Measurement uncertainty distributions and uncertainty propagation by the simulation approach

Abstract

A complete and accurate evaluation of measurement uncertainty requires the knowledge of the uncertainty distributions. The latter are rarely determined or verified experimentally, and hence up to now only crude estimates or assumptions based on intuition have been used. The simulation of experimental results is readily accessible and provides a more reliable solution to this problem. When using an appropriate model of measurement and after determination of input value parameters by present state-of-the-art techniques, simulation data supply reliable information about the distribution of the output results of a complex measurement. The method permits simple variation of preposition and therefore ready analysis of various features influencing the measurement of uncertainty intervals. In the paper we described examples of such evaluations related to the preparation of certified reference materials, where there is excellent agreement between the traditional and simulation approaches. And evaluation of more complex measurements of diffusion coefficients by the open capillary method, where uncertainty of the simulated result is more realistic than the result from the traditional error method due to non-linearity and probably Cauchy distribution in some steps.