A new overreading model for wet gas vortex metering based on vorticity transport mechanism. (1st October 2020)

• Record Type: Journal Article
• Authors: Li, Jinxia; Wang, Chao; Ding, Hongbing; Sun, Hongjun
• Is Part Of: Measurement. Volume 162(2020)
• Publication Date: 2020-10-01
• Subjects: Vortex flowmeter -- Wet gas flow -- Annular mist flow -- Strouhal number -- Vorticity transport; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.107884
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A new overreading model for vortex metering in wet gas flow was proposed. The Strouhal number was modelled based on vorticity transport mechanism. The scale parameters were revealed and various entrainment cases were considered. The meter overreading is a function of droplet mass loading and Stokes number. Relative errors of the overreading prediction by the new equation are within ±1.0% Abstract: Vortex flowmeters are widely used in wet gas metering, however, the output gas flowrate is over-predicted, leading to large measurement error. To improve the wet gas measurement accuracy by vortex flowmeters, the meter overreading was modelled based on the particle-laden vorticity dynamic equation and vorticity transport mechanism. The scaling parameters were revealed and different droplet entrainment conditions were considered. For the experiments, an annular mist flow loop with film metering device was developed to study the vortex metering characteristics. Then, a new overreading equation was developed by using the scaling group of droplet mass loading and macroscopic Stokes number. Finally, performances of the existing overreading correlations were evaluated and analyzed in detail. The results indicate that the proposed equation provides a uniform prediction for the meter overreading, the relative deviations are within ±1.0% error band, and the predicted accuracy is greatly improved compared with other overreading correlations.