New PDF release: Advanced Mathematical And Computational Tools in Metrology
By P. Ciarlini, E Filipe, A B Forbes, F Pavese, C Perruchet, B R L Siebert
This quantity collects the refereed contributions in keeping with the displays made on the 7th Workshop on complex Mathematical and Computational instruments in Metrology, a discussion board for metrologists, mathematicians and software program engineers that may motivate a more suitable synthesis of abilities, features and assets. the quantity includes articles via global popular metrologists and mathematicians focused on dimension technological know-how and, including the six prior volumes during this sequence, constitutes an authoritative resource of the mathematical, statistical and software program instruments valuable in sleek metrology.
Read or Download Advanced Mathematical And Computational Tools in Metrology VII (Series on Advances in Mathematics for Applied Sciences) PDF
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Additional info for Advanced Mathematical And Computational Tools in Metrology VII (Series on Advances in Mathematics for Applied Sciences)
Pp. 23-34) DATA EVALUATION OF K E Y COMPARISONS INVOLVING SEVERAL ARTEFACTS M. G. C O X , P. M. uk OLW, UK Key comparison data evaluation can be influenced by many factors including artefact instability, covariance effects, analysis model, and consistency of model and data. For a comparison involving several artefacts, further issues concern the manner of determination of a key comparison reference value and degrees of equivalence. This paper discusses such issues for key comparisons comprising a series of linked bilateral measurements, proposing a solution approach.
5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. Technical report, Bureau International des Poids et Mesures, Sevres, France, 1999. BIPM, IEC, IFCC, ISO, IUPAC, IUPAP, and OIML. Guide to the Expression of Uncertainty in Measurement, 1995. ISBN 92-67-10188-9, Second Edition. M. G. Cox. A discussion of approaches for determining a reference value in the analysis of key-comparison data. Technical Report CISE 42/99, National Physical Laboratory, Teddington, UK, 1999. M. G. Cox. The evaluation of key comparison data.
Thus, the value component of the unilateral DoE for NMI % is given by di = Sj and the associated uncertainty by u(di) = u(si). Under a normality assumption, the unilateral DoE for NMI i would be taken as (s*, 2u(si)). The u2(si) are relevant diagonal elements of Uy. However, U(SJ) so obtained would be too small as a result of the effect of processing a quantity of data on the uncertainties associated with random effects. Hence, the value obtained can be augmented in quadrature by a typical uncertainty associated with random effects as reported by NMI i.
Advanced Mathematical And Computational Tools in Metrology VII (Series on Advances in Mathematics for Applied Sciences) by P. Ciarlini, E Filipe, A B Forbes, F Pavese, C Perruchet, B R L Siebert