Journal of Chemical Engineering of Japan, Vol.36, No.8, 940-945, 2003
Drop size distribution in liquid-liquid mixing
The experiments of immiscible liquid-liquid mixing in a stirred vessel were performed in order to relate the drop size distribution with impeller revolutional speed and to examine the applicability of a new formula of the drop size distribution presented by authors. The new formula based on an information entropy concept is composed of the product of the original distribution function and the realizable probability function derived under following two assumptions. First, the break-up of a drop occurs when the external force/energy exceeds the internal force/energy of the drop. Second, there is a limitation in the drop size which can exist in actuality.In the present work, ethyl malonate and water were adopted as a dispersed phase and a continuous phase, respectively. By setting the dilute volume fraction of the dispersed phase, the break-up of drops seems to be dominant while coalescence could be negligible. Impeller revolutional speed was varied from 210 to 300 rpm. A photographic method was utilized to measure the drop size.It is clarified that the new formula can express sufficiently the experimental data. Additionally, the drop size distribution for the number density derived from the new formula is also in agreement with the experimental data. The usefulness of the newly expressed formula is confirmed by applying it to other experimental data presented by other investigators.The parameter L as a mean size in the new formula is correlated with the impeller revolutional speed and it is made clear that L is in proportion to the impeller revolutional speed to the minus 1.2 power like the case of the Sauter mean drop size and the maximum drop size. The other parameter B as a coefficient is considered to be affected only by the ratio of the viscosity of dispersed phase to that of continuous phase of the liquid-liquid system.
Keywords:size distribution function;drop break-up;liquid-liquid mixing;turbulent flow;information entropy