Uncertainty Analysis for Engineers and Scientists

A Practical Guide

AvFaith A. Morrison

Häftad, Engelska, 2021

583 kr

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Beskrivning

Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.

Produktinformation

Utgivningsdatum:2021-01-07
Mått:230 x 150 x 20 mm
Vikt:550 g
Format:Häftad
Språk:Engelska
Antal sidor:390
Förlag:Cambridge University Press
ISBN:9781108745741

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Mer om författaren

Faith A. Morrison is Professor of Chemical Engineering at Michigan Technological University. She is the author of An Introduction to Fluid Mechanics (Cambridge, 2013). She is a fellow of the Society of Rheology, member of the Dean's Teaching Showcase (2019), and was a board member of the American Institute of Physics.

Recensioner i media

'This book would be an ideal text for an introductory uncertainty analysis course in any engineering discipline. It offers an excellent mix of theory and practice, with numerous engineering examples (using both Excel and MATLAB®) on every topic discussed. It also provides a large number of problems at the end of each chapter, something I find to be relatively uncommon among similar texts.' Jake Blanchard, University of Wisconsin, Madison

Innehållsförteckning

1. Introduction and definitions; 2. Quick start: replicate error basics; 3. Reading error; 4. Calibration error; 5. Error propagation; 6. Model fitting.