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Application of quantile functions for the analysis and comparison of gas pressure balance uncertainties

机译:分位数函数在气体压力平衡不确定度分析和比较中的应用

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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 linearon-linear models, and how quantile functions may be applied to analyse results and compare uncertainties from a mixture of GUM and GS1 methodologies.
机译:传统上,在压力计量领域,不确定性的量化是使用《测量不确定度指南》(GUM)进行的;但是,随着GUM增补1(GS1)的引入,蒙特卡洛模拟的使用已成为计量学中不确定性分析数学模型的公认实践,在该数学模型中,GUM的基本假设无效。因此,开发了使用分位数函数作为轻松总结和报告基于蒙特卡洛模拟的不确定性数值结果的方法。在本文中,我们考虑了活塞-气缸操作压力平衡的情况,其中有效面积是根据显式/隐式和线性/非线性模型的组合进行建模的,以及如何使用分位数函数来分析结果和比较GUM和GS1方法论混合得出的不确定性。

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