In this work, feasibility of flow pattern and oil holdup prediction for vertical upward oil–water two–phase flow using pressure fluctuation signals was experimentally investigated. Water and diesel fuel were selected as immiscible liquids. Oil holdup was measured by Quick Closing Valve (QCV) technique, and five flow patterns were identified using high speed photography through a transparent test section with Inner Diameter (ID) of 0.0254 m. The observed flow patterns were Dispersed Oil in Water (D O/W), Dispersed Water in Oil (D W/O), Transition Flow (TF), Very Fine Dispersed Oil in Water (VFD O/W) and a new flow pattern called Dispersed Oil Slug & Water in Water (D OS& W/W). The pressure fluctuation signals were also measured by a static pressure sensor and decomposed at five levels using wavelet transform. Then, standard deviation values of decomposition levels were used as input parameters of a Probabilistic Neural Network (PNN) to train the network for predicting the flow patterns. In addition, some considered numerical values for actual flow patterns together with signal energy value of each level were used as input parameters of a MultiLayer Perceptron (MLP) network to estimate the oil holdup. The results indicated good accuracy for recognition of the flow patterns (accuracy of 100% and 95.8% for training data and testing data, respectively) and oil holdup (AAPE=9.6%, R=0.984 for training data and AAPE=8.07%, R=0.99 for testing data).

In case of poor-quality oil refining in the oil pipeline, water accumulations are formed, increasing hydraulic losses during transportation and contributing to corrosion processes. Hydrodynamic cleaning, which uses pumped oil flow, has been investigated due to its cost-effectiveness and adaptability for pipelines of varying diameters. This study develops a finite element hydrodynamic model to simulate the removal of water accumulations from inclined pipelines (inclination angle α = 45°). The model reveals a clear relationship between inlet velocity and multiphase flow patterns, demonstrating transitions from stratified flow (ST) at velocities below 0.1 m/s, to stratified with mixing (ST&MI) at 0.1–0.2 m/s, and finally to a dispersed water-in-oil (DW/O) pattern beyond 0.2 m/s. These velocity transitions are achieved in controlled steps: a steady increase to 0.1 m/s within 20 seconds, followed by acceleration phases reaching 0.25 m/s by 100 seconds. The DW/O regime exhibits the highest cleaning efficiency, reducing water volume from 660 ml to 273.29 ml over 125 seconds—a 58.5% reduction. The analysis further shows an initial rise in pressure gradient within the ST regime, peaking during the first plateau (0.1 m/s) before stabilizing and significantly declining in the DW/O regime at velocities exceeding 0.25 m/s. These findings emphasize the importance of optimizing flow velocity to achieve effective water removal while minimizing hydraulic losses. The study also highlights limitations in existing experimental setups, which predominantly use small diameters (<50 mm), and underscores the need for larger-scale experiments to validate these findings in real-world pipeline operations.

The study on the flow behave inside of a ball valve is important for heavy crude oil transportation. Owe to the fast progress of the numerical technique, it becomes an effective way to observe the flows inside a valve and to analyze the flow structure of the oil-water core annular flow. In the present study, the simulation of the oil-water core annular flowing through the valve is conducted by combined the VOF and CSF model, and the effects of open rate on vortex and oil distribution characteristics are analyzed. The simulated data is a satisfactory match with empirical value and the experimental results. The results show that there are lots of vortexes inside and behind the valve, the coordinate values of the vortex decrease and the aggregation rate increases with increase in open rate. As the input velocity increases, the change rate of the vortex position is greater, and the oil aggregation rate decreases, the highly viscous oil with has greater aggregation rate after flow through the valve, and the variation of the vortex core position is relatively slow. As the vortex flow across the oil core, the oil will be scattered and contributes to the instability of the annular flow.

Oil–air flow within an oil bath lubrication tapered roller bearing is essential for the lubrication and cooling of the bearing. In this paper, we develop a simulation model to investigate the flow field of tapered roller bearings with oil bath lubrication. The multiple reference frame (MRF) approach is used to describe the physical motion of the bearing, and the volume of fluid (VOF) two–phase flow model is used to track the oil–air interface in the flow field. The effects of mesh scale, geometric gap, and oil reservoir size on calculation time and convergence accuracy are examined in detail, and the effects of inner ring rotational speed and lubricant viscosity on frictional torque are systematically studied. The results of the numerical simulation indicate that as the gap distance between the raceway and the rolling elements decreases, the frictional torque is mainly generated by churning losses at the inner raceway and the rolling elements. The frictional torque increases with increasing inner ring speed and lubricating oil viscosity, with the rolling element contributing the largest portion at approximately 50% of the total. We demonstrate the effectiveness of a method to reduce frictional torque by optimizing the internal structure of the bearing to control oil flow. By optimizing the cage structure and reducing the roller half-cone angle, frictional torque can be reduced by 29. 1% and 26. 2%, respectively.