Taylor bubble velocity in slug flow is a closure relation which significantly affects the prediction of liquid holdup (or void fraction) and pressure gradient in mechanistic models of slug flow for oil and gas pipe applications. In this work, we use a validated Computational Fluid Dynamics (CFD) approach to simulate the motion of Taylor bubbles in pipes; the interface is tracked with a Level-Set method implemented in a commercial code. A large numerical database is generated covering the most ample range of fluid properties and pipe inclination angles explored to date (Eo ∈ [10, 700], M o ∈ [1•10 −6 , 5•10 3 ], and θ ∈ [0 • , 90 • ]). A unified Taylor bubble rise velocity correlation is extracted from that database. The new correlation predicts the numerical database with 8.6% absolute average relative error and a coefficient of determination R 2 = 0.97, and other available experimental data with 13.0% absolute average relative error and R 2 = 0.84 outperforming existing correlations and models.

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Manufacturers of fluid power equipment have decreased the size of hydraulic fluid reservoirs in response to economic, environmental and performance requirements. Residence times as brief as 30 seconds in mobile equipment are not unusual. Shorter fluid residence times dictate use of hydraulic fluids with improved air release characteristics. In this investigation, hydraulic fluids of the same ISO viscosity grade but varying base oil and additive composition were evaluated in a dynamometer fitted with a reservoir that incorporated an aerator at the inlet, and a mass flow meter at the outlet. The effects of aeration on piston pump efficiency and air borne noise generation were evaluated. Fluids of the same ISO viscosity grade exhibited significantly different air release rates and as a result sustained different volume fractions of entrained air. Hydraulic oils that entrained a greater volume of air demonstrated lower volumetric efficiencies and higher sound levels. Aerated fluids of the identical viscosity grade differed in volumetric efficiency by as much as 8% and perceived sound level by as much as 50%. Models for the effect of aeration on pump performance are presented.

The velocity of Taylor bubbles in inclined pipes is reduced if a lubricating liquid film between the bubble and the pipe wall is not present. An analytical model predicting the gravity-driven drainage of the lubricating film is presented in this article. The model is then used to establish a criterion for film breakup: ift bubble = t bubble /τ < 0.01 the thin film would not break up, where t bubble is the bubble's passage time, and τ is the characteristic film drainage time based on the fluid properties, pipe geometry, and critical film thickness. The model is validated experimentally with Taylor bubbles in inclined pipes (5• to 90• , the latter being vertical) of stagnant liquids (ethanol, methanol, and mixtures of deionized water and methanol).

Nowadays, GPS receivers are very reliable because of their good accuracy and precision; however, uncertainty is also inherent in geospatial data. Quality of GPS measurements can be influenced by atmospheric disturbances, multipathing, synchronization of clocks, satellite geometry, geographical features of the observed region, low broadcasting coverage, inadequate transmitting formats, or human or instrumental unknown errors. Assuming that the scenario and technical conditions that can influence the quality of GPS measurements are optimal, that functional and stochastic models that process the signals to a geodetic measurement are correct, and that all the GPS observables are taken in the same conditions, it is still possible to estimate the positional errors as the difference between the real coordinates and those measured by the GPS. In this paper, three spatial linear mixed models, one for each axis, are used for modelling real-time kinematic (RTK) GPS accuracy and precision, of a multiple-referencestation network in dual-frequency with carrier phase measurements. We interpret "accuracy" as unbias and "precision" as a variance, but not for a particular signal or a set of signals when they are processed to become