부산대학교 도서관

A commercial CFD (Computational Fluid Dynamics) code CFX (version 4.2 to 4.4) from AEA Technologyl'' has been used to compute the fluid flow, power number, Po, the stresses on baffles, mixing time and a precipitation reaction in a mixing vessel. The impellers investigated were Rushton turbine and 4 or 6 blade 45° pitch blade turbine. The impeller generated flow was modelled primarily using the sliding mesh technique, with additional modelling using Multiple Frames of Reference (MFR) for the mixing time simulations. The Po was estimated from three different methods i.e. specific energy dissipation rate, ET, summation, torque acting on the impeller surfaces, POp(primary power number), and the reaction torque acting on the vessel walls and baffles, POs (the secondary power number). The Po from the summation of ET, was underpredicted as compared with experimental values in all the simulations by over 50%. The investigation of the calculated power numbers for the vessels found that the closest and most consistent values of Po compared to experimental results were obtained from the torque acting on the impeller surfaces, POp. The value of POs was found to be greatly dependent on the sliding mesh simulation parameters and an improvement in the POsprediction could be obtained by using a small time step. A further investigation lead to the computation of the tangential forces and subsequently the axial pressure distribution on the baffles. The baffle pressure distribution depends on the impeller type and its clearance and was better predicted for greater impeller clearances and for the radial flow impellers. The mixing times simulations were performed using a computational method analogous to the experimental method of probe responses. The system was in the high transitional flow regime (Re=8800) and a low Reynolds k-e turbulence model was used in the development of the flow field. The simulations were compared with experimental results (based on decolorisation technique) and to three different mixing time correlations giving mixing times at three different levels of homogenisation (i.e. 90%, 95% and 99%). Worryingly, the simulation results were found to depend on the radial feed position even though the experimental results suggest that it does not. At certain radial position, the simulated mixing time responses accurately predicted the mixing times from the experiments and empirical correlations. CFD based flow visualisation showed that the feed position influenced where the majority of the tracer was initially distributed. The further the radial position was from the axis of the impeller, the more the bulk of the tracer moved towards the low velocity region near the vessel walls, leading to an overestimate of the mixing time. The sliding mesh and MFR simulations of the velocity fields were used for the computation of the mixing time. The results were similar in each case. The precipitation modelling was achieved through the coupling of the CFD hydrodynamics and user defined precipitation model. This approach was able to predict the performance of a semi-batch process involving the precipitation of BaS04 with 270 s addition time. The results (i.e. mean crystal size (d[4,3]) and the particle size distributions) were compared with experimental results for a double feed precipitation reaction for a number of feed configurations and concentration ratios. Overall reasonable trends and agreement have been obtained for the modelled Po, mixing time and baffle stresses. The precipitation model was less successful and was very dependant on the different crystal shape factors used in the simulation model. Further experimental work is required in order to define this parameter accurately, especially as experiments have shown that it varies during the addition time.