Issue |
Int. J. Metrol. Qual. Eng.
Volume 8, 2017
|
|
---|---|---|
Article Number | 4 | |
Number of page(s) | 18 | |
DOI | https://doi.org/10.1051/ijmqe/2016020 | |
Published online | 15 February 2017 |
Research Article
Application of quantile functions for the analysis and comparison of gas pressure balance uncertainties
Department of Mechanical and Industrial Engineering, University of South Africa, Private Bag X6, Florida 1710, South Africa
⁎ Corresponding author: ramnav@unisa.ac.za
Received:
4
July
2016
Accepted:
13
September
2016
Traditionally in the field of pressure metrology uncertainty quantification was performed with the use of the Guide to the Uncertainty in Measurement (GUM); however, with the introduction of the GUM Supplement 1 (GS1) the use of Monte Carlo simulations has become an accepted practice for uncertainty analysis in metrology for mathematical models in which the underlying assumptions of the GUM are not valid. Consequently the use of quantile functions was developed as a means to easily summarize and report on uncertainty numerical results that were based on Monte Carlo simulations. In this paper, we considered the case of a piston–cylinder operated pressure balance where the effective area is modelled in terms of a combination of explicit/implicit and linear/non-linear models, and how quantile functions may be applied to analyse results and compare uncertainties from a mixture of GUM and GS1 methodologies.
Key words: pressure balance / GUM / GS1 / uncertainty quantification / quantile function
© V. Ramnath, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.