Last modified: 25 Sep 2019 09:58
The aim of this course is to understand and be able to carry out probabilistic modelling of uncertainty in engineering components and systems. Students will be able to obtain a good knowledge and understanding on random variables in probabilistic analysis and be able to carry out approximation and numerical schemes on components and systems.
Study Type | Postgraduate | Level | 5 |
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Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
Campus | Aberdeen | Sustained Study | No |
Co-ordinators |
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The course focuses on advanced modelling of random variables. All 3 levels of modelling are discussed with
emphasis on FORM and simulations. Extensive tutorials are provided to help students to obtain a good understanding of the subject.
The following modules will be covered in the course:
1. Convolution integral
2. First-order reliability methods (FORM).
3. FORM for non-normal variables.
4. Correlated variables.
5. Monte Carlo simulation techniques.
6. Safety factors in engineering design.
7. Introduction to systems analysis.
Information on contact teaching time is available from the course guide.
Assessment Type | Summative | Weighting | 10 | |
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Assessment Weeks | Feedback Weeks | |||
Feedback |
A short exam designed to test conceptual understanding. Generic and individual feedback given. |
Knowledge Level | Thinking Skill | Outcome |
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Assessment Type | Summative | Weighting | 10 | |
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Assessment Weeks | Feedback Weeks | |||
Feedback |
Generic and individual feedback given. |
Knowledge Level | Thinking Skill | Outcome |
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Assessment Type | Summative | Weighting | 80 | |
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Assessment Weeks | Feedback Weeks | |||
Feedback |
Individual feedback available on request. |
Knowledge Level | Thinking Skill | Outcome |
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There are no assessments for this course.
Assessment Type | Summative | Weighting | ||
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Assessment Weeks | Feedback Weeks | |||
Feedback |
Knowledge Level | Thinking Skill | Outcome |
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Knowledge Level | Thinking Skill | Outcome |
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