Churn turbulent flow

Introduction

In Fluid dynamics, many a times we encounter bubble flow. Initially the number of bubbles in the flow is low, this we call as ideally-separated bubble flow. In this type of flow the bubbles don’t interact each other directly or indirectly but as the number of bubbles increase they started colliding each other and their size get reduced. Suddenly a situation comes when they tend to coalesce to form cap bubbles, and the new flow pattern formed is called churn turbulent flow. The bubbles occurring in such a flow can be classified in small, large, and distorted bubbles. The small bubbles are generally spherical or elliptical and are encountered in a major concentration in the wake of large and distorted bubbles and close to the walls. Large, -ellipsoidal or cap bubbles can be found in the core region of the flow as well as the distorted bubbles with a highly deformed interface. Churn-turbulent flow has a high application in industries. It is commonly encountered in industrial applications, and so there is a necessity to understand the physics behind it, and model it in a much efficient and accurate manner. A typical example of churn turbulent flow is boiling flow in nuclear reactors. Especially for many accident scenarios, boiling may lead to high void portion including churn-turbulent flow. Its flow structure may have a strong impact on the safety. For all these reasons, consistent predictions of such flows are an important and major issue for safety analyses.

Contents:

• Introduction
• Numerical Simulation of Bubble Column Flow In Churn-Turbulent Regime

Numerical Simulation of Bubble Column Flows in Churn-Turbulent Regime

The numerical simulations of cylindrical bubble column operating in the churn-turbulent regime have been simulated using Euler–Euler approach incorporated with the RNG k–ε model for liquid turbulence. Here we will see single-sized bubble modelling, double-sized bubble modelling, and the multiple sizes group modelling (MUSIG), including the homogeneous and inhomogeneous discrete methods are employed in the simulations. Breakup mass conserved formulations and coalescence rates mass conserved formulation was used in the computation of bubble size distributions. For single size modelling the Schiller–Naumann drag force was used, and for the modelling of MUSIG the Ishii–Zuber drag force was used. An empirical drag formulation was used for the double size bubble model. The simulation results of time-averaged axial velocity and gas holdup obtained with the three models were compared with reported experimental data in the resulting literature. After the comparison of all the three results it gets very clear that only MUSIG models with some lift force can replicate the measured radial distribution of gas holdup in the fully developed flow regime. The inhomogeneous MUSIG model gives a little better result than other models in the prediction of axial liquid velocity. For all the simulations the RNG k–ε model was used, and the results showed that this version of k–ε model did yield comparatively high rate of turbulence dissipation and high bubble breakup and, hence, a rational bubble size distribution formed. Here the ad hoc manipulation of the breakup rates was ignored. Mutual effects of drag force, mean bubble sizes, and turbulence characteristics profound from the simulation results. A decrease in the relative velocity between two phases is encounters due to an increase in the drag force, and this could result in decrease in k and ε. Low breakup rates results a large sauter diameter which was directly connected to the dissipation rates of turbulence. Drag force is directly influenced by the change of Sauter diameter. Computational modelling of the flow is done using an Eulerian multi-fluid approach using ANSYS software package CFX, while for generating the mesh ICEM CFD is generally utilized. The preliminary point which is based on already existing models for bubbly flows comprise turbulent dispersion, drag force, bubble induced turbulence. Some examples of these are the particle induced turbulence model done by Rzehak (Rzehak and Krepper, 2012), the bubble-bubble interaction model done by Liao (Liao et al, 2011), and the inhomogeneous MUSIG (MUltiple SIze Group) approach established by Krepper (Krepper et al., 2008). The last one allows us to define many different bubble sizes groups with different velocity fields for both large as well as small bubbles. For the simulation of the churn-turbulent flows, the gas phase is showed by three different gas fields corresponding to the three types of bubbles mentioned above. This multi size group technique allows us creating a more realistic approximation of the churn-phenomenon.