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.

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.

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.

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.

A combination of two texts authored by Patrick Dunn, this set covers sensor technology as well as basic measurement and data analysis subjects, a combination not covered together in other references. Written for junior-level mechanical and aerospace engineering students, the topic coverage allows for flexible approaches to using the combination book in courses. MATLAB® applications are included in all sections of the combination, and concise, applied coverage of sensor technology is offered. Numerous chapter examples and problems are included, with complete solutions available.

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.

Risk Analysis in Engineering and Economics is required reading for decision making under conditions of uncertainty. The author describes the fundamental concepts, techniques, and applications of the subject in a style tailored to meet the needs of students and practitioners of engineering, science, economics, and finance. Drawing on his extensive e

Measurement and Data Analysis for Engineering and Science, Fourth Edition, provides up-to-date coverage of experimentation methods in science and engineering. This edition adds five new "concept chapters" to introduce major areas of experimentation generally before the topics are treated in detail, to make the text more accessible for undergraduate students. These feature Measurement System Components, Assessing Measurement System Performance, Setting Signal Sampling Conditions, Analyzing Experimental Results, and Reporting Experimental Results. More practical examples, case studies, and a variety of homework problems have been added; and MATLAB and Simulink resources have been updated.

The current book, Advanced Fluid Mechanics and Heat Transfer is based on author's four decades of industrial and academic research in the area of thermofluid sciences including fluid mechanics, aero-thermodynamics, heat transfer and their applications to engineering systems. Fluid mechanics and heat transfer are inextricably intertwined and both are two integral parts of one physical discipline. No problem from fluid mechanics that requires the calculation of the temperature can be solved using the system of Navier-Stokes and continuity equations only. Conversely, no heat transfer problem can be solved using the energy equation only without using the Navier-Stokes and continuity equations. The fact that there is no book treating this physical discipline as a unified subject in a single book that considers the need of the engineering and physics community, motivated the author to write this book. It is primarily aimed at students of engineering, physics and those practicing professionals who perform aero-thermo-heat transfer design tasks in the industry and would like to deepen their knowledge in this area. The contents of this new book covers the material required in Fluid Mechanics and Heat Transfer Graduate Core Courses in the US universities. It also covers the major parts of the Ph.D-level elective courses Advanced Fluid Mechanics and Heat Transfer that the author has been teaching at Texas A&M University for the past three decades.

Presenting the fundamental tools of experimentation that are currently used by engineers and scientists, Measurement and Data Analysis for Engineering and Science, Second Edition covers the basics of experimentation, hardware of experiments, and methods of data analysis. It also offers historical perspectives throughout. Updating and reorganizing its popular predecessor, this second edition makes the text much easier to follow and enhances the presentation with electronic material. New to the Second Edition Order of chapters now reflects the sequence of topics usually included in an undergraduate course Asterisked sections denote material not typically covered formally during lecture in an introductory undergraduate course More than 150 new problems, bringing the total to over 420 problems Supplementary website that provides unit conversions, learning objectives, review crossword puzzles and solutions, differential equation derivations, laboratory exercise descriptions, MATLAB® sidebars with M-files, and homework data files Thorough and up to date, this edition continues to help students gain a fundamental understanding of the tools of experimentation. It discusses basic concepts related to experiments, measurement system components and responses, data analysis, and effective communication of experimental findings. Ancillary materials for instructors are available on a CD-ROM and a solutions manual is available for qualifying instructors. More data available on www.nd.edu/~pdunn/www.text/measurements.html