Deep pine shovel is one of the protective tillage machines for the soda saline-alkali soil in Northeast China. Among them, the subsoiling shovel blade is one of the main working components in the deep pine shovel. The liquid lubrication and drag reduction have been explored in the self-developed deep pine shovel with the structure of leaf vein-like inner channel in the early stage for the saline and alkaline land improvement. This study aims to determine the effect of self-lubrication and drag reduction of deep pine shovel on the application of the modified liquid layer. The modified agent was also utilized for the layering of self-lubrication and drag reduction in the process of liquid flow rate within the leaf vein-like inner channel. The simulation analysis was adopted as the computational fluid dynamics with the physical test. A systematic investigation was then implemented to clarify the influence of structural parameters (inner channel aperture diameter, aperture spacing, and the number of apertures), and working parameters (inlet flow velocity of the main channel) on the liquid outlet velocity of the branch outlet. Firstly, the simulation model was established with the initial and boundary conditions, meshing and irrelevant verification. The single factor test was then carried out, where the structural and working parameters were taken as the test factors. The optimal level range was also achieved after optimization. The initial conditions were set for the simulation: an inner channel branch outlet hole diameter of 6 mm, a hole spacing of 90-110 mm, a number of holes of 4-6, and a main channel inlet flow rate of 5-7 m/s. After that, the Box-Behnken test was designed and then carried out, according to the single-factor simulation test. The target value was taken as the maximum liquid outflow velocity at the outlet of each branch. The structural and working parameters were optimized for the multi branch outlet pipes in the leaf vein shaped inner channel. The analysis of variance (ANOVA) of the test was used to establish the second-order regression equation between the influencing factors and the branch outlet flow rate. The optimal combination of simulation parameters was obtained to optimize and solve the equation. Finally, a field test was also conducted to verify the model. The results show that the better performance of the improved model was achieved for the further prediction analysis of the target mean flow rate. The ANOVA results showed that the influencing factors of the mean flow rate were ranked in the descending order of the main channel inlet flow rate, the number of branch exit holes in the inner channel, the spacing of branch exit holes in the inner channel. The second-order regression equation was optimally solved to take the maximum average flow velocity at the branch outlet as the target value. The optimal combination of parameters was achieved in the inner channel branch outlet hole spacing of 110 mm, the number of holes at the inner channel branch outlet of 4, the inlet flow velocity of the main channel of 7 m/s, and the hole diameter of the inner channel branch outlet of 6mm. Moreover, the average flow velocity at the branch outlet of the inner channel was 3.264 m/s under the optimal conditions. The physical test was then performed on the optimal combination of parameters for the leaf vein-like inner channel. The maximum flow velocity of 2.971 m/s was found in the inner channel branch outlet. There was the average error of 8.97% between the simulation and the physical test. Therefore, the reliability of numerical simulation was verified to examine the optimized design of the leaf-vein-like inner channel structure. The finding can provide the theoretical reference for the coupled deep-pine and chemical improvement using the leaf-vein-like inner channel with the multi-branch outlet pipe structure in soda saline soils.

Accurate simulation of the olive fruits can be often required to optimize the harvesting equipment using the Discrete element method (DEM). In this study, the sensitivity analysis of Young’s modulus was performed on the olive fruits using DEM. The geometric model of the olive fruits was constructed to appropriately select the contact parameters. Four varieties of olive fruits were taken as the Picual, Frantoi, Leecio, and E'zhi No.8. Then, 5-, 9- and 13-sphere particle models were established for the olive varieties using multi-sphere modeling. Meanwhile, the rest models were constructed using the automatic filling function in EDEM software. Multi-sphere models were obtained with 13 spheres, as well as the models with the 0 and 2 levels of smoothness. Six DEM multi-sphere models in total were developed per variety. A comparison was then made on the volume ratios between manual-filling and auto-filling models. The volumes of the model types closely resembled the actual shape of the seed particle. Additionally, the manually filled models used fewer spheres, indicating the more efficient model with less complexity. Various contact parameters of the olive fruits were also measured, such as Young's modulus, the static friction coefficient, the rolling friction coefficient, and the restitution coefficient. The rotating hub test was performed to verify the accuracy of the models. A comparison was then carried out on the actual experiment and simulation. The results indicated that the dynamic angle of the repose was increasingly closer to the measured values after experiments, as the number of combined spheres decreased. The optimal number of five spheres was determined for the manually filled models of each variety, in terms of the CPU computation time. Moreover, the stacking test was also conducted on the particle-wall collision. A systematic investigation was then made to explore the influence of Young’s modulus on the movement of individual particles and particle assembly. It was found that the stiffness represented by the DEM model increased significantly, as Young’s modulus value increased. The overlap between particle particles was reduced to increase the stack height. As such, the higher Young’s modulus corresponded to the smaller time step. Consequently, the overall simulation also increased the CPU computation time. Young’s modulus was found to significantly impact the collision behavior of individual particles, in terms of the collision time and overlap between particles. As Young’s modulus increased, the overlap between particle-particle or particle-boundary collisions decreased, which in turn resulted in a reduction in the number of contact points. This finding also highlighted the relationship between the material properties of the olive fruits and their interaction in the simulated environment. Furthermore, the relationship between DEM simulation and Young’s modulus can also provide a multi-dimensional evaluation of the suitability of the models. The contact parameters and DEM models are of significant practical value for the optimization of olive harvesting equipment. The accuracy of these models can be improved under various values of Young’s modulus. These insights can also be applied to the interaction of the granular materials in engineering applications.