NUMERICAL EVALUATION OF PRESSURE DROP ACROSS ORIFICES FOR DIFFERENT GAS-LIQUID MIXTURES
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Modeling two-phase flow across orifices is critical in optimizing orifice design and fluids operation in countless architectures and machineries. While flow across different orifice geometries has been extensively studied for air-water flow, simulations and experiments on other two-phase flow combinations are limited. Since every fluid mixture has its own physical properties, such as densities, viscosities and surface tensions, the effect of these properties on the local pressure drops across the orifices may differ. This study aims to investigate the effect of different fluid combinations on the pressure drop across sharp-edged orifices with varying gas mass fractions, orifice thicknesses, and area ratios. A numerical model was developed and validated using experimental data for air-water flow. Then, the model was extended to include various gas-liquid flows including gasoil, argon-diesel and fuel oil. The local pressure drops were then estimated and compared with the existing empirical correlations. The developed model presents a unified approach to measure pressure drop across orifices for different fluid mixtures with different geometries and gas-liquid compositions, unlike existing empirical correlations which are applicable for specific orifice geometries. The results showed that Morris correlation, Simpson correlation, and Chisholm correlation are more appropriate for gasoil, argon-diesel and fuel oil mixtures, respectively. They also yielded that for all fluid combinations, increasing orifice thickness and area ratio led to a decrease in local pressure drop, while increasing gas mass fraction led to an increase in local pressure drop. This revealed that, despite having similar responses to changes in orifice geometries and gas fractions, unlike the assumption made by previous works on air-water flow, no empirical correlation is able to predict pressure drops for all flow mixtures, while the presented numerical model can efficiently determine the local pressure drop for all combinations of flow mixtures, orifice geometries and gas mass fractions.
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Volume 3: Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control
