Spring 2024

NPRE 561: Advanced Risk Analysis for Technological Systems

Fall 2022

NPRE 461: Probabilistic Risk Assessment

Fall 2021

NPRE 461: Probabilistic Risk Assessment

NPRE461_Fall 2021_Course Flyer

Spring 2021

NPRE 561: Advanced Risk Analysis for Technological Systems

NPRE_561_Spring2021_Flyer

Spring 2020

NPRE 561: Advanced Risk Analysis for Technological Systems

NPRE 561_Spring 2020_Advanced Risk Analysis_Flyer

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

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

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

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.

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

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

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.

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

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.

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

Location: 106B6 Engineering Hall

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:

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

[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).

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

[View Fall 2015 Flyer]

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

[View Course Flier]

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.

[Full Course Information]

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.