Multiphase Flow Characteristics Analysis And Structural Optimization Of Static Mixer

Static mixer is a kind of high-efficiency mixing equipment without moving parts,it can use the mixing unit fixed in the pipeline to change the flow state of the fluid,so that the medium in the pipe is mixed or dispersed,because of its high efficiency,low energy consumption,small size,continuous work and other advantages,is widely used in petroleum,chemical,biological and other fields.Since the mixing effect of the static mixer is determined by the structure of the mixing unit,and the mixing unit cannot be removed after fabrication,the analysis and structural optimization of the mixing effect for the REAC inlet static mixer is particularly important.In order to improve the mixing effect of static mixer,scholars at home and abroad are committed to studying the mixing structure of various forms of static mixer,and this paper is based on the previous research,using numerical simulation(CFD)method to improve the multiphase flow mixing effect under the premise of ensuring its pressure drop.Firstly,the research status of static mixer at home and abroad is introduced,the appropriate turbulence model and multiphase flow model are selected,the appropriate boundary conditions are set according to the working conditions,the multiphase flow mixing process of the static mixer is simulated and calculated through mesh independence verification,and the trace pattern,velocity cloud map,turbulence intensity cloud map,water fraction cloud and wall shear stress cloud are analyzed to study the multiphase flow characteristics of the static mixer.The monitoring surface is selected,and the monitoring data of the monitoring surface is output,the mixing index is calculated,and the mixing process in the pipeline is explored.Secondly,taking the mixing index as the index,the univariate analysis method was used to study the influence of operation parameters and mixing element structure parameters on the mixing effect and pressure drop respectively.Among them,the operating parameters are inlet 1 flow rate and inlet 2 flow rate,and the structural parameters of the mixing unit are the torsion angle of the mixing unit,the spacing of adjacent mixing units,the number of mixing units,the thickness of the mixing unit,the opening diameter of the mixing unit and the length to diameter ratio of the mixing unit.In addition,the influence of the water injection position on the mixing effect is also considered.Based on the results of univariate analysis,a four-factor four-level orthogonal test is designed,and the optimal parameter combination under this method is obtained by range analysis.The results of the orthogonal experiment were used as the sample data of the BP neural network,and 16 sets of data were fitted,and the error rate of the fitted data was less than 4%.The genetic algorithm was used to optimize the fitted neural network,and the optimization results were compared with the numerical simulation results,and the error rate was 3.6%.Finally,the numerical simulation results of the structure and original structure obtained by the genetic algorithm and orthogonal test are compared,and the results show that the structure mixing effect obtained by BP neural network-genetic algorithm is the best,and the mixing effect of the original structure is the worst.The parameters of the best mixing effect were combined with a torsion angle of 133°,a distance of 8mm between adjacent mixing elements,a hole diameter of 35 mm,and a length-diameter ratio of 1.25,which reduced the mixing index by 62.1% compared with the original structure,and the optimized pressure was reduced to the original structure.The work done provides a reference for the optimization of static mixers.