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School of Chemical and Environmental Engineering

Now offering two distinct diplomas: Chemical Engineering and Environmental Engineering

Risk Analysis

1. COURSE INFORMATION:

School Chemical and Environmental Engineering
Course Level Undergraduate
Direction Environmental Engineering
Course ID ENVE 535 Semester 9th
Course Category Elective
Course Modules Instruction Hours per Week ECTS

Lectures and Tutorials

3
T=2, E=1, L=0

5
Course Type Scientific Area
Prerequisites  
Instruction/Exam Language Greek
The course is offered to Erasmus students No
Course URL https://www.eclass.tuc.gr/courses/MHPER225/

 

2. LEARNING OUTCOMES

Learning Outcomes

Upon successful completion of the course, the student will be able to:

  • Recall basic principles of statistics and data analysis and decision making
  • Recognize decision-making criteria and the concept of risk in project planning and management as well as the concept of cost/benefit analysis
  • Use appropriate software in decision-making
  • Assess environmental risk
  • Manage projects with environmental policy criteria
  • Analyze environmental data
General Competencies/Skills
  • Work in teams
  • Design and management of environmental engineering works/projects
  • Decision making
  • Review, analyze and synthesize data and information, with the use of necessary technologies

3. COURSE SYLLABUS

  1. Elements of probability and statistics, Bayes theorem, Discrete and Continuous Theoretical Probability Distributions, Statistical data analysis, Uncertainty of estimates.
  2. Decision trees. Extending the calculation of the cost of pollution by adding the loss of value of a good.
  3. Bayesian Decision Making Theory (prior and posterior distributions). Hazard and Bayesian optimal decision.
  4. Sensitivity analysis and influence of number of samples on decisions.
  5. Use of the loss function in promoting environmental policy. Economic value of information. Repentance and loss of opportunity.
  6. Correlation of risk and cost/benefit analysis.
  7. Environmental risk (pollutants and permissible exposure limits - practical applications).
  8. Risk analysis of hydrological projects and processes.
  9. Risk analysis using spatial analysis.
  10. Introduction to Game Theory for water resources management.
  11. The integration of data and qualitative information in decision-making.
  12. Decision-making criteria (minimax, maximin), applications in economic and environmental subjects.
  13. Presentation of Irrigania software for the application of non-fixed-sum game theory (decision-making) in water resources management.

4. INSTRUCTION and LEARNING METHODS - ASSESSMENT

Lecture Method Direct (face to face)

Use of Information and Communication Technology

  • Specialized software
  • Power point presentations
  • E-class support
Instruction Organisation Activity Workload per Semester
(hours)
- Lectures 28
- Tutorials 11
- Projects and 2 sets of exercises 51
- Autonomous study 35
Course Total 125

Assessment Method

I. Written final examination (50%).
- Theoretical problems with data to be resolved

ΙΙ. Autonomous assignments (20%).

III. Group assignments (30%).

5. RECOMMENDED READING

  • Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering ALFREDO H., ANG S., TANG W. H.
  • SYSTEMIC METHODOLOGY & TECHNICAL ECONOMY, PANAGIOTAKOPOULOS DIMITRIOS

6. INSTRUCTORS

Course Instructor: Professor P. Gikas (Faculty-ChEnvEng)
Lectures: New Scientist or PD407/80
Tutorial exercises: New Scientist or PD407/80
Laboratory Exercises: