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In order to solve the problems of high resistance and high power consumption of rotary tillage and land preparation, the rotary blade is studied based on theoretical analysis, simulation and field experiment in this paper. First, a wedge drag reduction rotary blade is designed based on the theoretical force model of cutting tools in mechanical soil dynamics. Second , the three-dimensional model of the national rotary blade and the wedge drag reduction rotary blade is established by using the Inventor software and the simulation experiment is carried on. The cutting soil model of 2 kinds of rotary blades is established by using HyperMesh software, and the material parameters, boundary constraints and working parameters are defined. On this basis, the soil cutting process, stress and cutting resistance are analyzed. It is proved that the wedge drag reduction rotary blade design is reasonable. In order to verify whether the wedge drag reduction rotary blade meets the strength requirement, the stress of the rotary blades is analyzed, and the cutting resistance of the national rotary blade and the wedge drag reduction rotary blade are compared. Third, field comparative experiments are carried out on national rotary blade and wedge drag reducing rotating blade with the evaluation indexes of torque, power consumption and soil breakage. The results show that the cutting resistance of the wedge drag reduction rotary blade is smaller than that of the national rotary blade; the maximum stress of the national rotary blade is 35.68 MPa and the maximum stress of the wedge drag reduction rotary blade is 29.49 MPa, which is less than that of the national rotary blade and far less than the yield strength of the material 430 MPa. On the premise of ensuring the strength of the blade body, the weight of the wedge drag reduction rotary blade is reduced by about 50 g, which is about 8.3% lower than that of the national rotary blade. The maximum cutting resistance of the national rotary blade is 530 N, the average cutting resistance is 375.5 N, and the maximum cutting resistance of the wedge drag reduction rotary blade is 510 N, the average cutting resistance is 335.5 N, the average cutting resistance of the wedge drag reduction rotary blade is 10.65% lower than that of the national rotary blade, which proves the feasibility of the wedge drag reduction rotary blade designed; The average torque of the wedge drag reduction rotary blade is 11.35% lower than that of the national rotary blade. In the working process of rotary blades, the average power consumption of the national rotary blade is 74.2 kW, the average power consumption of the wedge drag reduction rotary blade is 67.3 kW, and the average power consumption of the wedge drag reduction rotary blade is 9.29% lower than that of the national rotary blade. The average breaking rate of soil of the national rotary blade is 75%, and the average breaking rate of wedge drag reduction rotary blade is 79%, which is 4% higher than that of the national rotary blade; After continuous 33 hm2 tillage, rotary blades did not break, and the average wear of the national rotary blade is 98.5 g, the average wear of the wedge shaped drag reduction rotary blade is 97.3 g, the wear difference is 1.3%, and the wear degree is the same. The wedge drag reduction rotary blade can effectively solve the problems of high resistance and high power consumption of rotary blade, which is helpful to accelerate the development of arable land machinery, improve the mechanization level of cultivated land, and reduce the production cost of crops. [ABSTRACT FROM AUTHOR]

The cluster-cluster aggregation (CCA) model bridges the study of colloid aggregation by computer simulation and laboratory experiment. Two distinct and limiting regimes of irreversible colloid aggregation have been identified by computer simulation with the CCA model. One regime is diffusion-limited cluster aggregation (DLCA) corresponding to the rapid colloid aggregation. The other is reaction-limited cluster aggregation (RLCA) corresponding to the slow colloid aggregation. The simulations of the two regimes are both start with N non-overlapping identical particles distributed randomly in a cubic box with side-lengths of L. A three dimensional array, hypothetically named Cube[L][L][L], was usually used to represent the cubic box. Each particle in the cubic box occupies an element of the three dimensional array and are labeled with a different integer. When particles and/or clusters collide and aggregate, all particles in the resulting cluster are modified with the same label (one of them). The progression of Brownian movement and aggregation are realized by updating the labels of the corresponding array elements. However, a critical issue in this kind of simulation is how to efficiently distinguish all of the particles in any selected cluster only based on the three dimensional array Cube[L][L][L] when the cluster is to be moved. Similarly, there are difficulties in the process of collision detection to locate all neighboring positions of the cluster. The traditional method must perform exhaustive search in the whole system, what's more, this kind of exhaustive search will repeated over and over again in the simulation progression. In this paper, the traditional on-lattice CCA algorithm is optimized by improving the storage structure to reduce the time complexity, in which the simulation system is represented by a three dimensional array, while the clusters in the system are simultaneously stored by the linked lists respectively in programming. Another one dimensional array Cluster[N] is used to organize the linked lists and store the basic attributes of the clusters in the system. Initially, N linked lists, each only has one node, are created for the N randomly placed particles. After a cluster is moved, its particles is examined to determine whether any other clusters have been contacted via nearest neighbor occupancy. If aggregation does occur after the collision detection, the simple operation is to link the corresponding clusters. After an aggregation, the array Cluster should be indexed simultaneously because there may be some vacant linked lists. In the later random selection for the potential movement, these vacant linked lists should not be in the candidate lists. For the indexing, a one dimensional array Index[N] is used to store the non-vacant linked list subscripts of the array Cluster[N]. The current length of the Index is the number of the remaining clusters in the system. For example, if the new generated random number for the random selection is k, the label of the next moving cluster should be Index [k], and the linked list of this cluster is exactly linked by Cluster [Index[k]]. From this entry, all the particles in the cluster can be easily accessed. And then, the positions of the six neighboring boxes of each particle in the cluster can also be accessed by the element subscripts of the array Cube, which is needed for the collision detection. Brownian motion, collision detection and aggregation as the basic operations in the CCA simulation are all improved based on the compounded data structure. The results show that the new algorithm achieves linear time complexity from three cubed time complexity. This is a great contribution for researchers in large scale simulation of fractal aggregation. [ABSTRACT FROM AUTHOR]