Simulation And Optimization Of Reactor Configuration Based On CFD And MOEA

Flow and mixing in chemical reactors,which are largely affected by the reactor configuration,play an important part in the mass transfer and reaction.Therefore,the optimization of reactor configuration is of great significance in the design of high-efficiency reactor.Computational fluid dynamics(CFD)and the particle image velocimetry(PIV)could reveal the macroscopic and microscopic characteristics of the fluid flow and mixing.However,current optimization on reactors is usually based on the influence of one single parameter on the flow and mixing,or simply comes from a large amount of experiments,which can only result in local optimum.To achieve global optimum,various parameters with multiple parameter levels have to be taken into account during optimization,which requires a lot of experiments and computing time.The multi-objective evolutionary algorithm(MOEA)is a simple,universal and robust algorithm which employs parallel optimal search to analyze problems comprehensively and save experiment and simulation time.It is favorable to combine the optimization methods and CFD for global optimization of reactor configuration.But the parameterization of reactor configuration,the complexity of the fluid flow and the combination of CFD and optimization algorithm are the problems to be solved.The main contents and results are as follows:(1)A multi-objective optimization strategy for the reactor configuration design based on experiments(DOE),CFD and MOEA is established,which is composed of CFD for the revealing of flow field information and genetic algorithm for its advantages of optimization.(2)In the simulation of low viscosity fluid flow of axial flow impellers,realizable k-? turbulent model has better performance than the standard k-? turbulent model which was validated by particle image velocimetry(PIV)experiments.In the simulation of high viscosity flow patterns of broken helical-ribbon(BHR),the CFD model based on SST k-? model was validated by PIV experiments.The Eulerian-Eulerian two fluid model combined with the kinetic theory of granular flow was validated by experiments of two-dimensional bed.(3)Axial flow impellers for low viscosity fluid were optimized by the multi-objective optimization strategy.According to the optimization results,the increase of loop height or the width ratio of blades,or the decrease of blade twist angle promotes stronger flow of fluid discharging from the impeller,while causes more energy dissipation.Compared with 45° three pitched blade turbine,optimal axial flow impeller PBT25-0.6-2 increases 16%in the axial flow rate under the same power consumption,while the Np/NQd and the zone of high local specific energy dissipation rate decrease greatly.The axial circulation capability of axial flow impeller PBT35-0.8-2 produced by optimization is better than A310,which has low energy consumption and high discharge.(4)Broken helical-ribbon(BHR)impellers for high viscosity fluid were optimized for global optimum by multi-objective optimization.According to the optimization results,the outer blade angle is the main factor influencing the power number and average axial flow number.The increase of outer blade angle not only enhances the axial circulation capability,but also leads to higher energy consumption.The inner blade angle has an influence on flow around it,while the clearance between impellers can affect the fluctuation of velocity distribution.Compared with double helical ribbon(DHR),the optimized BHR can improve the flow and shear distribution in the center of the tank,while the mixing efficiency increases greatly as the Wv of optimized BHR is 33.5%less than that of DHR.(5)The holes distribution of the distributor of fluidized bed was optimized with multi-objective optimization strategy.Uniform distribution of holes leads to high particle packing along the wall of fluidized bed and generates big bubbles in the center.Similar result is observed when big holes are placed in the center.Distribution with small holes in the center could reduce the particle packing along the wall,yet it severely weakens the fluidization in the center.The optimized distributor can avoid the generation of the big bubbles,which is beneficial for the interaction between the gas and solid phase.Compared with those traditional distributors,the optimized distributor could efficiently prevent the generation of big bubbles and particle packing,as is validated by its pressure drop and fluctuation.