The frequent occurrence of rockburst and the difficulty in predicting were considered in deep engineering and underground engineering.In this work,laboratory experiments on rockburst under true triaxial conditions wer...The frequent occurrence of rockburst and the difficulty in predicting were considered in deep engineering and underground engineering.In this work,laboratory experiments on rockburst under true triaxial conditions were carried out with granite samples.Combined with the deformation characteristics of granite,acoustic emission(AE)technology was well applied in revealing the evolution law of micro-cracks in the process of rockburst.Based on the comprehensive analysis of acoustic emission parameters such as impact,ringing and energy,the phased characteristics of crack propagation and damage evolution in granite were obtained,which were consistent with the stages of rock deformation and failure.Subsequently,based on the critical point theory,the accelerated release characteristics of acoustic emission energy during rockburst were analyzed.Based on the damage theory,the damage evolution model of rock under different loading conditions was proposed,and the prediction interval of rock failure time was ascertained concurrently.Finally,regarding damage as an intermediate variable,the synergetic prediction model of rock failure time was constructed.The feasibility and validity of model were verified.展开更多
The setting of attention parameters plays a role in the performance of synergetic neural network based on PFAP model. This paper first analyzes the attention parameter setting algorithm based on award-penalty learning...The setting of attention parameters plays a role in the performance of synergetic neural network based on PFAP model. This paper first analyzes the attention parameter setting algorithm based on award-penalty learning mechanism. Then, it presents an improved algorithm to overcome its drawbacks. The experimental results demonstrate that the novel algorithm is better than the original one under the same circumstances.展开更多
The problem of optimal aeroassisted symmetric transfer between elliptical orbits is concerned.The complete trajectory is assumed as consisting of two impulsive velocity changes at the beginning and the end of an inter...The problem of optimal aeroassisted symmetric transfer between elliptical orbits is concerned.The complete trajectory is assumed as consisting of two impulsive velocity changes at the beginning and the end of an interior atmospheric subarc,where the vehicle is controlled via the lift coefficient and thrust.The corresponding dynamic equations are built and bounded controls are considered.For the purpose of optimization computation,the equations are normalized.In order to minimize the total fuel consumption,the geocentric radius of initial elliptical transfer orbital perigee and controls during atmospheric flight should all be optimized.It is an optimal control problem which involves additional parameter optimization.To solve the problem,a two-level optimization method denoted by ＂genetic algorithm ＋ Gauss pseudospectral method＂ is adopted：the genetic algorithm is used for parameter optimization and the Gauss pseudospectral method is used for optimal control problems.The flow chart of simulation is given.On this basis,the issue of more realistic modeling with two finite-thrust subarcs in the nonatmospheric part of the trajectory is simultaneously addressed.The orbital transfer problem is transformed to three continuous optimal control problems,and the constraints at different times are given,which are respectively solved by using the Gauss pseudospectral method.The obtained numerical results indicate that the optimal thrust control is of bangbang type.The minimum-fuel trajectory in the atmosphere consists of aeroglide,aerocruise and aeroglide.They are compared with the results of pure impulsive model,and the conclusions that a significant fuel saving will be achieved by synergetic maneuver are drawn.展开更多
基金Projects(52074294,51574246,51674008)supported by the National Natural Science Foundation of ChinaProjects(2017YFC0804201,2017YFC0603000)supported by the National Key Research and Development Program of ChinaProject(2011QZ01)supported by the Fundamental Research Funds for the Central Universities,China。
文摘The frequent occurrence of rockburst and the difficulty in predicting were considered in deep engineering and underground engineering.In this work,laboratory experiments on rockburst under true triaxial conditions were carried out with granite samples.Combined with the deformation characteristics of granite,acoustic emission(AE)technology was well applied in revealing the evolution law of micro-cracks in the process of rockburst.Based on the comprehensive analysis of acoustic emission parameters such as impact,ringing and energy,the phased characteristics of crack propagation and damage evolution in granite were obtained,which were consistent with the stages of rock deformation and failure.Subsequently,based on the critical point theory,the accelerated release characteristics of acoustic emission energy during rockburst were analyzed.Based on the damage theory,the damage evolution model of rock under different loading conditions was proposed,and the prediction interval of rock failure time was ascertained concurrently.Finally,regarding damage as an intermediate variable,the synergetic prediction model of rock failure time was constructed.The feasibility and validity of model were verified.
基金Supported by Fujian Natural Science Foundation(A0110010).
文摘The setting of attention parameters plays a role in the performance of synergetic neural network based on PFAP model. This paper first analyzes the attention parameter setting algorithm based on award-penalty learning mechanism. Then, it presents an improved algorithm to overcome its drawbacks. The experimental results demonstrate that the novel algorithm is better than the original one under the same circumstances.
基金supported by the National High Technology Research and Development Program of China(863Program)(2011AA0469)
文摘The problem of optimal aeroassisted symmetric transfer between elliptical orbits is concerned.The complete trajectory is assumed as consisting of two impulsive velocity changes at the beginning and the end of an interior atmospheric subarc,where the vehicle is controlled via the lift coefficient and thrust.The corresponding dynamic equations are built and bounded controls are considered.For the purpose of optimization computation,the equations are normalized.In order to minimize the total fuel consumption,the geocentric radius of initial elliptical transfer orbital perigee and controls during atmospheric flight should all be optimized.It is an optimal control problem which involves additional parameter optimization.To solve the problem,a two-level optimization method denoted by ＂genetic algorithm ＋ Gauss pseudospectral method＂ is adopted：the genetic algorithm is used for parameter optimization and the Gauss pseudospectral method is used for optimal control problems.The flow chart of simulation is given.On this basis,the issue of more realistic modeling with two finite-thrust subarcs in the nonatmospheric part of the trajectory is simultaneously addressed.The orbital transfer problem is transformed to three continuous optimal control problems,and the constraints at different times are given,which are respectively solved by using the Gauss pseudospectral method.The obtained numerical results indicate that the optimal thrust control is of bangbang type.The minimum-fuel trajectory in the atmosphere consists of aeroglide,aerocruise and aeroglide.They are compared with the results of pure impulsive model,and the conclusions that a significant fuel saving will be achieved by synergetic maneuver are drawn.
