Experimentation, Validation, and Uncertainty Analysis for Engineers

Abstract

This book reveals to practitioner engineers and technicians involved in experimentation, modeling, and simulation, an approach based on uncertainty analysis concepts for the validation of simulation processes. This new edition incorporates new material: two methods for uncertainty propagation evaluation (Taylor Series Method, TSM, and the Monte Carlo Method, MCM) and a new chapter on "Validation of Simulations", where the contribution of the authors to the new ASME "Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer" V& V20-2009 is presented. The topic of uncertainty evaluation follows the ISO Guide: "Evaluation of Measurement Data-Supplement 1 to the "Guide to the expression of the uncertainty in Measurement"-Propagation of Distributions Using a Monte Carlo Method".The first chapter traces the leading line of the book, by detailing the importance of the uncertainty evaluation from the early stages of experiment planning through the validation of the simulations. The important definitions, the basic concepts of random and systematic errors and of measurement uncertainty are introduced, and the goal of the validation of simulations by quantitative evaluations is presented. Chapter 2 introduces the statistical distributions most encountered in uncertainty analysis, the estimators for their parameters, the confidence intervals for the mean value, and the Chauvenet's criterion for rejection of outliers from a sample. Finally, the uncertainty of one measured variable is evaluated using both TSM and MCM. Additional exercises are proposed at the end of this and every chapter.Chapter 3 continues the topic of the evaluation of the measurement uncertainty for the multivariate parameters using the TSM and MCM. For the TSM, an extrapolation of the relation of composing partial uncertainties for the limits of the confidence intervals is deduced for particular cases. The authors are unclear here because this can confuse some readers, as the relation may be seen as a method of composing confidence intervals deriving from different distributions-which has no mathematical justification. The advantage of the MCM method in evaluation of the uncertainty intervals when the uncertainty values are large and the resulting distribution is skewed is discussed through examples, along with the method of determination of the confidence intervals.Chapter 4 deals with application of the uncertainty analysis in experiment planning and validation. Through comparative, detailed examples, the uncertainty analysis is presented as a decision element in the method selection and for adjustments of experiments in the planning phase. The need of considering the domain of values of the variables and their evolving uncertainty values is discussed. The authors give advice to avoid pitfalls related to interpretation of specifications. In comparing the experimental techniques, the use of the uncertainty magnification factors and the uncertainty percentage contribution is recommended for decision making process.The fift...

Thermal management of GaN HEMT devices using serpentine minichannel heat sinks

“…The ASME standard [38] and the Root-Sum-Square (RSS) method described by Coleman and Steele [39] were used to estimate the experimental uncertainties. In the experiments, an electronic digital Vernier caliper is used to measure various geometric dimensions of the MCHS test sections.…”

Experimental Validation Data for Computational Fluid Dynamics of Forced Convection on a Vertical Flat Plate

“…Other measured BCs include the wall geometry and temperature and inlet air temperature. The uncertainties of these quantities are determined using methods discussed by Coleman and Steele [13]. The manufacturer provided the uncertainty of the heat flux sensors used in this study.…”

“…(1). A Taylor series method uncertainty propagation [13] is used to compute the uncertainty of the plate emissivity using the energy balance method and is found to be on the order of the computed emissivity itself. The heated plate is surrounded on the leading, trailing, and spanwise edges with blocks of Teflon V R to allow for thermal expansion and to increase the thermal resistance between the heated plate and the Lexan side walls.…”

Investigation of supersonic turbulent combustion in a Mach 10 scramjet engine

“…there is no correlated random error. This is possible because the test time is assumed to be longer than any factor affecting the random uncertainty and the high-speed acquisition guarantees that the number of samples is large enough to negate correlated random errors [28].…”

“…The voltage measurements are taken as the mean of 20,000 samples obtained with the T4 DAQ and the absolute uncertainty is calculated with the standard deviation of these measurements [28,32]. This averages to an uncertainty of 0.03% for the vacuum measurements and 0.001% for atmospheric pressure measurements.…”