Process Parameters Optimization And Mechanical Simulation In Densification Of Corn Stalk Powder

China has an annual corn stalk productivity about 265 million t. Its loose natural form makes the high cost in transportation and storage through direct use, which limits the commercial use of the material. To overcome this obstacle, Densification of corn stalk powder is the effective way to meet the technical requirement. Research of compact mechanism and related technology is of great significance for promoting the development and utilization of biomass resources.To explore mechanical behavior and the impact of compression process parameters and material properties on pellet quality, corn stalk powder is taken as the research material in the research. The main achievements are as follows:(1) Central composite design experiment design is put into use.with the application of typical compact equipment to compress crushed corn straw,and the feed motor speed, clearance adjusting angle between the ring die and roller, and moisture content of materials is selected to study the pellet unit density, bulk density, moisture content of pellet, energy consumption per mass. Analysis shows that, in addition to feed motor speed has insignificant influence on the pellet density, all the three experimental factors have significant impact on the bulk density and the energy consumption per mass, for the pellet moisture content and compression force, the influence of three experimental factors were not significant. According to multi-objective optimization in the unit density, bulk density and energy consumption per mass with index weight coefficient of 2,2,1 respectively, when the feed motor speed is of 450 r/min, clearance adjusting angle between the ring die and roller is of 11.25°and material moisture content of 22.5%, the multi-objective optimal values are:unit density is of 0.8110 g/cm3, bulk density is of 425.505 kg/m3, energy consumption per mass is of 78.32 (kW·h) /t. Verification test has a relative error less than 3%.(2) Single-hole forming test is applied to study the impact of process parameters on the corn stralk pellet density, pellet moisture content and energy consumed per unitmass. Six factors have important influence on experiment index are selected based on Plackett-Burman factorial experiment design, that is temperature, feed amount, hole diameter, compression speed, moisture content, and pre-load. Combination with the single factor experiment, the uniform design experiment method for the selected six factors of multiple factors and levels is applied. Pellet density regression model analysis showed that, in addition to the pre-load factors, hole diameter, cavity temperature, compression speed, feed amount, moisture content all have a significant effect on the unit density model; And all test factor regression model has significant impact on the water content of pellet model, and hole diameter and mold cavity temperature have a significant impact on energy consumption per mass regression model.By set the same weight index of pellet density, moisture content and energy consumption per mass model, the multi-objective optimization of particle density is of 1.719 g/cm3, moisture content is of 11.09%, energy consumption per mass of 1.3797 J/g (38.33 (kW·h)/t) with the hole diameter of 8 mm, cavity temperature of 93.81 ℃, the compressive bar compression speed of 100 mm/min, feeding in every stroke of 0.4 g, pre-load of 1kpa and the material moisture content of 20%. Verification test has a relative error 10.5%,1.26% and 17.4% respectively.(3) The generalized Maxwell model is found suitable for describing the constitutive properties of the material based on single-hole forming test of corn stalk powder.In closed-end compression mode, the maximum compressive force in each stroke versus has an exponential growth trend.(4) Based on the theory of soft ball contact model and discrete element method, the material compression process was simulated by combining artificial neural network algorithm, with the compression force simulated by the discrete element method as network input, normal stiffness, tangential stiffness and friction coefficient of contact particles can be reversely calculated. By Combining the two kinds of computing technology, the actual stress relaxation test is simulated, the simulation results with the measured results are in good consistency.This study provide theoretical basis and practical guidance for compression machine design and compact process optimization, the discrete element simulation method combined with artificial neural network provides a new technical means and analysis method for biomass densification.