The use of computational fluid dynamics to predict the turbulent dissipation rate and droplet size in a stirred autoclave

Abstract

The prediction of droplet sizes in emulsions is important for fields ranging from the chemical process industry to emergency planning in the event of an underwater oil release. Typically scale models have needed to be built and the results scaled up, but as computational resources have grown and turbulence models have matured it has become possible to use computational fluid dynamics (CFD) to simulate the behaviour of the fluid/s. While direct simulation of multiphase breakup at high Reynolds number is currently computationally impractical, this paper looks into the use of CFD along with a correlation function based on maximum turbulent kinetic energy dissipation rate to predict the Sauter mean diameter of droplets in a 1 in. baffle-and-vane type autoclave. The results show that using a RNG-k∊ turbulence model with a simplified 2D geometry gave droplet sizes within 26.2 μm of the Sauter mean diameter observed in experiments with no additional tuning of parameters. Correlating pipe and autoclave flows through the Reynolds number and the turbulent kinetic energy dissipation rate was also investigated. Using the traditional definitions of the Reynolds numbers the correlation is poor, the coefficient of determination of the linear fit to the log-log data is 0.64. The first modification replaced the diameter of the blade as characteristic length with the tip swept circumference which increased the coefficient of determination to 0.960. A further modification using data obtained from the turbulent fields of the simulation showed a significant improvement with the coefficient of determination increasing to 0.988.