Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management
Uncertainty in Industrial Practice:
- Features recent uncertainty case studies carried out in the nuclear, air & space, oil, mechanical and civil engineering industries set in a common methodological framework.
Presents methods for organizing and treating uncertainties in a generic and prioritized perspective.
- Illustrates practical difficulties and solutions encountered according to the level of complexity, information available and regulatory and financial constraints.
- Discusses best practice in uncertainty modeling, propagation and sensitivity analysis through a variety of statistical and numerical methods.
- Reviews recent standards, references and available software, providing an essential resource for engineers and risk analysts in a wide variety of industries.
This book provides a guide to dealing with quantitative uncertainty in engineering and modelling and is aimed at practitioners, including risk-industry regulators and academics wishing to develop industry-realistic methodologies.
Contributors and Acknowledgements.
Notation - Acronyms and abbreviations.
Part I: Common Methodological Framework.
1. Introducing the common methodological framework.
2. Positing of the case studies.
Part II: Case Studies.
3. CO2 emissions: estimating uncertainties in practice for power plants.
4. Hydrocarbon exploration: decision-support through uncertainty treatment.
5. Determination of the risk due to personal electronic devices (PEDs) carried out on radio-navigation systems aboard aircraft.
6. Safety assessment of a radioactive high-level waste repository - comparison of dose and peak dose.
7. A cash flow statistical model for airframe accessory maintenance contracts.
8. Uncertainty and reliability study of a creep law to assess the fuel cladding behaviour of PWR spent fuel assemblies during interim dry storage.
9. Radiological protection and maintenance.
10. Partial safety factors to deal with uncertainties in slope stability of river dykes.
11. Probabilistic assessment of fatigue life.
12. Reliability modelling in early design stages using the Dempster-Shafer theory of Evidence.
Part III: Methodological Review and Recommendations.
13. What does uncertainty management mean in an industrial context?
14. Uncertainty settings and natures uncertainty.
15. Overall approach.
16. Uncertainty modelling methods.
17. Uncertainty propagation methods.
18. Sensitivity analysis methods.
19. Presentation in a deterministic format.
20. Recommendations the overall process in practice.
Appendix A. A selection of codes and standards.
Appendix B. A selection of tools and websites.
Appendix C. Towards non-probabilistic settings: promises and industrial challenges.
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