Last modified: 23 Jul 2024 11:00
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 |
|---|---|---|---|
| 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.
| Assessment Type | Summative | Weighting | 25 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Generic individual feedback given. |
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| Knowledge Level | Thinking Skill | Outcome |
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| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Individual feedback given if requested. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Assessment Type | Summative | Weighting | 25 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
An additional 30mins to upload files |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
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| Factual | Remember | ILO’s for this course are available in the course guide. |
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