Uncertainty in Industrial Practice: A Guide to Quantitative by Etienne de Rocquigny, Nicolas Devictor, Stefano Tarantola PDF

By Etienne de Rocquigny, Nicolas Devictor, Stefano Tarantola

ISBN-10: 0470770740

ISBN-13: 9780470770740

ISBN-10: 0470994479

ISBN-13: 9780470994474

Dealing with uncertainties in commercial platforms is a regular problem to make sure greater layout, strong operation, responsible functionality and responsive hazard regulate. Authored via a number one eu community of specialists representing a move component to industries, Uncertainty in commercial perform goals to supply a reference for the dissemination of uncertainty remedy in any kind of undefined. it's concerned about the quantification of uncertainties within the presence of knowledge, model(s) and data in regards to the procedure, and provides a technical contribution to decision-making strategies while acknowledging business constraints. The technique awarded might be utilized to a number diversified enterprise contexts, from learn or early layout via to certification or in-service approaches. The authors target to foster optimum trade-offs among literature-referenced methodologies and the simplified techniques frequently inevitable in perform, as a result of information, time or price range boundaries of technical decision-makers.

Uncertainty in business perform:

  • Features contemporary uncertainty case reports performed within the nuclear, air & house, oil, mechanical and civil engineering industries set in a typical methodological framework.
  • provides tools for organizing and treating uncertainties in a usual and prioritized viewpoint.

  • Illustrates useful problems and suggestions encountered based on the extent of complexity, details on hand and regulatory and fiscal constraints.
  • Discusses top perform in uncertainty modeling, propagation and sensitivity research via numerous statistical and numerical equipment.
  • Reviews fresh criteria, references and to be had software program, supplying a necessary source for engineers and danger analysts in a large choice of industries.

This e-book offers a advisor to facing quantitative uncertainty in engineering and modelling and is aimed toward practitioners, together with risk-industry regulators and teachers wishing to advance industry-realistic methodologies.

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Additional resources for Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management

Example text

E. to reach an acceptable quality level for its use. This may involve calibrating sensors, estimating the parameters of the model inputs, simplifying the system model physics or structure, fixing some model inputs, and finally validating according to a context-dependent level. S (Select): To compare relative performance and optimize the choice of maintenance policy, operation or design of the system. g. nuclear or environmental licensing, aeronautical certification, etc). There may be several goals in any given study and they may be combined over the course of a more-or-less elaborate decision-making process.

Alternative representations of epistemic uncertainty, Special Issue of Reliability Engineering & System Safety, 85(1–3). D. and Saltelli, A. (2006) (Eds) Sensitivity Analysis of Model Output: SAMO 2004, Special Issue of Reliability Engineering & System Safety, 91(10–11). ), European Prestandard Env. 13005. J. (1981) On The Quantitative Definition of Risk, Risk Analysis, 1(1), 11–27. H. (1921) Risk, Uncertainty and Profit, Hart, Schaffner & Marx. M. D. (2000) Simulation Modelling and Analysis (3rd edition), London: McGraw Hill.

Treatment of Aleatory and Epistemic Uncertainty, Special Issue of Reliability Engineering & System Safety, 54(2–3). C. and Oberkampf, W. ) Alternative representations of epistemic uncertainty, Special Issue of Reliability Engineering & System Safety, 85(1–3). D. and Saltelli, A. (2006) (Eds) Sensitivity Analysis of Model Output: SAMO 2004, Special Issue of Reliability Engineering & System Safety, 91(10–11). ), European Prestandard Env. 13005. J. (1981) On The Quantitative Definition of Risk, Risk Analysis, 1(1), 11–27.

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Uncertainty in Industrial Practice: A Guide to Quantitative Uncertainty Management by Etienne de Rocquigny, Nicolas Devictor, Stefano Tarantola


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