Experimentation, Validation, and Uncertainty Analysis for Engineers 3rd Edition

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ISBN-13: 978-0470168882
ISBN-10: 0470168889
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Editorial Reviews


"…present a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, and reporting phases of experimental and validation programs." (Book News, August 2009)

About the Author

Hugh W. Coleman, PhD, PE, is a Professor of Mechanical and Aerospace Engineering at the University of Alabama in Huntsville. W. GLENN STEELE, PhD, PE, is a Giles Distinguished Professor and the Bobby Shackouls Professor of Mechanical Engineering at Mississippi State University.

Coleman and Steele received the prestigious AIAA Ground Testing Award for "pioneering efforts in experimental uncertainty analysis with significant methodology advances and effective dissemination of knowledge through a straightforward engineering approach in their text and short course." They have served on experimental uncertainty and validation standards committees associated with ASME, AIAA, SAE, ISO, and NATO AGARD. They are both Fellows of ASME and Associate Fellows of AIAA.


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Product Details

  • Hardcover: 336 pages
  • Publisher: Wiley; 3 edition (July 27, 2009)
  • Language: English
  • ISBN-10: 0470168889
  • ISBN-13: 978-0470168882
  • Product Dimensions: 6.4 x 0.8 x 9.6 inches
  • Shipping Weight: 1.3 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #338,932 in Books (See Top 100 in Books)

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2 of 2 people found the following review helpful By Tom on March 14, 2011
Format: Hardcover Verified Purchase
The other reviewer's comment is true but irrelevant. It is a pretty boring read, but the fact is, if your instructor uses this text, then you have to use this text. Also, this is one of THE definitive texts on the subject. The text begins with methods of statistical analysis for the use in uncertainty analysis. It describes the methods for modeling and simulating error propagation (Monte Carlo Method, and Taylor Series Method), and methods to incorporate uncertainty analysis into the planning phases of experiments. It then moves into how to conduct a detailed uncertainty analysis of a major experimentation efforts.

When an engineer is presented with data, the first question he or she should ask is how good is the data. This book provides the reader with the tools needed to be able to determine a degree of goodness to a set of data.

I'd give 5 stars, but the book's too expensive. That's my only legitimate gripe about this book... but then again, there might be a reason this is the most expensive text on the subject.
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Experimentation, Validation, and Uncertainty Analysis for Engineers
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