Probabilistic Risk Assessment And Management 3-Day Course

Course Description

The 3-day course includes an Introduction and basic definitions of risk; Elements of risk assessment; Probabilistic risk assessment that involves logic modeling and treatment of dependent failures; Performance assessment and data modeling; Uncertainty analysis that covers types, measures and propagation methods of uncertainty; Importance measures of the risk; Risk acceptance and representation of risk; Decision making techniques using risk information and risk communication.

Who Should Take the Course

This course is designed for practitioners of risk analysis and presents an engineering approach to the probabilistic risk assessment. The target audience should have basic understanding of probability, statistics and engineering at senior undergraduate level. The course assumes no knowledge of risk analysis and provides necessary engineering foundation.

What the Student Will Learn

In this course the student will learn about the three primary components of Risk analysis namely, risk assessment, risk management and risk communication. The course provides methods for comprehensive probabilistic risk studies, including formal decision techniques for risk management. The course also has a special emphasis on treatment of uncertainties in the model and parameters used in the analysis as a critical part of any PRA practice. Topics are further clarified using practical examples of engineering systems.

Included Materials

Attendees will receive course handouts.

Required Materials

Attendees should bring a scientific calculator. Recommended: "Risk Analysis in Engineering, Techniques, Tools and Trends," M. Modarres, CRC Press.

Course Outline

Day One

1. Introduction and Basic Definitions
• Importance of Risk and Performance Analysis
• Elements and Types of Risk Analysis
• Risk Assessment
• Risk Management
• Risk Communication
2. Elements of Risk Assessment
• Type of Risk Assessment
• Risk, Hazard, Performance and Engineering Risk Assessment
3. Probabilistic Risk Assessment
• Steps in Conducting a Probabilistic Risk Assessment
• Strength of PRA
• Scenario and Logic Modeling, Development and Quantification
• Modeling of Dependent Failures in Risk Assessment
• A Simple Example of PRA

Day Two

1. Performance Assessment: Data and Modeling
• Active Hardware Performance Assessment
• Statistical Data Analysis for Repairable Hardware
• Availability as a Measure of Performance for Repairable Hardware Items
• Classical Parameter Estimation of Distribution Models for Performance Assessment of Hardware
• Bayesian Parameter Estimation of Distribution Models
• Physics of Failure Modeling
• Software Performance Assessment
• Human Reliability Analysis
• Expert Opinion in Risk Assessment and Performance Assessment
2. Uncertainty Analysis
• Types of Uncertainty
• Measures of Uncertainty
• Uncertainty Propagation Methods
• Comparison of Uncertainty Propagation Methods
• Graphic Representation of Uncertainty
3. Identifying, Ranking and Predicting Contributors to Risk
• Importance Ranking in Probabilistic Risk Assessment
• Importance Measures in Success Space
• A Comprehensive Example of Importance Measure Application
• Consideration of Uncertainties in Importance Measures Used for Risk-Based Ranking
• Uncertainty Importance Measures
• Precursor Analysis

Day Three

1. Representation of Risk Values and Risk Acceptance Criteria
• Representation of Risk Results
• Human Health and Safety Risk Acceptance Criteria
• Economic Risk and Performance Acceptance Criteria
2. Decision Making Techniques Using Risk Information
• Economic Methods in Risk Analysis
• Non-Economic Techniques
3. Risk Communication
• Forms of Communication
• The Basic Rules of Risk Communication
• Elements of Effective Risk Communication
• Characteristics of an Effective Risk Communication
• Risk Perception