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Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition (Hardcover, 4th Edition)
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Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition (Hardcover, 4th Edition)
Expected to ship within 12 - 17 working days
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Helps engineers and scientists assess and manage uncertainty at all
stages of experimentation and validation of simulations Fully
updated from its previous edition, Experimentation, Validation, and
Uncertainty Analysis for Engineers, Fourth Edition includes
expanded coverage and new examples of applying the Monte Carlo
Method (MCM) in performing uncertainty analyses. Presenting the
current, internationally accepted methodology from ISO, ANSI, and
ASME standards for propagating uncertainties using both the MCM and
the Taylor Series Method (TSM), it provides a logical approach to
experimentation and validation through the application of
uncertainty analysis in the planning, design, construction,
debugging, execution, data analysis, and reporting phases of
experimental and validation programs. It also illustrates how to
use a spreadsheet approach to apply the MCM and the TSM, based on
the authors' experience in applying uncertainty analysis in
complex, large-scale testing of real engineering systems.
Experimentation, Validation, and Uncertainty Analysis for
Engineers, Fourth Edition includes examples throughout, contains
end of chapter problems, and is accompanied by the authors' website
www.uncertainty-analysis.com. Guides readers through all aspects of
experimentation, validation, and uncertainty analysis Emphasizes
the use of the Monte Carlo Method in performing uncertainty
analysis Includes complete new examples throughout Features
workable problems at the end of chapters Experimentation,
Validation, and Uncertainty Analysis for Engineers, Fourth Edition
is an ideal text and guide for researchers, engineers, and graduate
and senior undergraduate students in engineering and science
disciplines. Knowledge of the material in this Fourth Edition is a
must for those involved in executing or managing experimental
programs or validating models and simulations.
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