Open Access
Int. J. Metrol. Qual. Eng.
Volume 13, 2022
Article Number 9
Number of page(s) 15
Published online 02 August 2022
  1. BIPM, IEC, IFCC, ILAC, ISO, IUPAP, and OIML, Evaluation of measurement data − Guide to the expression of uncertainty in measurement, tech. rep., JCGM/WG1 GUM (2008). Revised 1st edition − [Google Scholar]
  2. S. Kline, F. Mcclintock, Describing uncertainties in single-sample experiments, Mech. Eng. 75 , 3–8 (1953) [Google Scholar]
  3. BIPM, IEC, IFCC, ILAC, ISO, IUPAP, and OIML, Evaluation of measurement data − Supplement 1 to the “Guide to the expression of uncertainty in measurement” − Propogation of distributions using a Monte Carlo method, tech. rep., JCGM/WG1 GUM Supplement 1, 2008. 1st edition − [Google Scholar]
  4. R. Willink, Representating Monte Carlo output distributions?for transfereability in uncertainty analysis: modelling with quantile functions, Metrologia 46 , 154–166 (2009) [CrossRef] [Google Scholar]
  5. V. Ramnath, Application of quantile functions for the analysis and comparison of gas pressure balance uncertainties, Int. J. Metrol. Qual. Eng. 8 , 4 (2017) [CrossRef] [EDP Sciences] [Google Scholar]
  6. BIPM, IEC, IFCC, ILAC, ISO, IUPAP, and OIML, Evaluation of measurement data − Supplement 2 to the “Guide to the expression of uncertainty in measurement” − Propogation of distributions using a Monte Carlo method, tech. rep., JCGM/WG1 GUM Supplement 2 (2011). 1st edition − [Google Scholar]
  7. J.S. Hansen, GNU Octave Beginner’s Guide (PACKT Publishing, 2011) [Google Scholar]
  8. V. Ramnath, Comparison of straight line curve fit approaches for determining variances and covariances, Int. J. Metrol. Qual. Eng. 11 , 16 (2020) [CrossRef] [EDP Sciences] [Google Scholar]
  9. V. Ramnath, Analysis and comparison of hyperellipsoidal and smallest coverage regions for multivariate Monte Carlo measurement uncertainty analysis simulation datasets, MAPAN J. Metrol. Soc. India 2019 , 1–16 (2019) [Google Scholar]
  10. M.G. Cox, B.R.L. Siebert, The use of a Monte Carlo method for evaluating uncertainty and expanded uncertainty, Metrologia 43 , S178–S188 (2006) [Google Scholar]
  11. V. Ramnath, Numerical analysis of the accuracy of bivariate quantile distributions utilizing copulas compared to the GUM supplement 2 for oil pressure balance uncertainties, Int. J. Metrol. Qual. Eng. 8 , 29 (2017) [CrossRef] [EDP Sciences] [Google Scholar]
  12. P.M. Harris, M.G. Cox, On a Monte Carlo method for measurement uncertainty evaluation and its implementation, Metrologia 51 , S176–S182 (2014) [Google Scholar]
  13. Z.L. Warsza, J. Puchalski, Estimation of uncertainties in indirect multivariable measurements: Part 2. influence of the processing function accuracy, in Automation 2020 Towards Industry of the Future, edited by R. Szewczyk, C. Zielinski, M. Kaliczynska (Springer, Warsaw, Poland, 2020), pp. 326–344 [Google Scholar]
  14. A. Forbes, Approximate models of CMM behavior and point cloud uncertainties, Measurement: Sensors 18 , 100304 (2021) [CrossRef] [Google Scholar]
  15. M.G. Cox, A.M.H. van der Veen, Understanding and treating correlated quantities in measurement uncertainty evaluation, in Good practice in evaluating measurement uncertainty: Compendium of examples, edited A.M.H. van der Veen, M.G. Cox (EURAMET/NPL, 2021), pp. 29–44 [Google Scholar]
  16. N.V. Kornilov, V.G. Pronyaev, S.M. Grimes, Systematic distortion factor and unrecognized source of uncertanties in nuclear data measurements and evaluations, Metrology 2 , 1–18 (2021) [CrossRef] [Google Scholar]
  17. W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes: The Art of Scientific Computing (Cambridge University Press, 2007), 3rd edn. [Google Scholar]
  18. A. Chhabra, J.R. Venepally, D. Kim, Measurement noise covariance-adapting Kalman filters for varying sensor noise situations, Sensors 21 , 8304 (2021) [CrossRef] [PubMed] [Google Scholar]
  19. O.M. Brastein, A. Ghaderi, C.F. Pfeiffer, N.O. Skeie, Analysing uncertainty in parameter estimation and prediction for grey-box building thermal behavior models, Energy Build. 224 , 110236 (2020) [CrossRef] [Google Scholar]
  20. I. Smith, Y. Luo, D. Hutzschenreuter, The storage within digital calibration certificates of uncertainty information obtained using a Monte Carlo method, Metrology 2 , 33–45 (2022) [CrossRef] [Google Scholar]
  21. P. Saunders, Uncertainty propogation through integrated quantities for radiation thermometry, Metrologia 55 , 863–871 (2018) [CrossRef] [Google Scholar]
  22. P. Saunders, D.R. White, Physical basis of interpolation equations for radiation thermometry, Metrologia 40 , 195–203 (2003) [CrossRef] [Google Scholar]
  23. S. Briaudeau, M. Sadli, F. Bourson, B. Rougi, A. Rihan, J.J. Zondy, Primary radiometry for the mise-en-pratique: the laser-based radiance method applied to a pyrometer, Int. J. Thermophys. 32 , 2183–2196 (2011) [CrossRef] [Google Scholar]
  24. H.W. Yoon, V.B. Khromchenko, G.P. Eppeldauer, C.E. Gibson, J.T. Woodward, P.S. Shaw, K.R. Lykke, Towards high-accuracy primary spectral radiometry from 400K to 1300 K, Philos. Trans. Roy. Soc. A 374 , 1–12 (2016) [Google Scholar]
  25. A. Manoi, P. Wongnut, X. Lu, P. Bloembergen, P. Saunders, Calibration of standard radiation thermometers using two fixed points, Metrologia 57 , 014002 (2020) [CrossRef] [Google Scholar]
  26. P. Saunders, General interpolation equations for the calibration of radiation thermometers, Metrologia 34 , 201–210 (1997) [CrossRef] [Google Scholar]
  27. P. Saunders, Propagation of uncertainty for nonlinear calibration equations with an application in radiation thermometry, Metrologia 40 , 93–101 (2003) [CrossRef] [Google Scholar]
  28. A. Meurer, C.P. Smith, M. Paprocki, O. Čertík, S.B. Kirpichev, M. Rocklin, A. Kumar, S. Ivanov, J.K. Moore, S. Singh, T. Rathnayake, S. Vig, B.E. Granger, R.P. Muller, F. Bonazzi, H. Gupta, S. Vats, F. Johansson, F. Pedregosa, M.J. Curry, A.R. Terrel, S. Rouficka, A. Saboo, I. Fernando, S. Kulal, R. Cimrman, A. Scopatz, Sympy: symbolic computing in python, PeerJ Comput. Sci. 3 , e103 (2017) [CrossRef] [Google Scholar]
  29. H. Preston-Thomas, The international temperature scale of 1990 (ITS-90), Metrologia 27 , 3–10 (1990) [CrossRef] [Google Scholar]
  30. F. Sakuma, S. Hattori, A practical type fixed point blackbody furnance, in Temperature: Its Measurement and Control in Science and Industry , edited by J.F. Schooley (AIP, New York, 1982), vol. 5 , pp. 535–539 [Google Scholar]
  31. E.R. Wooliams, G. Machin, D.H. Lowe, R. Winkler, Metal (carbide)-carbon eutectics for thermometry and radiometry: a review of the first seven years, Metrologia 43 , R11–R25 (2006) [CrossRef] [Google Scholar]
  32. A.D.W. Todd, K. Anhalt, P. Bloembergen, B.B. Khlevnoy, D.H. Lowe, G. Machin, N. Sasajima, P. Saunders, On the uncertainties in the realization of the kelvin based on thermodynamic temperatures of high-temperature fixed-point cells, Metrologia 58 , 035007 (2021) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.