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Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management

ISBN: 978-0-470-99447-4
364 pages
June 2008
Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management (0470994479) cover image


Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledging industrial constraints. The approach presented can be applied to a range of different business contexts, from research or early design through to certification or in-service processes. The authors aim to foster optimal trade-offs between literature-referenced methodologies and the simplified approaches often inevitable in practice, owing to data, time or budget limitations of technical decision-makers.

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.

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Table of Contents


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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Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management (US $133.00)

-and- Modelling Under Risk and Uncertainty: An Introduction to Statistical, Phenomenological and Computational Methods (US $123.00)

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