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Informationen zum Autor Editors: Etienne de Rocquigny, Electricite de France, R&D (Senior Research Fellow). Nicolas Devictor, Commissariat a l'Energie Atomique. Stefano Tarantola, J.R.C. Ispra. Authors: The 10 members of the Uncertainty Project Group, part of ESReDA: European Safety, Reliability and Data Association. Klappentext 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. Zusammenfassung There is a growing demand from institutional bodies for the justification of industrial methodologies and practices (e.g. safety criteria, environmental protection and control, maintenance and design optimization). Previous books in this area have either been too theoretical, or too specific in their scope. Inhaltsverzeichnis Preface xiii Contributors and Acknowledgements xv Introduction xvii Notation - Acronyms and abbreviations xxi Part I Common Methodological Framework 1 1 Introducing the common methodological framework 3 1.1 Quantitative uncertainty assessment in industrial practice: a wide variety of contexts 3 1.2 Key generic features, notation and concepts 4 1.2.1 Pre-existing model, variables of interest and uncertain/fixed inputs 4 1.2.2 Main goals of the uncertainty assessment 6 1.2.3 Measures of uncertainty and quantities of interest 7 1.2.4 Feedback process 9 1.2.5 Uncertainty modelling 10 1.2.6 Propagation and sensitivity analysis processes 10 1.3 The common conceptual framework 11 1.4 Using probabilistic frameworks in uncertainty quantification - preliminary comments 13 1.4.1 Standard probabilistic setting and interpretations 13 1.4.2 More elaborate level-2 settings and interpretations 14 1.5 Concluding remarks 17 References 18 2 Positioning of the case studies 21 2.1 Main study characteristics to be specified in line with the common framework 21 2...
