Events; 5
Reactive Approaches of Probability Update Based on Bayesian Methods ; 1. INTRODUCTION; 2. BAYESIAN INFERENCE; 2.1 Bayes' Theorem; 2.2 Hierarchical Bayesian Analysis; 3. BAYESIAN NETWORK; 3.1 Conventional Bayesian Network; 3.2 Dynamic Bayesian Network; 3.2.1 Interval-based Dynamic Bayesian Network; 3.2.2 Instant-based Dynamic Bayesian Network; 4. LIMITED MEMORY INFLUENCE DIAGRAM; 5. CONCLUSIONS; REFERENCES; 6
Proactive Approaches of Dynamic Risk Assessment Based on Indicators.
1. INTRODUCTION2. PROACTIVE AND DYNAMIC FEATURES; 3. TECHNIQUES FOR DEVELOPMENT OF INDICATORS; 4. TECHNIQUES FOR FREQUENCY MODIFICATION; 5. THE RISK BAROMETER TECHNIQUE; 5.1 Support to Decision-Making; 6. CONCLUSIONS; REFERENCES; 7
Reactive and Proactive Approaches: Tutorials and Example ; 1. INTRODUCTION; 2. METHODOLOGY TUTORIAL; 2.1 Bayesian Inference-based Dynamic Risk Assessment; 2.1.1 Step 0: Scenario Identification; 2.1.2 Step 1: Prior Function Formation; 2.1.3 Step 2: Likelihood Function Formation; 2.1.4 Step 3: Posterior Function Evaluation; 2.1.5 Step 4: Frequency Updating.
