Книга Uncertainty in Industrial Practice - A Guide to Quantitative Uncertainty Management De Rocquigny

Uncertainty in Industrial Practice - A Guide to Quantitative Uncertainty Management

Автор: De Rocquigny
Език: Английски език
Корици: С твърди корици
Издател: John Wiley & Sons Inc
Наличност: Външен склад в ограничено количество
Изпращаме след 11-15 дни
142.55 278.81 лв
Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С твърди корици
Издадена
2008
страници
364
EAN
9780470994474
ISBN
0470994479
Enbook ID
04380306
Издател
Теглоt
660
Размери
160 x 235 x 25

Пълно описание

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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