Uncertainty evaluation for aneroid barometer measurement part II: “Monte Carlo method”

To further improve the accuracy of the measurement uncertainty evaluation results of the aneroid barometer and verify the applicability of the GUM evaluation of the aneroid barometer, the Monte Carlo method (MCM) is proposed to evaluate the measurement uncertainty of the calibration results of the aneroid barometer. An improved calibration technique for the aneroid barometer was utilized in this process, yielding more precise calibration data through a meticulously designed experimental program. Subsequently, single-batch MCM and adaptive MCM (AMCM) were applied separately for evaluation, and their results were compared and analyzed against the GUM method to verify the applicability of each approach. In addition, to comprehensively assess the effectiveness of the new methods, this study also conducted control evaluations using traditional methods that did not account for the effects of the coefficient box and indicator box performance. The results show that MCM is superior to the GUM method in accuracy and reliability and is also more efficient in execution. In particular, the evaluation results of single-batch MCM and AMCM are in good agreement, but AMCM shows a superior performance with fewer simulations and more efficient execution. When evaluating the uncertainty of the temperature coefficient, introducing the new method has little effect on the evaluation results; however, when evaluating the uncertainty of the indication error, introducing a new method can significantly improve the accuracy of the evaluation results. This indicates that the new method has significant advantages in improving the accuracy of the evaluation results. In addition, the GUM method was validated by MCM, and the results showed that the GUM method is still suitable for the measurement uncertainty evaluation of the indication error of the aneroid barometer. Therefore, it is recommended that MCM, especially AMCM, which is more efficient in implementation, should be preferred in the field of measurement uncertainty evaluation of the aneroid barometer; meanwhile, the GUM method, as the basic assessment method in this field, should be retained and continue to play its role.

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Publication Details

Journal
Review of Scientific Instruments
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0233769
Citations
3
Primary Topic
Scientific Measurement and Uncertainty Evaluation
Type
article
Field-Weighted Citation Impact
4.20

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article

Uncertainty evaluation for aneroid barometer measurement part II: “Monte Carlo method”

Mingming Wei, X. R. Chen, Jie Miao, Taocheng Zhou et al.
3 citations
Review of Scientific Instruments
Scientific Measurement and Uncertainty Evaluation
4.20
article

Uncertainty evaluation for aneroid barometer measurement part II: “Monte Carlo method”

Mingming Wei, X. R. Chen, Jie Miao, Taocheng Zhou, Qi Yan
article en
3 citations

Abstract

To further improve the accuracy of the measurement uncertainty evaluation results of the aneroid barometer and verify the applicability of the GUM evaluation of the aneroid barometer, the Monte Carlo method (MCM) is proposed to evaluate the measurement uncertainty of the calibration results of the aneroid barometer. An improved calibration technique for the aneroid barometer was utilized in this process, yielding more precise calibration data through a meticulously designed experimental program. Subsequently, single-batch MCM and adaptive MCM (AMCM) were applied separately for evaluation, and their results were compared and analyzed against the GUM method to verify the applicability of each approach. In addition, to comprehensively assess the effectiveness of the new methods, this study also conducted control evaluations using traditional methods that did not account for the effects of the coefficient box and indicator box performance. The results show that MCM is superior to the GUM method in accuracy and reliability and is also more efficient in execution. In particular, the evaluation results of single-batch MCM and AMCM are in good agreement, but AMCM shows a superior performance with fewer simulations and more efficient execution. When evaluating the uncertainty of the temperature coefficient, introducing the new method has little effect on the evaluation results; however, when evaluating the uncertainty of the indication error, introducing a new method can significantly improve the accuracy of the evaluation results. This indicates that the new method has significant advantages in improving the accuracy of the evaluation results. In addition, the GUM method was validated by MCM, and the results showed that the GUM method is still suitable for the measurement uncertainty evaluation of the indication error of the aneroid barometer. Therefore, it is recommended that MCM, especially AMCM, which is more efficient in implementation, should be preferred in the field of measurement uncertainty evaluation of the aneroid barometer; meanwhile, the GUM method, as the basic assessment method in this field, should be retained and continue to play its role.

Review of Scientific InstrumentsVol. 96(3)
Shaanxi Provincial Meteorological Bureau (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province
Openalex Percentile: Top 6%
Scientific Measurement and Uncertainty Evaluation
4.20
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