Experimental Uncertainty Analysis A Textbook For Science And Engineering Students
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Experimental Uncertainty Analysis A Textbook For Science And Engineering Students
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Author : Supreet Singh Bahga
language : en
Publisher: Supreet Singh Bahga
Release Date : 2021-07-06
Experimental Uncertainty Analysis A Textbook For Science And Engineering Students written by Supreet Singh Bahga and has been published by Supreet Singh Bahga this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-06 with Technology & Engineering categories.
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.
Uncertainty Analysis For Engineers And Scientists
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Author : Faith A. Morrison
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-07
Uncertainty Analysis For Engineers And Scientists written by Faith A. Morrison and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with Computers categories.
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
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Author : John Robert Taylor
language : en
Publisher: Univ Science Books
Release Date : 1997-01-01
An Introduction To Error Analysis written by John Robert Taylor and has been published by Univ Science Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-01 with Mathematics categories.
Problems after each chapter
Uncertainty Quantification And Predictive Computational Science
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Author : Ryan G. McClarren
language : en
Publisher: Springer
Release Date : 2018-11-23
Uncertainty Quantification And Predictive Computational Science written by Ryan G. McClarren and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-23 with Science categories.
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.
An Introduction To Uncertainty In Measurement
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Author : L. Kirkup
language : en
Publisher: Cambridge University Press
Release Date : 2006-06-01
An Introduction To Uncertainty In Measurement written by L. Kirkup and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-01 with Science categories.
Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.
Measurement Uncertainty
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Author : Ronald H. Dieck
language : en
Publisher: ISA
Release Date : 2007
Measurement Uncertainty written by Ronald H. Dieck and has been published by ISA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
Literally an entire course between two covers, Measurement Uncertainty: Methods and Applications, Fourth Edition, presents engineering students with a comprehensive tutorial of measurement uncertainty methods in a logically categorized and readily utilized format. The new uncertainty technologies embodied in both U.S. and international standards have been incorporated into this text with a view toward understanding the strengths and weaknesses of both. The book is designed to also serve as a practical desk reference in situations that commonly confront an experimenter. The text presents the basics of the measurement uncertainty model, non-symmetrical systematic standard uncertainties, random standard uncertainties, the use of correlation, curve-fitting problems, and probability plotting, combining results from different test methods, calibration errors, and uncertainty propagation for both independent and dependent error sources. The author draws on years of experience in industry to direct special attention to the problem of developing confidence in uncertainty analysis results and using measurement uncertainty to select instrumentation systems.
Analysis Of Experimental Data In Science And Technology
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Author : Andrzej Zięba
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2023-09-26
Analysis Of Experimental Data In Science And Technology written by Andrzej Zięba and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-26 with Language Arts & Disciplines categories.
This textbook presents methods of data analysis and uncertainty estimation based on classical statistics whilst including the use of robust statistics, Monte Carlo modelling, informational criteria, and non-statistical methods. Related computer programs and their creative use are also discussed, without reference to specific packages. The book contains one hundred illustrations and numerous examples using real-world data, from a student lab to the latest scientific results. It will appeal to students, scientists, engineers, metrologists, and everyone interested in processing measurement results.
Planning And Executing Credible Experiments
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Author : Robert J. Moffat
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-19
Planning And Executing Credible Experiments written by Robert J. Moffat and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-19 with Technology & Engineering categories.
Covers experiment planning, execution, analysis, and reporting This single-source resource guides readers in planning and conducting credible experiments for engineering, science, industrial processes, agriculture, and business. The text takes experimenters all the way through conducting a high-impact experiment, from initial conception, through execution of the experiment, to a defensible final report. It prepares the reader to anticipate the choices faced during each stage. Filled with real-world examples from engineering science and industry, Planning and Executing Credible Experiments: A Guidebook for Engineering, Science, Industrial Processes, Agriculture, and Business offers chapters that challenge experimenters at each stage of planning and execution and emphasizes uncertainty analysis as a design tool in addition to its role for reporting results. Tested over decades at Stanford University and internationally, the text employs two powerful, free, open-source software tools: GOSSET to optimize experiment design, and R for statistical computing and graphics. A website accompanies the text, providing additional resources and software downloads. A comprehensive guide to experiment planning, execution, and analysis Leads from initial conception, through the experiment’s launch, to final report Prepares the reader to anticipate the choices faced throughout an experiment Hones the motivating question Employs principles and techniques from Design of Experiments (DoE) Selects experiment designs to obtain the most information from fewer experimental runs Offers chapters that propose questions that an experimenter will need to ask and answer during each stage of planning and execution Demonstrates how uncertainty analysis guides and strengthens each stage Includes examples from real-life industrial experiments Accompanied by a website hosting open-source software Planning and Executing Credible Experiments is an excellent resource for graduates and senior undergraduates—as well as professionals—across a wide variety of engineering disciplines.
Measurement Uncertainty
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Author : Simona Salicone
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-04
Measurement Uncertainty written by Simona Salicone and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-04 with Mathematics categories.
It is widely recognized, by the scienti?c and technical community that m- surements are the bridge between the empiric world and that of the abstract concepts and knowledge. In fact, measurements provide us the quantitative knowledge about things and phenomena. It is also widely recognized that the measurement result is capable of p- viding only incomplete information about the actual value of the measurand, that is, the quantity being measured. Therefore, a measurement result - comes useful, in any practicalsituation, only if a way is de?ned for estimating how incomplete is this information. The more recentdevelopment of measurement science has identi?ed in the uncertainty concept the most suitable way to quantify how incomplete is the information provided by a measurement result. However, the problem of how torepresentameasurementresulttogetherwithitsuncertaintyandpropagate measurementuncertaintyisstillanopentopicinthe?eldofmetrology,despite many contributions that have been published in the literature over the years. Many problems are in fact still unsolved, starting from the identi?cation of the best mathematical approach for representing incomplete knowledge. Currently, measurement uncertainty is treated in a purely probabilistic way, because the Theory of Probability has been considered the only available mathematical theory capable of handling incomplete information. However, this approach has the main drawback of requiring full compensation of any systematic e?ect that a?ects the measurement process. However, especially in many practical application, the identi?cation and compensation of all s- tematic e?ects is not always possible or cost e?ective.
Introductory Statistics And Random Phenomena
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Author : Manfred Denker
language : en
Publisher: Birkhäuser
Release Date : 2017-09-16
Introductory Statistics And Random Phenomena written by Manfred Denker and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-16 with Computers categories.
This textbook integrates traditional statistical data analysis with new computational experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in nonlinear dynamic systems. This was the first advanced text/reference to bring together such a comprehensive variety of tools for the study of random phenomena occurring in engineering and the natural, life, and social sciences. The crucial computer experiments are conducted using the readily available computer program Mathematica® Uncertain Virtual WorldsTM software packages which optimize and facilitate the simulation environment. Brief tutorials are included that explain how to use the Mathematica® programs for effective simulation and computer experiments. Large and original real-life data sets are introduced and analyzed as a model for independent study. This is an excellent classroom tool and self-study guide. The material is presented in a clear and accessible style providing numerous exercises and bibliographical notes suggesting further reading. Topics and Features Comprehensive and integrated treatment of uncertainty arising in engineering and scientific phenomena – algorithmic complexity, statistical independence, and nonlinear chaotic behavior Extensive exercise sets, examples, and Mathematica® computer experiments that reinforce concepts and algorithmic methods Thorough presentation of methods of data compression and representation Algorithmic approach to model selection and design of experiments Large data sets and 13 Mathematica®-based Uncertain Virtual WorldsTM programs and code This text is an excellent resource for all applied statisticians, engineers, and scientists who need to use modern statistical analysis methods to investigate and model their data. The present, softcover reprint is designed to make this classic textbook available to a wider audience.