LNG mass flow measurement uncertainty reduction using calculated Young's modulus and Poisson's ratio for Coriolis flowmeters

We have proposed new methods to reduce the LNG mass flow measurement uncertainty using a Coriolis mass flowmeters (CMF). Since the uncertainty in the corrected Young's modulus of meter tube is the dominating contribution factor, it is proposed to derive the Young's modulus at LNG temperature using the calculated LNG density and the natural bending frequency measurement. The expanded uncertainty of the calculated Young's modulus is evaluated to be 0.071%, which will enable the LNG mass flow measurement uncertainty of a straighttube CMF to be reduced from 0.50% to 0.20% (k=2). This approach has the potential to provide more accurate LNG mass flow measurement in comparison to conventional methods which use the corrected Young's modulus at LNG temperature. We have analysed the error in flow measurement using a U-tube CMF. An extra mass flow factor is shown to be the dominating mass flow measurement uncertainty factor due to the high uncertainty in the measured Poisson's ratio of the tube. A new method is proposed to calculate the Poisson's ratio from the torsional frequency and bending frequency measurements, with expanded uncertainty of 0.14%, 13 times lower than that of the measured values. The LNG mass flow measurement uncertainty of a U-tube CMF is estimated to be to 0.24% (k=2) using the calculated Poisson's ratio and Young's modulus. Our theoretical analysis shows that accurate estimation of Young's modulus and Poisson's ratio can significantly reduce the LNG mass flow measurement uncertainty using a CMF.

Automated summary

New methods have been proposed to reduce the measurement uncertainty of LNG mass flow using Coriolis mass flowmeters (CMF). By deriving the Young's modulus at LNG temperature and calculating the Poisson's ratio from torsional and bending frequency measurements, more accurate LNG mass flow measurement can be achieved. The expanded uncertainty of these calculations is significantly lower than the measured values, leading to a reduction in measurement uncertainty.