The purpose of this CFD analysis was to predict the level of agitation/circulation in the tank and the required torque on the shaft.
Introduction
A mud agitator is mainly used to agitate and mix the drilling mud to prevent solid particles from depositing in the tank. For proper mixing the mud agitator must be properly sized with respect to power requirement and impeller size.
Flow simulation (CFD) can be used to predict the rate of deposition in a tank. In many cases CFD is convenient for purposes of preliminary assessment, when the only opportunity to perform physical test is after the agitator is already installed in the field. Simulation can also be used efficiently to optimize with respect to engine power and impeller design.
The most accurate approach is to model the deposition in the tank as time passes. This is called a transient simulation. However, transient simulationis are very time consuming. A faster approach is to assume steady-state condition of the circulating fluid. For mud agitators this is usually a very good approximation to assume that the flow is not changing with time.
A normal measure of the degree of circulation is the turnover rate (TUR). This is a measure of the number of turns/circuits a reference volume of particles completes in the tank during a given time. The circuit is shown in the figure below.
Case study
The purpose of this CFD analysis was to predict the level of agitation/circulation in the tank and the required torque on the shaft. The required torque was later used to dimension the motor of the agitator.[/vc_column_text][/vc_column][/vc_row][vc_row][vc_column][vc_column_text]
CFD model
The model has been implemented in StarCCM+. The flow of slurry and particles was modelled using single phase flow. The particles were tracked using massless particles with a Lagrangian multiphase model. A moving reference frame was used to model the rotation of the propeller in the tank.
Results
The velocity streamlines are reported in a crossection of the tank in figure 3. The circuit in the vertical plane can be seen, and from this plot it is possible to qualitatively assess the degree of mixing. The particle tracks versus time is shown in figure 4. The turnover rate was found by measuring the fraction of particles completing one circuit within a given time frame. The different cases that were simulated is listed in the table below.
Conclusion
A CFD analysis of an industrial mud agitator has been performed. The purpose of the analysis was to predict the level of agitation/circulation in the tank and the required torque on the shaft. Data from the installed mud agitator is not available, however, the performance has been satisfactory.
