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Uncertainty Analysis of Indirect Measurements in Thermal Science
Published in Josua P. Meyer, Michel De Paepe, The Art of Measuring in the Thermal Sciences, 2020
X. Cui, L.C. Wei, C.F. Ma, X.Z. Meng, J.C. Chai, L.W. Jin
In probability and statistics, the concept of error does not express the connotation of mistake, but the unavoidable uncertainty in experimental data acquisition. Errors are not mistakes, and one cannot eliminate them by careful operation. The best expectation is to ensure that the experimental errors or uncertainties are as small as practically possible and to make some reliable estimates for them (Analytical Methods Committee 1995). Error analysis or experimental uncertainty estimation is the study and evaluation of uncertainty in measurement. In many scenarios, the words error and uncertainty are not explicitly distinguished and are interchangeable. In this chapter, for the sake of clarity, errors are used to describe the basic assessment of measurement, such as relative errors and absolute errors, while uncertainties are used to estimate the interval to which the “true” value belongs.
Finite Element Modeling of Grain Drying
Published in Ian Turner, Arun S. Mujumdar, Mathematical Modeling and Numerical Techniques in Drying Technology, 1996
Leandro S. Oliveira, Kamyar Haghighi
It is well established in the literature that the use of adaptive techniques can increase the accuracy and reliability of finite element solutions. The objective of an adaptive procedure is to enhance the quality of the finite element solutions by continuously redefining the mesh and reducing the discretization error until the solution converges to the desired accuracy. The adaptive finite element method uses the mathematics of error analysis to postulate that a finite element solution can indicate which regions in a given domain need refinement or derefinement of the mesh. The error analysis is based on the use of error estimates to evaluate the magnitude of the solution error. This information can then be used to adapt the mesh automatically in order to obtain the desired level of accuracy using the lowest possible number of degrees of freedom (Zienkiewicz and Taylor, 1989). In the past decade, considerable work has been done on the development of reliable and computationally inexpensive error estimates for finite element computations. These estimates play an important role in the development and implementation of an adaptive procedure. Extensive reviews of adaptive refinement techniques and error estimators were presented by Noor and Babuska (1987) and Oden et al. (1990).
Influence of fumigated calophyllum inophyllum vapours on the combustion, performance and emission characteristics of a diesel engine
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
Error analysis is the measurement of the accuracy of an obtained result. Without measuring, it is difficult to judge the fitness of the value. Error analysis is important to implement the near values on the accuracy of the estimated parameters. The model, name, range, accuracy, and uncertainties of different instruments used in this study are listed in Table 3.
Batch adsorption isotherm models applied in single and multicomponent adsorption systems – a review
Published in Journal of Dispersion Science and Technology, 2021
Beniah Obinna Isiuku, Paul C. Okonkwo, Chibuike Dickson Emeagwara
Error analysis is a method of determining mathematically the relationship between experimental and calculated data.[135] Coefficient of determination R2 is normally applied to show the closeness of experimental and calculated data but it is not always enough.[136]