Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title UNCERTAINTY, RELIABILITY AND RISK 1
Code ENGG304
Coordinator Dr E Patelli
Civil Engineering and Industrial Design
Edoardo.Patelli@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2018-19 Level 6 FHEQ Second Semester 7.5

Aims

This module develops understanding and appreciation of uncertainties in engineering on a basic level. It involves the qualitative analysis of the uncertainty and risks in engineering systems in view of engineering decision making under uncertainty.

Particular focus is on the quantification of the uncertainty, reliability analyis and simulation techniques as well associated concepts for code-compliant verification and design. The methods shown in the module have a general applicability, which is demonstrated by examples and practical applications.


Learning Outcomes

Students will understand the importance of Risk Analysis in Engineering

Students will learn how to quantify the effect of uncertainty by means analytical and simulation methods.

Student will understand how risk and uncertainty can be managed effectively

Students will acquire knowledge of the theoretical elements of risk and uncertainty

Syllabus
1 

Introduction to Risk

  • Definition of Risk
  • Effect of Uncertainties
  • Risk communication
  • Challenges in Engineering
  • Design under uncertainty

< span class="a4_UbAoOiS0UC74KlUE_3">Qualitative Risk Assessment

  • Hazard and operability study
  • Failure mode effects and criticality analysis
  • Event Tree and Fault Tree
  • ALARP approach

Uncertainty Modelling for Engineers:
  • Event structures, probability structures and basic operations 
  • Random variables and common distributions for random variables in engineering
  • Expected values and moments of distribution
  • Statistical inference
  • Bayesian Approaches

Probabilistic Methods for Engineering Applications

  • Analytical and approximate approaches
  • Markov Chain
Monte Carlo simulation with application
  • Basic concepts of scientific computing
  • Sampling for different distribution 
  • Variance reduction methods
  • Matlab implementation
Engineering applications from different fields

Teaching and Learning Strategies

Lecture - Standard lectures

2 hours per week

Tutorial - Solution of simple examples

Other - Computer Lab - Implementation of simple computer codes for Monte Carlo simulation

Seminar - Risk Analysis and Uncertainty quantification methods in Industry


Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 14
Standard lectures
2
Risk Analysis and Uncertainty quantification methods in Industry
6
Solution of simple examples
    2
Computer Lab - Implementation of simple computer codes for Monte Carlo simulation
24
Timetable (if known) 2 hours per week
  		           
Private Study 51
TOTAL HOURS 75

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Unseen Written Exam  2 hours  End of semester 2  100  No reassessment opportunity    Written Exam There is no reassessment opportunity, Final year of (BEng) degree programme. Reassessment is available at the next academic session. Notes (applying to all assessments) written exam  
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
Explanation of Reading List: