The model describing the dependence of the mechanical properties on the chemical composition and as deformation techniques of tungsten heavy alloy is established by the method of improved the backpropagation neural ne...The model describing the dependence of the mechanical properties on the chemical composition and as deformation techniques of tungsten heavy alloy is established by the method of improved the backpropagation neural network. The mechanical properties＇ parameters of tungsten alloy and deformation techniques for tungsten alloy are used as the inputs. The chemical composition and deformation amount of tungsten alloy are used as the outputs. Then they are used for training the neural network. At the same time, the optimal number of the hidden neurons is obtained through the experiential equations, and the varied step learning method is adopted to ensure the stability of the training process. According to the requirements for mechanical properties, the chemical composition and the deformation condition for tungsten heavy alloy can be designed by this artificial neural network system.展开更多
The appearance of high-entropy alloys (HEAs) makes it possible for a material to possess both high strength and high ductility. It is with great potential to apply HEAs under extreme conditions such as in the penetrat...The appearance of high-entropy alloys (HEAs) makes it possible for a material to possess both high strength and high ductility. It is with great potential to apply HEAs under extreme conditions such as in the penetration process. In this paper, experiments of WFeNiMo HEA and tungsten heavy alloy (WHA) projectiles penetrating medium-carbon steel were conducted by using the ballistic gun and two-stage light-gas gun that can accelerate projectiles to impact velocities ranging from 1162 m/s to 2130 m/s. Depth of penetration (DOP) at elevated impact velocities of HEA and WHA projectiles were obtained firstly. Combined with the macroscopic and microscopic analysis of the residual projectiles, the transition of the penetration mode of the WFeNiMo HEA projectile was identified systemically. The experimental results indicated that the penetration mode of the HEA projectile changes from self-sharpening to mushrooming with the increase of impact velocity, while for the WHA projectile, the penetration mode is always mushrooming. The microstructure of the residual HEA projectiles showed that the phases tangle with each other and the morphology of the microstructure of the phases differs in the two penetration modes. Besides, the evolution of shear bands and fractures varies in the two modes. The evolution of the microstructure of HEAs causes the sharp-pointed nose to disappear and the HEA projectile ultimately becomes blunt as the impact velocity increases.展开更多
Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.H...Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.However,due to high density and elastic stiffness of WHAs,cutting forces will be higher than for most of the metals and alloys;thus,making the machining operation challenging.The machining variable,namely,cutting force components are significantly influenced by the cutting parameters.This paper makes use of Oxley’s predictive analytical model in conjunction with Johnson-Cook constitutive equation to predict forces under different speed and feed combinations during machining of 95 W tungsten heavy alloy.The cutting forces,so predicted by Ml,are considered as input data for the optimization of cutting parameters(cutting speed and feed)using Response Surface Method(RSM).展开更多
文摘The model describing the dependence of the mechanical properties on the chemical composition and as deformation techniques of tungsten heavy alloy is established by the method of improved the backpropagation neural network. The mechanical properties＇ parameters of tungsten alloy and deformation techniques for tungsten alloy are used as the inputs. The chemical composition and deformation amount of tungsten alloy are used as the outputs. Then they are used for training the neural network. At the same time, the optimal number of the hidden neurons is obtained through the experiential equations, and the varied step learning method is adopted to ensure the stability of the training process. According to the requirements for mechanical properties, the chemical composition and the deformation condition for tungsten heavy alloy can be designed by this artificial neural network system.
基金This work is funded by the National Natural Science Foundation of China(No.11790292)the NSAF Joint Fund(No.U1730101).
文摘The appearance of high-entropy alloys (HEAs) makes it possible for a material to possess both high strength and high ductility. It is with great potential to apply HEAs under extreme conditions such as in the penetration process. In this paper, experiments of WFeNiMo HEA and tungsten heavy alloy (WHA) projectiles penetrating medium-carbon steel were conducted by using the ballistic gun and two-stage light-gas gun that can accelerate projectiles to impact velocities ranging from 1162 m/s to 2130 m/s. Depth of penetration (DOP) at elevated impact velocities of HEA and WHA projectiles were obtained firstly. Combined with the macroscopic and microscopic analysis of the residual projectiles, the transition of the penetration mode of the WFeNiMo HEA projectile was identified systemically. The experimental results indicated that the penetration mode of the HEA projectile changes from self-sharpening to mushrooming with the increase of impact velocity, while for the WHA projectile, the penetration mode is always mushrooming. The microstructure of the residual HEA projectiles showed that the phases tangle with each other and the morphology of the microstructure of the phases differs in the two penetration modes. Besides, the evolution of shear bands and fractures varies in the two modes. The evolution of the microstructure of HEAs causes the sharp-pointed nose to disappear and the HEA projectile ultimately becomes blunt as the impact velocity increases.
文摘Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.However,due to high density and elastic stiffness of WHAs,cutting forces will be higher than for most of the metals and alloys;thus,making the machining operation challenging.The machining variable,namely,cutting force components are significantly influenced by the cutting parameters.This paper makes use of Oxley’s predictive analytical model in conjunction with Johnson-Cook constitutive equation to predict forces under different speed and feed combinations during machining of 95 W tungsten heavy alloy.The cutting forces,so predicted by Ml,are considered as input data for the optimization of cutting parameters(cutting speed and feed)using Response Surface Method(RSM).
