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Experimental Uncertainty Analysis: A Textbook for Science and Engineering Students

Experimental Uncertainty Analysis: A Textbook for Science and Engineering Students
Author: Supreet Singh Bahga
Publisher: Supreet Singh Bahga
Total Pages: 186
Release: 2021-07-06
Genre: Technology & Engineering
ISBN: 1636402321

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Uncertainties are inevitable in any experimental measurement. Therefore, it is essential for science and engineering graduates to design and develop reliable experiments and estimate the uncertainty in the measurements. This book describes the methods and application of uncertainty analysis during the planning, data analysis, and reporting stages of an experiment. This book is aimed at postgraduate and advanced undergraduate students of various branches of science and engineering. The book teaches methods for estimating random and systematic uncertainties and combining them to determine the overall uncertainty in a measurement. In addition, the method for propagating measurement uncertainties in the calculated result is discussed. The book also discusses methods of reducing the uncertainties through proper instrumentation, data acquisition, and experiment planning. This book provides detailed background and assumptions underlying the uncertainty analysis techniques for the reader to understand their applicability. Various solved examples are provided to demonstrate the application of the uncertainty analysis techniques. The exercises at the end of the chapters have been chosen carefully to reinforce the concepts discussed in the text.


Experimentation and Uncertainty Analysis for Engineers

Experimentation and Uncertainty Analysis for Engineers
Author: Hugh W. Coleman
Publisher: John Wiley & Sons
Total Pages: 298
Release: 1999
Genre: Psychology
ISBN: 9780471121466

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Now, in the only manual available with direct applications to the design and analysis of engineering experiments, respected authors Hugh Coleman and Glenn Steele have thoroughly updated their bestselling title to include the new methodologies being used by the United States and International standards committee groups.


Experimentation, Validation, and Uncertainty Analysis for Engineers

Experimentation, Validation, and Uncertainty Analysis for Engineers
Author: Hugh W. Coleman
Publisher: John Wiley & Sons
Total Pages: 384
Release: 2018-05-08
Genre: Technology & Engineering
ISBN: 1119417511

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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.


Experimental Methods for Science and Engineering Students

Experimental Methods for Science and Engineering Students
Author: Les Kirkup
Publisher: Cambridge University Press
Total Pages: 239
Release: 2019-09-05
Genre: Science
ISBN: 1108418465

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An overview of experimental methods providing practical advice to students seeking guidance with their experimental work.


Uncertainty Analysis for Engineers and Scientists

Uncertainty Analysis for Engineers and Scientists
Author: Faith A. Morrison
Publisher: Cambridge University Press
Total Pages: 389
Release: 2021-01-07
Genre: Computers
ISBN: 1108478352

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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.


An Introduction to Error Analysis

An Introduction to Error Analysis
Author: John Robert Taylor
Publisher: Univ Science Books
Total Pages: 327
Release: 1997-01-01
Genre: Mathematics
ISBN: 9780935702422

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Problems after each chapter


Introduction to Engineering Experimentation

Introduction to Engineering Experimentation
Author: Anthony J. Wheeler
Publisher:
Total Pages: 472
Release: 2003
Genre: Science
ISBN:

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This text for an undergraduate junior or senior course covers the most common elements necessary to design, execute, analyze, and document an engineering experiment or measurement system and to specify instrumentation for a production process. In addition to descriptions of common measurement systems, the text covers computerized data acquisition systems, common statistical techniques, experimental uncertainty analysis, and guidelines for planning and documenting experiments. The authors are affiliated with the school of engineering at San Francisco State University. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com)


Doubt-Free Uncertainty In Measurement

Doubt-Free Uncertainty In Measurement
Author: Colin Ratcliffe
Publisher: Springer
Total Pages: 0
Release: 2016-09-22
Genre: Technology & Engineering
ISBN: 9783319364476

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This volume presents measurement uncertainty and uncertainty budgets in a form accessible to practicing engineers and engineering students from across a wide range of disciplines. The book gives a detailed explanation of the methods presented by NIST in the “GUM” – Guide to Uncertainty of Measurement. Emphasis is placed on explaining the background and meaning of the topics, while keeping the level of mathematics at the minimum level necessary. Dr. Colin Ratcliffe, USNA, and Bridget Ratcliffe, Johns Hopkins, develop uncertainty budgets and explain their use. In some examples, the budget may show a process is already adequate and where costs can be saved. In other examples, the budget may show the process is inadequate and needs improvement. The book demonstrates how uncertainty budgets help identify the most cost effective place to make changes. In addition, an extensive fully-worked case study leads readers through all issues related to an uncertainty analysis, including a variety of different types of uncertainty budgets. The book is ideal for professional engineers and students concerned with a broad range of measurement assurance challenges in applied sciences. This book also: Facilitates practicing engineers’ understanding of uncertainty budgets, essential to calculating cost-effective savings to a wide variety of processes contingent on measurement Presents uncertainty budgets in an accessible style suitable for all undergraduate STEM courses that include a laboratory component Provides a highly adaptable supplement to graduate textbooks for courses where students’ work includes reporting on experimental results Includes an expanded case study developing uncertainty from transducers though measurands and propagated to the final measurement that can be used as a template for the analysis of many processes Stands as a useful pocket reference for all engineers and experimental scientists


Uncertainty Analysis of Experimental Data with R

Uncertainty Analysis of Experimental Data with R
Author: BENJAMIN DAVID. SHAW
Publisher: CRC Press
Total Pages: 196
Release: 2020-06-30
Genre: Probabilities
ISBN: 9780367573393

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This book covers methods for evaluation of experimental data commonly encountered in science and engineering. Measurements of quantities that vary in a continuous fashion, cannot be measured exactly; it is of interest to be able to quantify these uncertainties. The book centers around using the (free) software package R.


Measurements and their Uncertainties

Measurements and their Uncertainties
Author: Ifan Hughes
Publisher: OUP Oxford
Total Pages: 152
Release: 2010-07-02
Genre: Science
ISBN: 0191576565

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This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.