Dynamic risk analysis in the chemical and petroleum industry : evolution and interaction with parallel disciplines in the perspective of industrial application

Dynamic risk analysis in the chemical and petroleum industry evolution and interaction with parallel disciplines in the perspective of industrial application

Dynamic Risk Analysis in the Chemical and Petroleum Industry focuses on bridging the gap between research and industry by responding to the following questions: What are the most relevant developments of risk analysis? How can these studies help industry in the prevention of major accidents? Paltrin...

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Detalles Bibliográficos
Otros Autores: Paltrinieri, Nicola, author (author), Paltrinieri, Nicola, editor (editor), Khan, Faisal I., editor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Oxford, United Kingdom : Butterworth-Heinemann [2016]
Edición:1st edition
Colección:Butterworth-Heinemann/IChemE series.
Materias:
Chemical industry > Risk assessment.
Petroleum industry and trade > Risk assessment.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629870106719
Tabla de Contenidos:
  • 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 - Introduction
  • 1 - 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 Limitations
  • 4. 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 - Hazard Identification
  • 3 - 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 DyPASI
  • 4.1.1 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 Analysis.
  • 3.2 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. INTRODUCTION
  • 2. 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
  • 2.2 Risk Barometer
  • 2.2.1 Step 1: Define Major Accident Scenarios
  • 2.2.2 Step 2: Review Relevant Information Sources
  • 2.2.3 Step 3: Establish Barrier Functions and Barrier Systems
  • 2.2.4 Step 4: Evaluate Relative Importance of the Barrier Systems
  • 2.2.5 Step 5: Establish Suitable Barrier Indicators
  • 2.2.6 Step 6: Establish Risk Model Based on Barrier Indicators
  • 2.2.7 Step 7: Visualization and Application
  • 3. APPLICATION OF REACTIVE AND PROACTIVE APPROACHES
  • 3.1 Topside Process of an Oil and Gas Offshore Platform
  • 3.2 Bayesian Inference-based Dynamic Risk Assessment
  • 3.3 Risk Barometer
  • 4. CONCLUSIONS.
  • REFERENCES
  • 8 - Comparison and Complementarity between Reactive and Proactive Approaches
  • 1. INTRODUCTION
  • 2. BENEFITS AND LIMITATIONS OF REACTIVE AND PROACTIVE APPROACHES
  • 2.1 Bayesian Inference-Based Dynamic Risk Assessment
  • 2.2 Risk Barometer
  • 3. COMPARISON AND COMPLEMENTARITY OF THE TWO TECHNIQUES
  • 3.1 Comparison
  • 3.2 Complementarity
  • 4. CONCLUSIONS
  • REFERENCES
  • 2.3 - Analysis of Consequences
  • 9 - Dynamic Consequence Analysis through Computational Fluid Dynamics Modeling
  • 1. INTRODUCTION
  • 2. IMPLEMENTATION OF COMPUTATIONAL FLUID DYNAMICS MODELING INTO DYNAMIC RISK ASSESSMENT
  • 3. COMPUTATIONAL FLUID DYNAMIC MODELS FOR SPECIFIC ACCIDENTAL SCENARIOS
  • 3.1 Advanced Source Terms and Outflow Models
  • 3.1.1 Computational Fluid Dynamic Modeling of Jet Releases
  • 3.1.2 Computational Fluid Dynamic Modeling of Pool Spreading and Evaporation
  • 3.2 Dispersion Studies
  • 3.2.1 Computational Fluid Dynamic Modeling of Flammable Gas Dispersion
  • 3.2.2 Computational Fluid Dynamic Modeling of Toxic Gas Dispersion
  • 3.2.3 Guidelines for the Selection of the Most Suitable Modeling Strategy
  • 3.3 Fire Studies
  • 3.3.1 Computations Fluid Dynamic Modeling of Dynamic Fire Scenarios
  • 3.3.2 Assessment of Domino Effect Triggered by Fire
  • 3.4 Explosion Studies
  • 4. CONCLUSIONS
  • REFERENCES
  • 10 - Computational Fluid Dynamics Modeling: Tutorial and Examples
  • 1. INTRODUCTION
  • 2. METHODOLOGY TUTORIAL
  • 3. APPLICATION OF THE APPROACH
  • 3.1 Description of the Case Study
  • 3.2 Simulation Settings
  • 3.2.1 Computational Fluid Dynamics Model
  • 3.2.2 Integral Models
  • 3.3 Results and Discussion
  • 4. CONCLUSIONS
  • REFERENCES
  • 11 - Assessing the Severity of Runaway Reactions
  • 1. INTRODUCTION
  • 2. SAFETY MEASURES FOR RUNAWAY REACTIONS
  • 3. ANALYSIS OF RISKS RELATED TO RUNAWAY REACTIONS
  • 4. DYNAMIC METHOD
  • 5. CONCLUSIONS.
  • REFERENCES
  • 12 - Dynamic Assessment of Runaway Reaction Risk: Tutorial and Examples
  • 1. INTRODUCTION
  • 2. METHODOLOGY TUTORIAL
  • 2.1 Prerequirements
  • 2.2 Steps 1 and 2: Normal Operating Conditions
  • 2.3 Steps 3 to 6: Runaway Reaction
  • 3. RESULTS
  • 4. DISCUSSION
  • 5. CONCLUSIONS
  • REFERENCES
  • 2.4 - Establishing the Risk Picture
  • 13 - Risk Metrics and Dynamic Risk Visualization
  • 1. INTRODUCTION
  • 2. TRADITIONAL RISK METRICS
  • 2.1 Limitations of Traditional Risk Metrics
  • 3. DYNAMIC RISK VISUALIZATION
  • 3.1 Risk Visualization Elements
  • 3.1.1 Risk Barometer
  • 3.1.2 Risk Trend
  • 3.1.3 Area Risk Comparison
  • 3.2 Drill-down Capability
  • 3.2.1 Top Risk Contributors
  • 3.2.2 Barrier Level
  • 3.2.3 Indicator Level
  • 4. CONCLUSIONS
  • REFERENCES
  • III - Interaction With Parallel Disciplines
  • 3.1 - Humans
  • 14 - Human Reliability Analysis: from the Nuclear to the Petroleum Sector
  • 1. INTRODUCTION
  • 2. BASIC CONCEPTS
  • 2.1 The Probabilistic Risk Assessment Framework
  • 2.2 Human Failure Probabilities: Data and Judgment
  • 2.3 Human Reliability Analysis Generations
  • 2.3.1 First Generation
  • 2.3.2 Second Generation
  • 2.4 Human Reliability Analysis Process and Practice
  • 3. REVIEW OF SELECTED HUMAN RELIABILITY ANALYSIS METHODS
  • 3.1 Technique for Human Error Rate Prediction
  • 3.1.1 Human Error Probabilities
  • 3.1.2 Process and Practice
  • 3.2 Human Error Assessment and Reduction Technique
  • 3.2.1 Human Error Probabilities
  • 3.2.2 Process and Practice
  • 3.3 A Technique for Human Event Analysis
  • 3.3.1 Human Error Probabilities
  • 3.3.2 Process and Practice
  • 3.4 Méthode d'Evaluation de la Réalisation des Missions Opérateur pour la Sûreté
  • 3.4.1 Human Error Probabilities
  • 3.4.2 Process and Practice
  • 4. HUMAN RELIABILITY ANALYSIS APPLICATION IN THE PETROLEUM SECTOR.
  • 4.1 Standardized Plant Analysis Risk-Human Reliability Analysis Method
  • 4.2 Petro-Human Reliability Analysis
  • 5. CONCLUSIONS
  • REFERENCES
  • 15 - Human Reliability Analysis in the Petroleum Industry: Tutorial and Examples
  • 1. INTRODUCTION
  • 2. METHODOLOGY TUTORIAL
  • 2.1 Step 1: Human Error Categorization
  • 2.2 Step 2: Performance-Shaping Factor Rating
  • 2.3 Step 3: Human Error Probability Calculation
  • 2.4 Step 4: Accounting for Dependence
  • 2.5 Step 5: Minimum Cut-off Value
  • 3. APPLICATION OF SPAR-H
  • 3.1 Drive-off of a Semisubmersible Drilling Unit
  • 3.2 Human Failure Event Identification and Modeling
  • 3.3 Human Error Probability Quantification
  • 4. CONCLUSIONS
  • REFERENCES
  • 3.2 - Costs and Benefits
  • 16 - Cost-Benefit Analysis of Safety Measures
  • 1. INTRODUCTION
  • 2. THE FOUNDATIONS OF COST-BENEFIT ANALYSIS
  • 2.1 Cost-Benefit Analysis Approach
  • 2.2 Present Value, Discount Rate, and Annuity
  • 2.3 Investment Analysis
  • 2.3.1 Internal Rate of Return
  • 2.3.2 Payback Period
  • 3. PREVENTION COSTS
  • 3.1 Safety Measures
  • 3.2 Categories of Safety Measure Costs
  • 4. HYPOTHETICAL BENEFITS: CATEGORIES OF AVOIDED ACCIDENT COSTS
  • 5. COST-BENEFIT ANALYSIS
  • 6. CONCLUSIONS
  • REFERENCES
  • 17 - Cost-Benefit Analysis for Low-Probability, High-Impact Risks: Tutorials and Examples
  • 1. INTRODUCTION
  • 2. COST-BENEFIT ANALYSIS BASED ON THE DISPROPORTION FACTOR
  • 2.1 Methodology Tutorial
  • 2.1.1 Step 1: Evaluate Cost of Failure
  • 2.1.2 Step 2: Evaluate Probability of Failure
  • 2.1.3 Step 3: Calculate Disproportion Factor
  • 2.1.4 Step 4: Calculate Maximum Justifiable Spend
  • 2.2 Application
  • 3. COST-BENEFIT ANALYSIS BASED ON MULTICRITERIA DECISION-MAKING
  • 3.1 Methodology Tutorial
  • 3.1.1 Step 1: Define the Decision Context
  • 3.1.2 Step 2: Identify All Safety Investment Alternatives.
  • 3.1.3 Step 3: Identify Objectives and Criteria.

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