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The existing coal mine equipment digital twin modeling method mainly focuses on single equipment modeling. It lacks three machine coupling collaborative relationship analysis. In order to solve the above problems, the paper puts forward three machine digital twin and collaborative modeling method for fully mechanized working face. By adopting an intelligent modeling method, the method constructs agent-based models of a coal mining machine, a hydraulic support and a scraper conveyor which comprise a sensing unit, a control unit and an execution unit. The method constructs corresponding visual models according to a three-dimensional modeling process. The method drives the three-dimensional models to move by the intelligent models. The combination of the two forms a digital twin model of three machines. A discrete event modeling method is used to construct a collaborative process model covering the interaction process of the three machine digital twin model. The three machine mining process is sorted out according to the time sequence to form a three machine collaborative process time sequence table. The digital twin model is used to describe the state and behavior of the three machines in fully mechanized mining and to simulate the calculation at the individual level. The collaborative process model is used to represent the sequential action transformation between digital twin models and realize the deduction of the whole three machine collaborative process. The simulation of rocker lifting and lowering for the digital twin model of the shearer is carried out. The simulation results show that compared with the measured data of real equipment, the model error is small, an average error of rocker arm dip angle is 2.3°. The simulation of continuous column lifting action for the digital twin model of hydraulic support is carried out. The simulation results show good consistency between the model and real equipment. Compared with the measured data of the real equipment, the average angle error is 0.14° and the average stroke error is 6.3 mm. Combined with the actual production log of the coal mine, the virtual and real simulation experiment of the three machine collaborative model is carried out. The results show that the three machine digital twin model of the fully mechanized working face and real equipment realize mutual mapping. The simulation results are close to the real records. The three machine collaborative model can accurately reflect the collaborative mining process. The method of three machine digital twin and collaborative modeling for fully mechanized working face provides a new idea for the digital twin modeling of fully mechanized coal mining equipment and its collaborative relationship.

In order to improve the uniformity of the horizontal magnetic induction on the target surface, a cathode target configuration with a cylindrical permanent magnet inside and some cuboidal permanent magnets outside arranged roundly was designed for circular magnetron sputtering. The magnetic field was simulated by COMSOL software and verified by measurement. The experimental results were basically consistent with the simulation results. The magnetic field of the circular plane was distributed uniformly, and met the basic requirements of magnetic induction i.e. 20-50 mT for magnetron sputtering. The target utilization rate reached 40%-50%, and the heat dissipation capacity was improved to a certain extent. [ABSTRACT FROM AUTHOR]

It is valuable for soil and water loss control and its benefits evaluation to understand the relationship between rainfall and soil erosion process. In order to make clear what rainfall type accelerates soil erosion on slopes of red soil in south part of China, and to ascertain the response of soil erosion intensity to rainfall characteristic under various rainfall types, data of meteorology and hydrology of 134 individual rainfalls in experimental plots on bare slopes of red soil in north part of Jiangxi Province were collected and analyzed. The amount, duration and intensity of rainfall were selected as the characteristic indices for erosive rainfall. Two methods including quick clustering and discriminant clustering were introduced to classify the rainfall types resulting in soil erosion. Pearson correlation analysis was then used to find the main indices that contributed the most to the slope soil erosion. Further, Mann-Kendall test and the other statistics method were used to determine the relationship between soil erosion intensity and the rainfall characteristic indices under different rainfall types. The results showed that the erosive rainfall in north part of Jiangxi Province could be classified into three types: type A (high frequency, short duration, minor amount of rainfall, and strong rainfall intensity), type B (medium frequency, medium duration, medium amount of rainfall, and medium rainfall intensity) and type C (low frequency, long duration, great amount of rainfall, and low rainfall intensity). Soil erosion on bare slopes of red soil in south part of China was mainly caused by type A. During the process of individual rainfall, soil erosion on bare slopes of red soil was mainly affected by the joint influences of rainfall intensity and amount, the former resulted in erosion change directly through the closest index - maximum 30 min rainfall intensity, the latter had indirectly effects by changing the former. With the increase of maximum 30 min rainfall intensity, soil erosion occurred remarkably different properties at rainfall intensity of 15 mm/h. The soil erosion increased relatively slowly before that critical point but increased rapidly after the point. Generally, soil erosion intensity increased with the amount of rainfall, whereas the erosion ability of different rainfall types varied, which followed the pattern: type A > type B > type C. Excluding the influence of rainfall happened in earlier time, the erosion intensity on bare slopes of red soil had a significant power function relationship with both the maximum 30 min rainfall intensity and the rainfall amount, however, the exponents and coefficients were different when different rainfall types occurred. It has been proven that this model is not only best for intensive rainfall with short duration, but also runs very well while applying to erosion prediction for all three rainfall types - the values of multiple correlation coefficient and the Nash-Suttclife efficiency coefficient were both above 0.9, and the average relative error was less than 25%. In conclusion, this study is very helpful both in exploring further red soil erosion laws and in process-based prediction model establishment. [ABSTRACT FROM AUTHOR]

This paper examined a case study of hydrological model for identifying parameter uncertainty by using three sensitivity analysis methods: HSY algorithm, linear regressional method and coupling analysis method. The results showed that optimal algorithms cannot give a sound explanation for complexity of model structure and identifying model parameters via uncertainty analysis methods presented an effective alternative to understand model system.

Parameters identification is achieved through the minimization of objective function based on model outputs and the observed data. Because of ever increasing complexity of environmental-models, there are significant difficulty for conventional optimal methods to present a global optimization. On the contrast, however, direct optimization algorithms are widely developed in recent years due to increasing computer efficiency and show promising applications. Four direct optimal algorithms, i.e. CRS algorithm, SCE UA algorithm, SA algorithm and Annealing-Simplex algorithm, were thus selected in this paper to compare their performances via case studies.