This paper presents an actuator used for the trajectory correction fuze,which is subject to high impact loadings during launch.A simulation method is carried out to obtain the peak-peak stress value of each component,...This paper presents an actuator used for the trajectory correction fuze,which is subject to high impact loadings during launch.A simulation method is carried out to obtain the peak-peak stress value of each component,from which the ball bearings are possible failures according to the results.Subsequently,three schemes against impact loadings,full-element deep groove ball bearing and integrated raceway,needle roller thrust bearing assembly,and gaskets are utilized for redesigning the actuator to effectively reduce the bearings’stress.However,multi-objectives optimization still needs to be conducted for the gaskets to decrease the stress value further to the yield stress.Four gasket’s structure parameters and three bearings’peak-peak stress are served as the four optimization variables and three objectives,respectively.Optimized Latin hypercube design is used for generating sample points,and Kriging model selected according to estimation result can establish the relationship between the variables and objectives,representing the simulation which is time-consuming.Accordingly,two optimization algorithms work out the Pareto solutions,from which the best solutions are selected,and verified by the simulation to determine the gaskets optimized structure parameters.It can be concluded that the simulation and optimization method based on these components is effective and efficient.展开更多
This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material poin...This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material point method(GIMP). Random fields are simulated using Cholesky matrix decomposition(CMD) method and Latin hypercube sampling(LHS) method, which represent material properties discretized into sets of random soil shear strength variables with statistical properties. The approach is applied to landslides in clayey deposits under undrained conditions with random fields of undrained shear strength parameters, in order to quantify the uncertainties of post-failure behavior at different scales of fluctuation(SOF) and coefficients of variation(COV). Results show that the employed approach can reliably simulate the whole landslide process and assess the uncertainties of runout motions. It is demonstrated that the natural heterogeneity of shear strength in landslides notably influences their post-failure behavior. Compared with a homogeneous landslide model which yields conservative results and underestimation of the risks, consideration of heterogeneity shows larger landslide influence zones. With SOF values increasing, the variances of influence zones also increase, and with higher values of COV, the mean values of the influence zone also increase, resulting in higher uncertainties of post-failure behavior.展开更多
基金The authors would like to acknowledge National Defense Pre-Research Foundation of China(Grant No.41419030102)to provide fund for conducting experiments.
文摘This paper presents an actuator used for the trajectory correction fuze,which is subject to high impact loadings during launch.A simulation method is carried out to obtain the peak-peak stress value of each component,from which the ball bearings are possible failures according to the results.Subsequently,three schemes against impact loadings,full-element deep groove ball bearing and integrated raceway,needle roller thrust bearing assembly,and gaskets are utilized for redesigning the actuator to effectively reduce the bearings’stress.However,multi-objectives optimization still needs to be conducted for the gaskets to decrease the stress value further to the yield stress.Four gasket’s structure parameters and three bearings’peak-peak stress are served as the four optimization variables and three objectives,respectively.Optimized Latin hypercube design is used for generating sample points,and Kriging model selected according to estimation result can establish the relationship between the variables and objectives,representing the simulation which is time-consuming.Accordingly,two optimization algorithms work out the Pareto solutions,from which the best solutions are selected,and verified by the simulation to determine the gaskets optimized structure parameters.It can be concluded that the simulation and optimization method based on these components is effective and efficient.
文摘This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material point method(GIMP). Random fields are simulated using Cholesky matrix decomposition(CMD) method and Latin hypercube sampling(LHS) method, which represent material properties discretized into sets of random soil shear strength variables with statistical properties. The approach is applied to landslides in clayey deposits under undrained conditions with random fields of undrained shear strength parameters, in order to quantify the uncertainties of post-failure behavior at different scales of fluctuation(SOF) and coefficients of variation(COV). Results show that the employed approach can reliably simulate the whole landslide process and assess the uncertainties of runout motions. It is demonstrated that the natural heterogeneity of shear strength in landslides notably influences their post-failure behavior. Compared with a homogeneous landslide model which yields conservative results and underestimation of the risks, consideration of heterogeneity shows larger landslide influence zones. With SOF values increasing, the variances of influence zones also increase, and with higher values of COV, the mean values of the influence zone also increase, resulting in higher uncertainties of post-failure behavior.
