UN 0701 – Engineering Risk and Reliability
For the most up-to-date Course Material and Information go to http://www.civil.uwaterloo.ca/watrisk/un0701.html
February 25 & 26, 2017
March 11 & 12, 2017
March 25 & 26, 2017
April 8 & 9, 2017
Durham College – Whitby Campus
1610 Champlain Avenue, Whitby, ON, L1N 6A7
Directions to Durham College Whitby Campus:
- Final date to Register – March 10, 2017
- Last day to Drop Course – March 10, 2017
Recordings – https://mcmaster.webex.com/
|23.03.2017||Posted Problem Set 3|
|09.03.2017||Posted revised version of Section 8 of course notes|
|09.03.2017||Posted Problem Set 2|
|27.02.2017||Posted modified version of Problem Set 1. Question 10 has been removed.|
|22.02.2017||Posted Problem Set 1.|
|22.02.2017||Posted data files to be used in the in-class exercises.|
The first session for Winter 2017 will be held on February 25 & 26 (Sat/Sun) in the Lecture Theatre at the Durham College Skills Training Centre in Whitby. The start time for the first day is 9:00 am.
NOTE: Please bring a copy of the course notes prior to the first session (either electronic or hard copy). Also, bring a laptop (with MS-Excel) to be used for the in-class exercises. Please review the accompanying tutorial if you are not familiar with MS-Excel.
This course presents a broad treatment of the subject of engineering decision, risk, and reliability. Emphasis is on
the modelling of engineering problems and evaluation of systems performance under conditions of uncertainty;
risk-based approach to life-cycle management of engineering systems;
systematic development of design criteria, explicitly taking into account the significance of uncertainty; and
logical framework for risk assessment and risk-benefit tradeoffs in decision making.
The necessary mathematical concepts are developed in the context of engineering problems. The main topics of discussion are: probability theory, statistical data analysis, component and system reliability concepts, time-dependent reliability analysis, computational methods, life-cycle optimization models and risk management in public policy.
The course is divided into eight separate modules delivered over four weekends: Course schedule (pdf 164 kb)
|Module 1: Fundamentals of Probability||February 25 (Saturday)|
|Module 2: Statistical Analysis||February 26 (Sunday)|
|Module 3: Functions of Random Variables||March 11 (Saturday)|
|Module 4: Repairable System Reliability||March 12 (Sunday)|
|Module 5: Uncertainty Analysis||March 25 (Saturday)|
|Module 6: Bayesian Reliability||March 26 (Sunday)|
|Module 7: System Reliability Analysis||April 8 (Saturday)|
|Module 8: Risk Ranking and Significance||April 9 (Sunday)|
Marking Scheme: Assignments 75%, Final Exam 25%
- Microsoft Excel (2007/2010) Tutorial (pdf 0.9 Mb)
Please submit the first problem set by the end of the March 25-26 session.
- Problem Set 3 – Due date: April 9, 2017
Please submit the third problem set by the end of the April 8-9 session.
- Problem Set 2 – Due Date: March 26, 2017
- Problem Set 1 (modified 27.02.2017) – Due date: March 12, 2017
Please submit the first problem set by the end of the March 11-12 session.
- Please download the following Excel data files to your laptop, memory stick, etc. to be used in the in-class exercises.
The main reference for the course will be the lecture notes. Additional references for the course are as follows:
- Any Probability and Statistics textbook used in an engineering program (typically at second year level).
- Ang, A.H-S. and W.H. Tang. 2006. Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering. John Wiley & Sons, New York.
- Benjamin, J.R. and C.A. Cornell. 1970. Probability, Statistics, and Decision for Civil Engineers. McGraw-Hill, New York.
- Fullwood, R.R. and R.E. Hall. 1988. Probabilistic Risk Assessment in the Nuclear Power Industry: Fundamentals & Applications. Pergamon Press, Oxford.
- McCormick, N.J. 1981. Reliability and Risk Analysis: Methods and Nuclear Power Applications. Academic Press, New York.
- Melchers, R.E. 1999. Structural Reliability Analysis and Prediction (2nd ed.). John Wiley & Sons, Chichester.