# Fall 2019

## NPRE 461: Probabilistic Risk Assessment

# Spring 2019

## NPRE 498/598: Advanced Risk Analysis

**Credit:** 3 undergraduate hours, 4 graduate hours.

**Prerequisite****:** NPRE 498 Probabilistic Risk Assessment or Permission of the Instructor

**Meeting Schedule/Contact Hours****: **Tu. and Th. 1:30 -3:20pm; Fall 2015

**Location: **100H Talbot Laboratory

**Introduction:** It covers advanced topics of Probabilistic Risk Assessment

and Management such as: Fundamental Theories of Risk Modeling, Risk Scenario Development, Precursor Analysis, Uncertainty Modeling, Common Cause Failures, Bayesian Analysis, Human Reliability Analysis, Expert Elicitation and Aggregation, Next Generation PRA Methods and Tools, Probabilistic Physics of Failure, Risk Communication, Homogeneous & Non-Homogeneous Data Analysis, Risk-Informed Regulation

**Undergraduate Grading: **Homework (35%), Midterm exam (30%,), Final exam (35%), Term Project (optional; for extra credit).** ****Graduate Grading: **Homework (20%), Midterm exam (20%), Final exam (25%), Term project (35%).

** ****Reading Materials**

** **A set of slides, reports, and articles:

- Modarres, M., 2006,
*Risk Analysis in Engineering: Techniques, Tools, and Trends*, Taylor & Francis - Bedford, T., Cooke, R., 2001,
*Probabilistic Risk Analysis: Foundations and Methods*, Cambridge University Press

# Fall 2018

## NPRE 461: Probabilistic Risk Assessment

**Credit:** 3 undergraduate hours, 4 graduate hours.

** This course is now counted as a Technical Elective in several departments*

**Prerequisite****: **Junior, senior, or graduate standing in any engineering discipline, or consent of instructor (This course is a prerequisite for a 500-level advanced risk analysis course that is offered every Fall).

**Meeting Schedule/Contact Hours****: **MWF 10:00AM – 10:50AM; Spring 2017

**Introduction: **This course surveys multidisciplinary issues of risk, safety, and reliability of complex systems. It encompasses state-of-the-art methodologies in Probabilistic Risk Assessment. Topics include:

- Probability and Statistics for Risk Analysis
- Systematic Risk Scenario Modeling
- Hardware Reliability Modeling in Risk Analysis
- Bayesian Analysis
- Uncertainty propagation
- Human Error Modeling in Risk Analysis
- Failure Causal Modeling
- Risk Importance Ranking
- Data Analytics
- Risk-Informed Regulation
- Treatment of Failure Dependencies

Software codes for risk analysis and reliability modeling will be utilized.

**Undergraduate Grading**: Homework (45%), Midterm exam (20%,), Final exam (35%), Term Project (optional; for extra credit). **Graduate Grading**: Homework (35%), Midterm exam (15%), Final exam (30%), Term project (15%), Computer Project (5%).

**Reading Materials:**

- Mohammad Modarres, Mark Kaminskiy, and Vasiliy Krivtsov, “Reliability Engineering and Risk Analysis-A Practical Guide (2nd edition)”, CRC Press Taylor & Francis Group, 2010.
- A set of notes, slides, reports, and articles

# Spring 2018

## NPRE 498/598: Advanced Risk Analysis

**Credit:** 3 undergraduate hours, 4 graduate hours.

**Prerequisite****:** NPRE 498 Probabilistic Risk Assessment or Permission of the Instructor

**Meeting Schedule/Contact Hours****: **Tu. and Th. 1:30 -3:20pm; Fall 2015

**Location: **100H Talbot Laboratory

**Introduction:** It covers advanced topics of Probabilistic Risk Assessment

and Management such as: Fundamental Theories of Risk Modeling, Risk Scenario Development, Precursor Analysis, Uncertainty Modeling, Common Cause Failures, Bayesian Analysis, Human Reliability Analysis, Expert Elicitation and Aggregation, Next Generation PRA Methods and Tools, Probabilistic Physics of Failure, Risk Communication, Homogeneous & Non-Homogeneous Data Analysis, Risk-Informed Regulation

**Undergraduate Grading: **Homework (35%), Midterm exam (30%,), Final exam (35%), Term Project (optional; for extra credit).** ****Graduate Grading: **Homework (20%), Midterm exam (20%), Final exam (25%), Term project (35%).

** ****Reading Materials**

** **A set of slides, reports, and articles:

- Modarres, M., 2006,
*Risk Analysis in Engineering: Techniques, Tools, and Trends*, Taylor & Francis - Bedford, T., Cooke, R., 2001,
*Probabilistic Risk Analysis: Foundations and Methods*, Cambridge University Press

# Fall 2017

## NPRE 461: Probabilistic Risk Assessment

**Credit:** 3 undergraduate hours, 4 graduate hours.

** This course is now counted as a Technical Elective in several departments*

**Prerequisite****: **Junior, senior, or graduate standing in any engineering discipline, or consent of instructor (This course is a prerequisite for a 500-level advanced risk analysis course that is offered every Fall).

**Meeting Schedule/Contact Hours****: **MWF 10:00AM – 10:50AM; Spring 2017

**Introduction: **This course surveys multidisciplinary issues of risk, safety, and reliability of complex systems. It encompasses state-of-the-art methodologies in Probabilistic Risk Assessment. Topics include:

- Probability and Statistics for Risk Analysis
- Systematic Risk Scenario Modeling
- Hardware Reliability Modeling in Risk Analysis
- Bayesian Analysis
- Uncertainty propagation
- Human Error Modeling in Risk Analysis
- Failure Causal Modeling
- Risk Importance Ranking
- Data Analytics
- Risk-Informed Regulation
- Treatment of Failure Dependencies

Software codes for risk analysis and reliability modeling will be utilized.

**Undergraduate Grading**: Homework (45%), Midterm exam (20%,), Final exam (35%), Term Project (optional; for extra credit). **Graduate Grading**: Homework (35%), Midterm exam (15%), Final exam (30%), Term project (15%), Computer Project (5%).

**Reading Materials:**

- Mohammad Modarres, Mark Kaminskiy, and Vasiliy Krivtsov, “Reliability Engineering and Risk Analysis-A Practical Guide (2nd edition)”, CRC Press Taylor & Francis Group, 2010.
- A set of notes, slides, reports, and articles

# Spring 2017

## NPRE 461: Probabilistic Risk Assessment

**Credit:** 3 undergraduate hours, 4 graduate hours.

** This course is now counted as a Technical Elective in several departments*

**Prerequisite****: **Junior, senior, or graduate standing in any engineering discipline, or consent of instructor (This course is a prerequisite for a 500-level advanced risk analysis course that is offered every Fall).

**Meeting Schedule/Contact Hours****: **MWF 10:00AM – 10:50AM; Spring 2017

**Introduction: **This course surveys multidisciplinary issues of risk, safety, and reliability of complex systems. It encompasses state-of-the-art methodologies in Probabilistic Risk Assessment. Topics include:

- Probability and Statistics for Risk Analysis
- Systematic Risk Scenario Modeling
- Hardware Reliability Modeling in Risk Analysis
- Bayesian Analysis
- Uncertainty propagation
- Human Error Modeling in Risk Analysis
- Failure Causal Modeling
- Risk Importance Ranking
- Data Analytics
- Risk-Informed Regulation
- Treatment of Failure Dependencies

Software codes for risk analysis and reliability modeling will be utilized.

**Undergraduate Grading**: Homework (45%), Midterm exam (20%,), Final exam (35%), Term Project (optional; for extra credit). **Graduate Grading**: Homework (35%), Midterm exam (15%), Final exam (30%), Term project (15%), Computer Project (5%).

**Reading Materials:**

- Mohammad Modarres, Mark Kaminskiy, and Vasiliy Krivtsov, “Reliability Engineering and Risk Analysis-A Practical Guide (2nd edition)”, CRC Press Taylor & Francis Group, 2010.
- A set of notes, slides, reports, and articles

# Fall 2016

## NPRE 498/598: Advanced Risk Analysis

**Credit:** 3 undergraduate hours, 4 graduate hours.

**Prerequisite****:** NPRE 498 Probabilistic Risk Assessment or Permission of the Instructor

**Meeting Schedule/Contact Hours****: **Tu. and Th. 1:30 -3:20pm; Fall 2015

**Location: **100H Talbot Laboratory

**Introduction:** It covers advanced topics of Probabilistic Risk Assessment

and Management such as: Fundamental Theories of Risk Modeling, Risk Scenario Development, Precursor Analysis, Uncertainty Modeling, Common Cause Failures, Bayesian Analysis, Human Reliability Analysis, Expert Elicitation and Aggregation, Next Generation PRA Methods and Tools, Probabilistic Physics of Failure, Risk Communication, Homogeneous & Non-Homogeneous Data Analysis, Risk-Informed Regulation

**Undergraduate Grading: **Homework (35%), Midterm exam (30%,), Final exam (35%), Term Project (optional; for extra credit).** ****Graduate Grading: **Homework (20%), Midterm exam (20%), Final exam (25%), Term project (35%).

** ****Reading Materials**

** **A set of slides, reports, and articles:

- Modarres, M., 2006,
*Risk Analysis in Engineering: Techniques, Tools, and Trends*, Taylor & Francis - Bedford, T., Cooke, R., 2001,
*Probabilistic Risk Analysis: Foundations and Methods*, Cambridge University Press

# Spring 2016

## NPRE 498: Probabilistic Risk Assessment

**Credit:** 3 undergraduate hours, 4 graduate hours.

**Prerequisite****: **Junior, senior, or graduate standing in any engineering discipline, or consent of instructor (This course is a prerequisite for a 500-level advanced risk analysis course that is offered every Fall).

**Meeting Schedule/Contact Hours****: **Tu. and Th. 12:30 – 1:50pm; Spring 2016

**Location: **106B6 Engineering Hall

**Introduction: **This course surveys multidisciplinary issues of risk, safety, and reliability of complex systems. It encompasses state-of-the-art methodologies in Probabilistic Risk Assessment. Topics include:

- Probability and Statistics for Risk Analysis
- Safety and Reliability Modeling
- Systematic Risk Scenario Modeling
- Availability Modeling for Repairable Systems
- Bayesian Updating
- Uncertainty propagation
- Human Error Modeling in Risk Analysis
- Failure Causal Modeling
- Risk Importance Ranking
- Data Analytics
- Probabilistic Physics of Failure
- Risk-Informed Regulation

Software codes for risk analysis, uncertainty treatment, and Bayesian analysis will be utilized.

**Undergraduate Grading**: Homework (45%), Midterm exam (15%,), Final exam (40%), Term Project (optional; for extra credit). **Graduate Grading**: Homework (35%), Midterm exam (15%), Final exam (35%), Term project (15%)

**Reading Materials:**

- A set of notes, slides, reports, and articles

[View Spring 2016 NPRE498 PRA Flyer]

# Fall 2015

## NPRE 498/598: Advanced Risk Analysis

**Credit:** 3 undergraduate hours, 4 graduate hours.

**Prerequisite****:** NPRE 498-PR1 Probabilistic Risk Assessment or NPRE 498-RA1 Intro to Socio-Technical Risk Analysis or CEE 491 or Permission of the Instructor.** **Graduate class standing.

**Meeting Schedule/Contact Hours****: **Tu. and Th. 1:30 -3:20pm; Fall 2015

**Location: **100H Talbot Laboratory

**Introduction: ** It offers a comprehensive and in-depth review of advanced methods for Probabilistic Risk Analysis (PRA). Topics include: Fundamental theories of risk modeling, Risk scenario development, Model uncertainty, Parameter uncertainty, Uncertainty propagation (e.g., Method of Moment, Monte Carlo), Bayesian updating, Data analysis, Hardware reliability, Human error modeling, Risk importance ranking, Precursor analysis, Expert elicitation and aggregation, and Next generation PRA methods and tools. Software codes for risk analysis, uncertainty treatment, and Bayesian analysis will be utilized. While the examples will primarily focus on the nuclear power domain, the course will also cover current advancements in risk analysis of other complex systems (e.g., space, aviation, oil and gas).

**Undergraduate Grading: **Homework (35%), Midterm exam (30%,), Final exam (35%), Term Project (optional; for extra credit).** ****Graduate Grading: **Homework (20%), Midterm exam (20%), Final exam (25%), Term project (35%).

** ****Reading Materials**

** **A set of notes, slides, reports, and articles:

- Modarres, M., 2006,
*Risk Analysis in Engineering: Techniques, Tools, and Trends*, Taylor & Francis - Bedford, T., Cooke, R., 2001,
*Probabilistic Risk Analysis: Foundations and Methods*, Cambridge University Press - Lee, J., McCormick, N. 2011,
*Risk and Safety Analysis of Nuclear Systems*, John Wiley& Sons

# Spring 2015

## NPRE 498: Probabilistic Risk Analysis

**Credit**: 3 Undergraduate hours, 4 Graduate hours.

**Meeting Schedule/Contact Hours**: Mon., Wed., Fri., 10:00 AM – 10:50 AM

**Prerequisite**: Recommended: STAT 400 or equivalent probability/statistics or consent of instructor

This course surveys multidisciplinary issues of risk, safety, and reliability of complex systems. It encompasses foundations of risk science and state-of-the-art methodologies in Probabilistic Risk Assessment, which provides input for risk-informed decision-making for design, operation, and regulatory oversight in a variety of fields including nuclear power plants, aviation, space, chemical processes, healthcare, and oil and gas industry. The course covers applications and practical insights to the essential component of decision-making under uncertainties associated with complex systems, particularly for undergraduate students interested in a career in the risk analysis field. Additionally, it will provide exposure to many cutting-edge and active research subjects for graduate students. Software codes for risk analysis, uncertainty treatment, and Bayesian analysis will be introduced and utilized for assignment. This course will be a prerequisite for a 500-level advanced risk analysis course to be offered in Fall of 2015.

**Course Topics:**

- Probability and statistics for risk analysis
- Systems risk scenario modeling
- Treatment of failure dependencies
- Uncertainty propagation
- Probabilistic physics of failure
- Human reliability analysis
- Failure causal modeling & Bayesian Belief Network applications in risk assessment
- Dynamic/simulation-based probabilistic risk assessment
- Risk importance ranking
- Data analytics

# Fall 2014

## NPRE 598: Probabilistic Risk Analysis

**Credit**: 4 graduate hours.

**Meeting Schedule/Contact Hours**: Tu. and Th. 2:00 -3:50pm

**Prerequisite**: Recommended: STAT 400 or equivalent probability/statistics

This course offers a comprehensive and in-depth review of advanced methods for Probabilistic Risk Analysis (PRA). Topics include: fundamental theories of risk modeling, risk scenario development, model uncertainty, parameter uncertainty, uncertainty propagation (e.g. Method of Moment, Monte Carlo), Bayesian updating, data analysis, hardware reliability, human error modeling, risk importance ranking, precursor analysis, expert elicitation and aggregation, and next generation PRA methods and tools. Risk analysis software will be used for homework and class projects. While the examples will primarily focus on the nuclear power domain, the course will also cover current advancements in risk analysis of other complex systems (e.g. space, aviation, oil and gas). Recommended Prerequisite: STAT 400 or equivalent probability/statistics course.

# Spring 2014

## Systems Reliability Modeling

Reliability analysis relates to the study of “how often” and “why” failures occur in order to *predict* and *prevent *the failures and, consequently, maximize systems performance and efficiently use their resources. This course covers fundamental theories and techniques for reliability analysis of complex engineering systems and their components, covering statistical models and probabilistic physics of failure approaches. Specific topics include: Why we study reliability; Probabilistic life models for mechanical/electrical components; Systems logic modeling; Reliability of repairable components and systems; Reliability data analysis; Bayesian methods in engineering; Uncertainty propagation; Reliability growth models; Dependent failure models; Stress-strength analysis & damage tolerance. RARE software will be used for homework problems drawn from the design and operation of nuclear and other industries.

# Fall 2013

## Introduction to Socio-Technical Risk Analysis

Survey of multidisciplinary issues of risk, safety, and reliability of nuclear power plans and other complex systems. Topics: technical and social risk-contribution factors and issues arising from their dynamic interactions; the advantages of integrating probabilistic and deteministic perspectives; probalistic risk assessment and managment; risk-informed decision-making for design, operation, and regulatory oversight; challenges of multi-dimensional risk evaluation considering diverse interrelated performance metrics (e.g. safety, cost, quality) of high-risk organizations; issues of risk communication; public risk perceptions; and risk acceptance criteria. While the examples will primarily focus on the nuclear power domain, the course will also cover current advancements in risk analysis of other socio-technical systems (e.g., space, oil and gas). Prerequisites: Jr or Sr or Graduate level standing in engineering.