Prediction of gas–liquid flow in an annular gap bubble column using a bi-dispersed Eulerian model

Machine learning applications to predict two-phase flow patterns

Recent advances in artificial intelligence with traditional machine learning algorithms and deep learning architectures solve complex classification problems. This work presents the performance of different artificial intelligence models to classify two-phase flow patterns, showing the best alternatives for this specific classification problem using two-phase flow regimes (liquid and gas) in pipes. Flow patterns are affected by physical variables such as superficial velocity, viscosity, density, and superficial tension. They also depend on the construction characteristics of the pipe, such as the angle of inclination and the diameter. We selected 12 databases (9,029 samples) to train and test machine learning models, considering these variables that influence the flow patterns. The primary dataset is Shoham (1982), containing 5,675 samples with six different flow patterns. An extensive set of metrics validated the results obtained. The most relevant characteristics for training the models using Shoham (1982) dataset are gas and liquid superficial velocities, angle of inclination, and diameter. Regarding the algorithms, the Extra Trees model classifies the flow patterns with the highest degree of fidelity, achieving an accuracy of 98.8%.

CFD Simulation of flow pattern in a bubble column reactor for forming aerobic granules and its development

The flow pattern is considered to play an important role in the formation of aerobic granular sludge in a bubble column reactor; therefore, it is necessary to understand the behavior of the flow in the reactor. A three-dimensional computational fluid dynamics (CFD) simulation for bubble column reactor was established to visualize the flow patterns of two-phase air-liquid flow and three-phase air-liquid-sludge flow under different ratios of height to diameter (H/D ratio) and superficial gas upflow velocities (SGVs). Moreover, a simulation of the three-phase flow pattern at the same SGV and different characteristics of the sludge was performed in this study. The results show that not only SGV but also properties of sludge involve the transformation of flow behaviors and relative velocity between liquid and sludge. For the original activated sludge floc to cultivate aerobic granules, the flow pattern has nothing to do with sludge, but is influenced by SGV, and the vortices is occurred and the relative velocity is increased with an increase in SGV; the two-phase flow can simplify the three-phase flow that predicts the flow pattern development in bubble column reactor (BCR) for aerobic granulation. For the aerobic granules, the liquid flow behavior developed from the symmetrical circular flow to numbers and small-size vortices with an increase in the sludge diameter, the relative velocity is amount up to u_r = 5.0, it is 29.4 times of original floc sludge.

Prediction of Main Regime Transition with Variations of Gas and Liquid Phases in a Bubble Column

Industrial bubble columns mainly operate in a heterogeneous flow regime and identifying transition from homogeneous to heterogeneous flow is important. This work addresses the determination of flow regimes with gas-liquid systems in a bubble column. Various parameters of gas holdup, volumetric mass transfer coefficient, drift flux, and pressure standard deviations were investigated to precisely determine the superficial gas velocity at the transition regime. For a column aspect ratio (H/D: static liquid height to column diameter ratio) of 2.5 to 5, the transitional superficial gas velocity generally became higher with lower liquid height. However, the reverse trend was observed with a low density gas system due to the difference in force balance acting around the bubble. The weak body force and drag force in a lower axial position interrupted the mass transfer process. The experimental results showed similar ranges of the transitional superficial gas velocity regardless of the choice of parameter for detecting it. Because there is no precise correlation about transition regime properties, we proposed new correlations to predict both transition regime superficial gas velocity and gas holdup by taking the intersection of the two regimes. The correlations precisely captured the transition regime properties within 15% deviations even in gas-liquid systems that are not tested in this work.

Decaying Swirl Flow and Particle Behavior through the Hole Cleaning Device for Horizontal Drilling of Fossil Fuel

The hole cleaning device is a powerful application which can effectively slow down the deposition of cuttings during drilling. However, in this complicated swirl flow created by the device, the decay of the swirl flow and the particle behavior are not evident yet. In this paper, the decay of the swirl flow and the particle behavior in the swirl flow field are studied by the Eulerian–Eulerian two-fluid model (TFM) coupled with the kinetic theory of granular flows (KTGF), and sliding mesh (SM) technique for simulating the fluid flow. The results show that the swirl intensity decays exponentially along the flow direction under laminar flow conditions. The swirl flow has a longer acting distance at a higher rotational speed, which can effectively slow down the deposition of cutting particles. The initial swirl intensity of swirl flow induced by the blades increases significantly with the increase of blade height and the decrease of the blade angle. The tangential velocity of the cutting particles in the annulus is more significant near the central region, gradually decreases toward the wall in the radial direction, and rapidly decreases to 0 at the wall surface. The decay rate is negatively correlated with the initial swirl intensity. The results presented here may provide a useful reference for the design of the hole cleaning device.

Extended Short-Time Fourier Transform for Ultrasonic Velocity Profiler on Two-Phase Bubbly Flow Using a Single Resonant Frequency

This study introduces a measurement technique for simultaneous phase-separated velocity in two-phase bubbly flow. The non-invasive technique, based on an Ultrasonic Velocity Profiler (UVP), is used in order to obtain an instantaneous, separate velocity profile for both liquid and bubble. The aim of this paper is to measure each phase velocity at the same time and position it using only a single resonant frequency. To achieve this aim, extended signal processing of the Short-Time Fourier Transform (STFT) is proposed, combining with amplitude classification to analyze Doppler signal influenced from the bubbly flow. The use of developed algorithms allows the instantaneous separation of liquid and bubble velocity profiles. In this work, the developed technique is used to measure the velocity profile of bubbly flow in the vertical pipe, demonstrating the classification of liquid and bubble velocity. To confirm the accuracy of each velocity profile phase, the Particle Image Velocimetry (PIV) method is used for comparison. The results clarify that the proposed method is in good agreement with the PIV measurement. Finally, the effect of void fraction against velocity measurement of both phases was demonstrated.