Discrete Element Method Simulation Of Vertical Screw Conveying Based On Proper Orthogonal Decomposition

With the rapid development of the world’s bulk cargo transportation industry,vertical screw conveying equipment is widely used in the loading and unloading process of modern port bulk cargo terminals due to its simple structure,small footprint,and closed transportation.The actual conveying situation of vertical screw conveying equipment is relatively complicated,and its structural parameters and operating parameters will affect the conveying performance to varying degrees.Analyzing the influence of these parameters on the characteristics of vertical screw conveying,improving productivity and reducing energy consumption has good practical engineering significance and theoretical research value.In this dissertation,the vertical screw conveying process in the screw ship unloader is taken as the research object,and the discrete element simulation and numerical analysis methods are used to study and analyze the influence of structural parameters and operating parameters on the conveying performance.The proper-orthogonal decomposition-agent model method develops a discrete element reduction model to predict the state and performance of vertical screw conveyance to reduce the computational cost of discrete element analysis.The specific work is summarized as follows:(1)Based on similar theory and dimensional analysis method,a simplified model of the vertical screw conveying section was established,and productivity and energy consumption were determined as the main performance indicators in the vertical screw conveying process.The operating parameters of the vertical screw conveying process were selected such as speed,filling rate,and feed.The speed and structural parameters pitch and blade width were used as experimental factors and a suitable factor level was designed.A discrete element simulation experiment was designed through a 2~k factorial experiment to conduct a complete simulation study of the vertical screw conveying process.(2)Combine discrete-element simulation experiments and numerical analysis methods to perform single-factor analysis and analysis of variance on the simulation results,study the effects of different experimental factors on the productivity and energy consumption in the transportation process,and determine the influence components of each parameter;fit by polynomial response surface A prediction model of productivity and energy consumption is obtained,with an error of less than5%.The prediction model is used to determine the optimal parameter combination of each parameter in the transportation process to maximize the productivity and minimize the energy consumption.(3)Design experiments within the parameter range and perform principal component analysis to obtain the component variance contribution dataset and factor load dataset for productivity and energy consumption,respectively.Principal component analysis is used to determine the principal components obtained after dimensionality reduction,which are used instead of the original indicators to interpret the data results;through factor load analysis,the relationship between the principal components and the original variables is studied,and the performance of the original variables is further analyzed Degree of influence.Based on the proper orthogonal decomposition-agent model method,the construction process of the discrete element reduction model is developed.Taking the vertical screw conveying process as an example,the axial velocity distribution,radial velocity distribution,and particle kinetic energy distribution of the particle flow are quickly predicted.To verify the validity and accuracy of the discrete-element reduced-order model and propose related improvement strategies to further optimize the accuracy of the reduced-order model.