Elimination mechanism of coal and gas outburst based on geo‑dynamic system with stress–damage–seepage interactions

Coal and gas outburst is a complex dynamic disaster during coal underground mining.Revealing the disaster mechanism is of great signifcance for accurate prediction and prevention of coal and gas outburst.The geo-dynamic system of coal and gas outburst is proposed.The framework of geo-dynamic system is composed of gassy coal mass,geological dynamic environment and mining disturbance.Equations of stress–damage–seepage interaction for gassy coal mass is constructed to resolve the outburst elimination process by gas extraction with boreholes through layer in foor roadway.The results show the occurrence of outburst is divided into the evolution process of gestation,formation,development and termination of geo-dynamic system.The scale range of outburst occurrence is determined,which provides a spatial basis for the prevention and control of outburst.The formation criterion and instability criterion of coal and gas outburst are established.The formation criterion F1 is defned as the scale of the geo-dynamic system,and the instability criterion F2 is defned as the scale of the outburst geo-body.According to the geo-dynamic system,the elimination mechanism of coal and gas outburst—‘unloading+depressurization’is established,and the gas extraction by boreholes through layer in foor roadway for outburst elimination is given.For the research case,when the gas extraction is 120 days,the gas pressure of the coal seam is reduced to below 0.4 MPa,and the outburst danger is eliminated efectively.

An Improved Differential Evolution Whale Algorithm for Economic Load Distribution

An improved optimization algorithm combining the differential evolution algorithm and the whale algorithm is proposed for the problem of not being able to get rid of the local optimum in the economic load distribution algorithm. The algorithm adopts a nonlinear convergence strategy, a crossover strategy of differential evolution and the introduction of an elimination mechanism, which balances the global search and local exploitation ability of the algorithm and improves the accuracy of the solved optimal solution. The 13-unit and 40-unit systems are selected for economic load distribution calculation, and the experimental results show that the proposed improved algorithm is superior in distributing the economic load of the power system and can effectively reduce the economic cost.

Bionic Attitude Transformation Combined with Closed Motion for a Free Floating Space Robot

In order to realize the small error attitude transformation of a free floating space robot,a new method of three degrees of freedom（ DOF） attitude transformation was proposed for the space robot using a bionic joint. A general kinematic model of the space robot was established based on the law of linear and angular momentum conservation. A combinational joint model was established combined with bionic joint and closed motion. The attitude transformation of planar,two DOF and three DOF is analyzed and simulated by the model,and it is verified that the feasibility of attitude transformation in three DOF space. Finally,the specific scheme of disturbance elimination in attitude transformation is presented and simulation results are obtained.Therefore,the range of application field of the bionic joint model has been expanded.

Plastic Not Welcome

Kenya seeks to eliminate plastic packaging,an environmental scourge on a national and even continental scaleJOHN Onyango lives in Nairobi,Kenya＇s capital.As he comes out of a downtown supermarket on an afternoon in October,the 61-year-old mechanic is carrying fruit in a recyclable cloth bag.

An improved fruit fly optimization algorithm for solving traveling salesman problem

The traveling salesman problem(TSP), a typical non-deterministic polynomial(NP) hard problem, has been used in many engineering applications. As a new swarm-intelligence optimization algorithm, the fruit fly optimization algorithm(FOA) is used to solve TSP, since it has the advantages of being easy to understand and having a simple implementation. However, it has problems, including a slow convergence rate for the algorithm, easily falling into the local optimum, and an insufficient optimization precision. To address TSP effectively, three improvements are proposed in this paper to improve FOA. First, the vision search process is reinforced in the foraging behavior of fruit flies to improve the convergence rate of FOA. Second, an elimination mechanism is added to FOA to increase the diversity. Third, a reverse operator and a multiplication operator are proposed. They are performed on the solution sequence in the fruit fly's smell search and vision search processes, respectively. In the experiment, 10 benchmarks selected from TSPLIB are tested. The results show that the improved FOA outperforms other alternatives in terms of the convergence rate and precision.