Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which...Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.展开更多
The preparation process of amorphous nanometer boron powders through combustion synthesis was investigated, and the effects of the reactant ratio, the heating agent and the milling rate on the activity and particle si...The preparation process of amorphous nanometer boron powders through combustion synthesis was investigated, and the effects of the reactant ratio, the heating agent and the milling rate on the activity and particle size of amorphous boron powders were studied. The results show that the boron powders exist in the form of an amorphous phase which has the crystallinity lower than 30.4%, and the panicle size of boron powder decreases with an increase of the high-energy ball milling rate. The purity of amorphous boron powder is 94.8% and panicle sizes are much smaller than 100 nm when the mass ratio of B2O3/Mg/KClO3 is 100：105：17 and the ball milling time is 20 min with the milling rate of 300 r/min. At the same time, the amorphous boron nano-fibers appear in the boron powders.展开更多
Permeability is a vital property of rock mass, which is highly affected by tectonic stress and human engineering activities. A comprehensive monitoring of pore pressure and flow rate distributions inside the rock mass...Permeability is a vital property of rock mass, which is highly affected by tectonic stress and human engineering activities. A comprehensive monitoring of pore pressure and flow rate distributions inside the rock mass is very important to elucidate the permeability evolution mechanisms, which is difficult to realize in laboratory, but easy to be achieved in numerical simulations. Therefore, the particle flow code （PFC）, a discrete element method, is used to simulate permeability behaviors of rock materials in this study. Owe to the limitation of the existed solid-fluid coupling algorithm in PFC, an improved flow-coupling algorithm is presented to better reflect the preferential flow in rock fractures. The comparative analysis is conducted between original and improved algorithm when simulating rock permeability evolution during triaxial compression, showing that the improved algorithm can better describe the experimental phenomenon. Furthermore, the evolution of pore pressure and flow rate distribution during the flow process are analyzed by using the improved algorithm. It is concluded that during the steady flow process in the fractured specimen, the pore pressure and flow rate both prefer transmitting through the fractures rather than rock matrix. Based on the results, fractures are divided into the following three types： I） fractures link to both the inlet and outlet, II） fractures only link to the inlet, and III） fractures only link to the outlet. The type I fracture is always the preferential propagating path for both the pore pressure and flow rate. For type II fractures, the pore pressure increases and then becomes steady. However, the flow rate increases first and begins to decrease after the flow reaches the stop end of the fracture and finally vanishes. There is no obvious pore pressure or flow rate concentration within type III fractures.展开更多
A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural...A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method.展开更多
基金Project(NS2013091)supported by the Basis Research Fund of Nanjing University of Aeronautics and Astronautics,China
文摘Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.
基金Project(51002025) supported by the National Natural Science Foundation of China
文摘The preparation process of amorphous nanometer boron powders through combustion synthesis was investigated, and the effects of the reactant ratio, the heating agent and the milling rate on the activity and particle size of amorphous boron powders were studied. The results show that the boron powders exist in the form of an amorphous phase which has the crystallinity lower than 30.4%, and the panicle size of boron powder decreases with an increase of the high-energy ball milling rate. The purity of amorphous boron powder is 94.8% and panicle sizes are much smaller than 100 nm when the mass ratio of B2O3/Mg/KClO3 is 100：105：17 and the ball milling time is 20 min with the milling rate of 300 r/min. At the same time, the amorphous boron nano-fibers appear in the boron powders.
基金Project（BK20150005） supported by the Natural Science Foundation of Jiangsu Province for Distinguished Young Scholars, China Project（2015XKZD05） supported by the Fundamental Research Funds for the Central Universities, China
文摘Permeability is a vital property of rock mass, which is highly affected by tectonic stress and human engineering activities. A comprehensive monitoring of pore pressure and flow rate distributions inside the rock mass is very important to elucidate the permeability evolution mechanisms, which is difficult to realize in laboratory, but easy to be achieved in numerical simulations. Therefore, the particle flow code （PFC）, a discrete element method, is used to simulate permeability behaviors of rock materials in this study. Owe to the limitation of the existed solid-fluid coupling algorithm in PFC, an improved flow-coupling algorithm is presented to better reflect the preferential flow in rock fractures. The comparative analysis is conducted between original and improved algorithm when simulating rock permeability evolution during triaxial compression, showing that the improved algorithm can better describe the experimental phenomenon. Furthermore, the evolution of pore pressure and flow rate distribution during the flow process are analyzed by using the improved algorithm. It is concluded that during the steady flow process in the fractured specimen, the pore pressure and flow rate both prefer transmitting through the fractures rather than rock matrix. Based on the results, fractures are divided into the following three types： I） fractures link to both the inlet and outlet, II） fractures only link to the inlet, and III） fractures only link to the outlet. The type I fracture is always the preferential propagating path for both the pore pressure and flow rate. For type II fractures, the pore pressure increases and then becomes steady. However, the flow rate increases first and begins to decrease after the flow reaches the stop end of the fracture and finally vanishes. There is no obvious pore pressure or flow rate concentration within type III fractures.
基金Project(51075289) supported by the National Natural Science Foundation of ChinaProject(20122014) supported by the Doctor Foundation of Taiyuan University of Science and Technology,China
文摘A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method.
