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Title: Metering of two-phase slug flow
Author: Stewart, Colin
ISNI:       0000 0001 3483 807X
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2002
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This thesis describes the development of a novel system, for metering of two-phase (gaswater) slug flows. The approach combines a model for stable slug flow, a non-intrusive set of conductance sensors, and appropriate closure relationships. This system allows each of the parameters in the model to be determined. The slug flow model is analysed, to determine the sensitivity of the phase flowrates to each measurement parameter. A metering system is then proposed which combines ring-shaped electrodes, electronic instrumentation, and processing software. The ring electrodes are optimised, for the measurement of the phase fraction and the translation velocity. New instrumentation is developed to activate the electrodes, with high measurement accuracy and a wide bandwidth. Analysis software is developed, to process the sensor data, provide suitable closure relations, and deliver the flowrates. A unique feature of this software is its ability to calculate uncertainty margins in the predicted flowrates. The NEL multiphase facility is used, to obtain data for developed, horizontal, gas-water slug flow in a 4-inch pipe. The data span the range of liquid phase superficial velocities 0.1 m s⁻¹ to 1.0 m s⁻¹, and gas phase superficial velocities 0.6 m s⁻¹ to 6.0 m s⁻¹. The analysis software is used to obtain the flowrate predictions and estimates for the uncertainty margins. The stable slug flow model does not give good results. The relative error in the gas phase prediction is between 10% and 100%, and for the liquid phase prediction, between 50% and 500%. The uncertainty margins are also of comparable magnitude. Proposals for improving the accuracy of the translation velocity measurement, and for directly measuring the local velocities in the slug body (using a pressure transducer) are presented. These proposals aim to reduce the uncertainty that is caused by the use of the empirical closure relationships in the model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Sensors