Measurement of the homogeneous velocity of inclined oil-in-water flows using a resistance cross correlation flow meter

Lucas, Gary and Jin, N.D. (2001) Measurement of the homogeneous velocity of inclined oil-in-water flows using a resistance cross correlation flow meter. Measurement Science and Technology. pp. 1529-1537. ISSN 0957-0233

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Abstract

This paper describes an investigation into a cross correlation flow meter, using `global' resistance sensors, for measuring the homogeneous velocity of inclined oil-in-water flows. The cross correlation flow meter measures the axial propagation speed Ucc of intermittent Kelvin-Helmholtz structures in the flow. It is shown that, for inclination angles in the range 15° to 45° from the vertical, the measured velocity Ucc is dependent only upon the homogeneous velocity and is independent both of the inclination angle θ of the flow and of the oil volume fraction α. For an angle of inclination to the vertical of 60°, Ucc is dependent both upon the homogeneous velocity and upon the oil volume fraction α. For inclination angles in the range 15°≤θ≤45° predictions of the homogeneous velocity were obtained using only the measured cross correlation velocity Ucc. For 15°≤θ≤45°, the mean percentage error in the predicted homogeneous velocity was 0.1% whilst the standard deviation of the percentage error in the predicted values of the homogeneous velocity was found to be 4.0%. For the angle of inclination to the vertical of 60° predictions of the homogeneous velocity were obtained using the measured cross correlation velocity Ucc and the measured oil volume fraction α. For θ = 60° the mean percentage error in the predicted homogeneous velocity was -0.39% whilst the standard deviation of the percentage error in the predicted values of the homogeneous velocity was 5.2%

Item Type:	Article
Additional Information:	UoA 25 (General Engineering)
Subjects:	T Technology > T Technology (General) Q Science > QC Physics
Schools:	School of Computing and Engineering School of Computing and Engineering > Systems Engineering Research Group School of Computing and Engineering > High-Performance Intelligent Computing > High Performance Computing Research Group
Related URLs:	Author
Depositing User:	Briony Heyhoe
Date Deposited:	30 Sep 2008 14:10
Last Modified:	28 Aug 2021 10:41
URI:	http://eprints.hud.ac.uk/id/eprint/2044

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