The relationship between power and flow characteristics of batch rotor-stator mixers has been studied using CFD simulations with experimental power validation. The mixer studied was the Silverson L5M batch mixer with the standard emulsor head. The size of the holes in the screen and the constriction of the base hole were changed in small increments. The MRF technique was used to model rotor rotation. A model is developed in this study which links the power and flow numbers of the mixer. Since power is easy to measure experimentally, one can use this model to predict the flow number by measuring torque. A second model is also developed which allows one to predict the flow number using solely the geometry of the mixing head. This study greatly enhances our understanding of the relationship between power, flow and mixer geometry in rotor-stator mixers.
Numerical computations are presented for the temperature and velocity distributions of two differentially heated liquid columns with liquor depths of 0.1 m and 2.215 m respectively. The temperatures in the liquid columns vary considerably with respect to position for pure conduction, free convection and nucleate boiling cases using 1D thermal resistance networks. In the thermal resistance networks the solutions are not sensitive to the type of condensing and boiling heat transfer coefficients used. However these networks are limited and give no indication of velocity distributions occurring within the liquor. To alleviate this issue, 2D axisymmetric and 3D CFD simulations of the test rigs have been performed. The axisymmetric conditions of the 2D simulations produce unphysical solutions; however the full 3D simulations do not exhibit these behaviours. There is reasonable agreement for the predicted temperatures, heat fluxes and heat transfer coefficients when comparing the boiling case of the 1D thermal resistance networks and the CFD simulations. This work was undertaken by the University of Leeds and National Nuclear Laboratory Ltd as part of our on-going support of Sellafield Ltd's operations. The work was funded by the EPSRC, National Nuclear Laboratory Ltd and Sellafield Ltd/NDA through an EPSRC CASE award.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.