Abstract
The system designed to accomplish the engraving process of a rotating band projectile is called the gun engraving system. To obtain higher performance, the optimal design of the size parameters of the gun engraving system was carried out. First, a fluid–solid coupling computational model of the gun engraving system was built and validated by the gun launch experiment. Subsequently, three mathematic variable values, like performance evaluation indexes, were obtained. Second, a sensitivity analysis was performed, and four high-influence size parameters were selected as design variables. Finally, an optimization model based on the affine arithmetic was set up and solved, and then the optimized intervals of performance evaluation indexes were obtained. After the optimal design, the percent decrease of the maximum engraving resistance force ranged from 6.34% to 18.24%; the percent decrease of the maximum propellant gas temperature ranged from 1.91% to 7.45%; the percent increase of minimum pressure wave of the propellant gas ranged from 0.12% to 0.36%.
Highlights
The gun launch process can be introduced as follows: first, the propellant particles burn and produce propellant gas, and the propellant gas pushes projectile base to move along translation–rotation trajectory to the projectile leaves the muzzle
The sensitivity analysis was performed, and four high-influence size parameters were selected as design variables
The projectile rotating bands are squeezed by the bore surface and cut by riflings, which will lead to the plastic deformation and damage of the rotating bands
Summary
The gun launch process can be introduced as follows: first, the propellant particles burn and produce propellant gas, and the propellant gas pushes projectile base to move along translation–rotation trajectory to the projectile leaves the muzzle. Jiang et al [15] transformed the nonlinear objective function and constraints into an approximate linear model through first-order Taylor series expansion using the sequential linear programming method. Wu et al [20] proposed an interval uncertainty optimization method combining the Chebyshev surrogate model and higher-order Taylor expansion. It could effectively inhibit the interval expansion problem caused by interval arithmetic and could directly calculate the upper and lower bounds of interval functions. By using affine arithmetic to calculate the uncertain objective function and constraint, its interval bounds can be calculated directly so that the two-layer nested uncertain optimization can be transformed to a single-layer uncertain optimization problem. Modeling of the Gun Engraving System and Experimental Investigation of Engraving Process
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