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Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach

The importance of measurement quality cannot be over emphasized in medical applications, as one is dealing with life issues and the wellbeing of society, from oncology to new-borns, and more recently to patients of the COVID-19 pandemic. In all these dire situations, the accuracy of fluid delivered...

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Detalles Bibliográficos
Autores principales: Sousa, J.A., Batista, E., Demeyer, S., Fischer, N., Pellegrino, O., Ribeiro, A.S., Martins, L.L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756327/
https://www.ncbi.nlm.nih.gov/pubmed/36540695
http://dx.doi.org/10.1016/j.measurement.2021.109589
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author Sousa, J.A.
Batista, E.
Demeyer, S.
Fischer, N.
Pellegrino, O.
Ribeiro, A.S.
Martins, L.L.
author_facet Sousa, J.A.
Batista, E.
Demeyer, S.
Fischer, N.
Pellegrino, O.
Ribeiro, A.S.
Martins, L.L.
author_sort Sousa, J.A.
collection PubMed
description The importance of measurement quality cannot be over emphasized in medical applications, as one is dealing with life issues and the wellbeing of society, from oncology to new-borns, and more recently to patients of the COVID-19 pandemic. In all these dire situations, the accuracy of fluid delivered according to a prescribed dose can be critical. Microflow applications are growing in importance for a wide variety of scientific fields, namely drug development and administration, Organ-on-a-Chip, or bioanalysis, but accurate and reliable measurements are a tough challenge in micro-to-femto flow operating ranges, from 2.78 × 10(−4) mL/s down to 2.78 × 10(−7) mL/s (1000 μL/h down to 1 μL/h). Several sources of error have been established such as the mass measurement, the fluid evaporation dependent on the gravimetric methodology implemented, the tube adsorption and the repeatability, believed to be closely related to the operating mode of the stepper motor and drive screw pitch of a syringe pump. In addition, the difficulty in dealing with microflow applications extends to the evaluation of measurement uncertainty which will qualify the quality of measurement. This is due to the conditions entailed when measuring very small values, close to zero, of a quantity such as the flow rate which is inherently positive. Alternative methods able to handle these features were developed and implemented, and their suitability will be discussed.
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spelling pubmed-97563272022-12-16 Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach Sousa, J.A. Batista, E. Demeyer, S. Fischer, N. Pellegrino, O. Ribeiro, A.S. Martins, L.L. Measurement (Lond) Article The importance of measurement quality cannot be over emphasized in medical applications, as one is dealing with life issues and the wellbeing of society, from oncology to new-borns, and more recently to patients of the COVID-19 pandemic. In all these dire situations, the accuracy of fluid delivered according to a prescribed dose can be critical. Microflow applications are growing in importance for a wide variety of scientific fields, namely drug development and administration, Organ-on-a-Chip, or bioanalysis, but accurate and reliable measurements are a tough challenge in micro-to-femto flow operating ranges, from 2.78 × 10(−4) mL/s down to 2.78 × 10(−7) mL/s (1000 μL/h down to 1 μL/h). Several sources of error have been established such as the mass measurement, the fluid evaporation dependent on the gravimetric methodology implemented, the tube adsorption and the repeatability, believed to be closely related to the operating mode of the stepper motor and drive screw pitch of a syringe pump. In addition, the difficulty in dealing with microflow applications extends to the evaluation of measurement uncertainty which will qualify the quality of measurement. This is due to the conditions entailed when measuring very small values, close to zero, of a quantity such as the flow rate which is inherently positive. Alternative methods able to handle these features were developed and implemented, and their suitability will be discussed. The Authors. Published by Elsevier Ltd. 2021-08 2021-05-18 /pmc/articles/PMC9756327/ /pubmed/36540695 http://dx.doi.org/10.1016/j.measurement.2021.109589 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Sousa, J.A.
Batista, E.
Demeyer, S.
Fischer, N.
Pellegrino, O.
Ribeiro, A.S.
Martins, L.L.
Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title_full Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title_fullStr Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title_full_unstemmed Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title_short Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach
title_sort uncertainty calculation methodologies in microflow measurements: comparison of gum, gum-s1 and bayesian approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756327/
https://www.ncbi.nlm.nih.gov/pubmed/36540695
http://dx.doi.org/10.1016/j.measurement.2021.109589
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