Version 1
: Received: 28 October 2024 / Approved: 29 October 2024 / Online: 29 October 2024 (10:43:46 CET)
How to cite:
Garcia-Berrocal, A.; Montalvo, C.; Carmona, P.; García-Álvarez, R. Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer. Preprints2024, 2024102271. https://doi.org/10.20944/preprints202410.2271.v1
Garcia-Berrocal, A.; Montalvo, C.; Carmona, P.; García-Álvarez, R. Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer. Preprints 2024, 2024102271. https://doi.org/10.20944/preprints202410.2271.v1
Garcia-Berrocal, A.; Montalvo, C.; Carmona, P.; García-Álvarez, R. Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer. Preprints2024, 2024102271. https://doi.org/10.20944/preprints202410.2271.v1
APA Style
Garcia-Berrocal, A., Montalvo, C., Carmona, P., & García-Álvarez, R. (2024). Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer. Preprints. https://doi.org/10.20944/preprints202410.2271.v1
Chicago/Turabian Style
Garcia-Berrocal, A., Pablo Carmona and Raúl García-Álvarez. 2024 "Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer" Preprints. https://doi.org/10.20944/preprints202410.2271.v1
Abstract
The adaptive implementation of the Monte Carlo Method (AMCM) has been applied to optimize the calibration uncertainty of a positive displacement meter against a standard tank in an ISO 17025 accredited volume laboratory. These meters are used for custody transfer in liquid hydrocarbon logistics where any reduction in the uncertainty estimation may have an important economic impact. Several innovations are proposed when applying AMCM; regulation of AMCM convergence by applying the Student's t-distribution, validation of repeatability and filtering of outliers by performing 50 iterations of the AMCM, and characterization of the measurand's Probability Density Function (PDF) which results in a Flatten Gaussian. This work proves that GUM method does not assign the correct PDF. The uncertainty estimation is reduced 7.1 % compared to GUM method.
Keywords
Monte Carlo; custody transfer; flow meter; meter factor; uncertainty
Subject
Engineering, Mechanical Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
