Simulation And Optimization Of The Gas-Liquid Stirred Reactor Based On CFD And MOEA

Gas-liquid stirred reactors are widely used in the process industries owing to the remarkable advantages,such as strong operation flexibility,excellent mass transfer effect and high mixing efficiency.Configurations are important factors that affect the flow,mixing,mass transfer and reaction process in the reactor.Thus,the configuration optimization of gas-liquid stirred reactors is of great significance.The early optimization of the gas-liquid stirred tank depends on experiments.The measurement methods are limited and the trial and error process can be time-consuming and costly.With the development of computational fluid dynamics(CFD)technology,it is able to acquire detailed flow field information inside the reactor quickly and accurately.However,the CFD-based optimization generally only considers the variation of a single design parameter.A large amount of simulations will be involved to take into account multiple design variables,coupled with the inherent complexity of multiphase system,which results in heavy computation and local optimum.The multi-objective evolutionary algorithm(MOEA)has advantages like global optimization,parallel searching and fast convergence.In this study,a strategy was proposed combining CFD simulation with optimization algorithm.The feasibility and availability of the strategy were verified by taking the dual-impeller aerated tank as an example.The main contents and results are as follows:(1)A multi-objective optimization methodology based on experimental measurement and CFD analysis was developed for the design of gas-liquid stirred tanks.In this method,the dual electric conductivity probe and torque sensor were utilized to investigate the accuracy of CFD models.And the CFD analysis module as well as the optimization algorithm module was integrated on the MATLAB platform.The approaches of parametric modeling and automatic mesh generation were introduced.And the optimization strategy enabled CFD to make predictions for the flow field information,which can guide the non-dominated sorting genetic algorithm(NSGA-?)to conduct efficient parallel-searching in an enormous design space.The automatic optimization process was realized through the module interfaces,leading to greatly reduced computational cost and a set of global optimal solutions.(2)The research was carried out in an air-water system with a rotation speed of 300 rpm and a superficial gas velocity of 0.02 m/s.Based on the assumption of uniform bubble size,the multi-objective optimization methodology was used for the configuration optimization of a dual-impeller aerated tank,to achieve good gas dispersion under low energy consumption.Firstly,the maximum effective gas holdup and minimum power consumption were chosen as optimization objectives,with impeller geometrical parameters as the optimization variables.CFD and NSGA-?methods were adopted to obtain the optimal design PCBDT-PTD,including a pitched concave blade disk turbine(PCBDT)as the lower impeller and a down-pumping pitched blade turbine(PTD)as the upper impeller.Then the influence of the combinations and design variables on the objective functions was discussed.It was found that the up-pumping pitched blade turbine(PTU)combinations showed the worst gas distribution uniformity,while the PTD combinations exhibited the best gas dispersion properties.When the blade lean angle of the upper impeller increased,the gas distribution became more uniform,and the power consumption first increased and then began to decrease when the lean angle was greater than 90°.Besides,the lower impeller with concave blades gained excellent gas handling capacity,which enhanced with the increasing blade aspect ratio.And the bigger the blade cutting angle was,the lower the power consumption could be.Finally,the reliability of the optimization results was investigated experimentally.The optimal design achieved uniform axial gas distribution,and significantly improved the gas dispersion performance between impellers.The optimal design was energy-efficient as the energy cost was at least 25%lower than that of the reference design RT-RT with dual Rushton turbines.(3)A bubble size model associating turbulence dissipation rate with bubble diameter was introduced to CFD simulation.On the basis of experimental verification,the multi-objective optimization of dual-impeller aerated tank was implemented.At first,the proposition pursued the maximum gas-liquid interfacial area and the minimum power input with impeller geometrical parameters as design variables was established.The optimal designs including PCBDT-PTU and PCBDT-PTD combinations were obtained.Afterwards,the distribution regularity of bubble size was uncovered and the impact of impeller combinations on the objective functions was clarified.It can be concluded that the bubble size varied along the direction of discharge flow.Smaller bubbles were generated in the impeller region and then the bubbles became larger away from the impeller region.The bubbles near the free surface and the circulation loops were relatively large.Moreover,the optimal PCBDT-PTU presented the highest peak of local interfacial area while the optimal PCBDT-PTD obtained the most uniform interfacial area distribution.Both optimal designs were energy-efficient with the superior overall mass transfer performance.The optimization results were validated according to the experiments.The mass transfer coefficient of the optimal PCBDT-PTU was nearly twice that of the reference design RT-RT,and the power input was reduced by 29%.