Mathematics for Mechanical Engineers

Mathematics for Mechanical Engineers gives mechanical engineers convenient access to the essential problem solving tools that they use each day. It covers applications employed in many different facets of mechanical engineering, from basic through advanced, to ensure that you will easily find answers you need in this handy guide. For the engineer venturing out of familiar territory, the chapters cover fundamentals like physical constants, derivatives, integrals, Fourier transforms, Bessel functions, and Legendre functions. For the experts, it includes thorough sections on the more advanced topics of partial differential equations, approximation methods, and numerical methods, often used in applications. The guide reviews statistics for analyzing engineering data and making inferences, so professionals can extract useful information even with the presence of randomness and uncertainty. The convenient Mathematics for Mechanical Engineers is an indispensable summary of mathematics processes needed by engineers.

Science & Math

Cain, George

Coleman, Hugh W.

Steele, W. Glenn

Kreith, Frank

Ames, William F.

Tong, Y.L.

Kautz, Richard L.

Frangopol, Dan M.

Norton, Paul

Mathematics

CRC-Press

This Third Edition helps you assess and manage uncertainty at all stages of experimentation and validation of simulations In this greatly expanded Third Edition, the acclaimed Experimentation, Validation, and Uncertainty Analysis for Engineers guides readers through the concepts of experimental uncertainty analysis and the applications in validating models and simulations, solving problems experimentally, and characterizing the behavior of systems. This Third Edition presents the current, internationally accepted methodology from ISO, ANSI, and ASME standards to cover the planning, design, debugging, and execution phases of experiments. Cases in which the experimental result is determined only once or when the result is determined multiple times in a test are addressed and illustrated with examples from the authors' experience. The important practical cases in which multiple measured variables share correlated errors are discussed in detail, and strategies to take advantage of such effects in calibrations and comparative testing situations are presented. The methodology for determining uncertainty by Monte Carlo analysis is described in detail. Knowledge of the material in this Third Edition is a must for those involved in executing or managing experimental programs or validating models, codes, and simulations. Professionals and students in disciplines spanning the full range of engineering and science will find this book an essential guide.

Experimentation, Validation, and Uncertainty Analysis for Engineers

Research

wiley

The dramatic developments in the field of experimental uncertainty analysis over the last ten years have led to sweeping changes in applications, resulting in a new international experimental uncertainty standard. 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. Along with several new examples, this latest edition includes new material on: * The utilization of Uncertainty Magnification Factors (UMFs) and Uncertainty Percentage Contributions (UPCs) in the planning and early design phases of experiments * Refined procedures for accounting for the effects of correlated bias errors * Improved methods for accounting for the effects of asymmetric systematic uncertainties * The importance of (previously ignored) correlated random errors with an example illustrating how to account for them * Uncertainties in comparative testing * Uncertainties in the comparison of data and predictions (code validation) * Uncertainty analysis by direct Monte Carlo simulation * A new method to determine regression uncertainties that properly accounts for both random and systematic uncertainties With a step-by-step approach, engineering students as well as practicing professional engineers who analyze or design experiments will find Experimentation and Uncertainty Analysis for Engineers, Second Edition to be an invaluable reference tool.

Experimentation and Uncertainty Analysis for Engineers

Engineering & Transportation

Engineering

Wiley-Interscience

How to apply uncertainty analysis to experimentation. Describes how to incorporate uncertainty analysis into the planning, design, construction, debugging, execution, data analysis, and reporting stages of experimental programs. Estimation and propagation of both precision (random) errors and bias (fixed) errors are considered, as are procedures for handling small samples (which require use of the t-distribution), and practical cases in which bias errors in different variables are correlated. Treatment follows (and explains) the ANSI/ASME Standard on Measurement Uncertainty. Chapters 1 through 4 develop methodology for proper consideration of the uncertainty in measured variables and their propagation into the result of an experimantal program. Chapters 5 through 7 present additional considerations in the design of experiments, and illustrate application of the methods given in earlier chapters.

Mathematics for Mechanical Engineers gives mechanical engineers convenient access to the essential problem solving tools that they use each day. It covers applications employed in many different facets of mechanical engineering, from basic through advanced, to ensure that you will easily find answers you need in this handy guide. For the engineer venturing out of familiar territory, the chapters cover fundamentals like physical constants, derivatives, integrals, Fourier transforms, Bessel functions, and Legendre functions. For the experts, it includes thorough sections on the more advanced topics of partial differential equations, approximation methods, and numerical methods, often used in applications. The guide reviews statistics for analyzing engineering data and making inferences, so professionals can extract useful information even with the presence of randomness and uncertainty. The convenient Mathematics for Mechanical Engineers is an indispensable summary of mathematics processes needed by engineers.

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. <ul>
<li>Guides readers through all aspects of experimentation, validation, and uncertainty analysis</li> <li>Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis</li> <li>Includes complete new examples throughout</li> <li>Features workable problems at the end of chapters</li> </ul>
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.

See the best price to sell, buy, or rent books by Coleman, Hugh W.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Coleman, Hugh W.

See the best price to sell, buy, or rent books by Coleman, Hugh W.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Mathematics for Mechanical Engineers

Experimentation, Validation, and Uncertainty Analysis for Engineers

Experimentation and Uncertainty Analysis for Engineers

Experimentation and Uncertainty Analysis for Engineers

Mathematics for Mechanical Engineers

Experimentation, Validation, and Uncertainty Analysis for Engineers