基于Fluent与GA-BP的筒弹充氮设备多参数优化

航天产品发射筒主要用于导弹运输和贮存，发射筒内部装配有导弹导轨、导弹、弹上电缆网及其他精密元器件，导弹运输与贮存对于发射筒需要特定的环境要求。针对现有的XX型号发射筒充氮设备置换工艺性能不佳问题，基于Fluent数值分析方法，仿真充氮设备在不同参数(充气压力、放气压力、保压时间)下对发射筒进行置换工艺时所需的时间和氮气消耗量；再利用GA-BP神经网络对各参数进行拟合，建立多输入多输出数学模型并用遗传算法寻找最优解，满足最小的置换工艺时间与氮气消耗量；最后调整充氮设备置换工艺的各个参数进行工程验证。实验表明，充氮设备多参数优化后对发射筒置换工艺时间减少，氮气消耗量降低，在一定程度上提高了工作效率并节省了成本。

Multi-parameter Optimization of Barrel Bomb Nitrogen Charging Equipment Based on Fluent and GA-BP

Launch tubes of aerospace products are mainly used for missile transportation and storage. Missile guide rails, missiles, cable nets and other precision components are installed inside the launch tubes. Missile transportation and storage require specific environmental requirements for the launch tubes. Aiming at the problem of poor performance of the existing nitrogen filling equipment replacement process of launch tubes, based on Fluent numerical analysis method, simulate the time and nitrogen consumption required by nitrogen charging equipment to replace the launcher under different parameters (inflation pressure, deflation pressure and holding time), then use BP neural network to fit the parameters, establish a multi-input multi-output mathematical model and use genetic algorithm to find the optimal solution, so as to meet the minimum replacement process time and nitrogen consumption. Finally, adjust the parameters of nitrogen charging equipment replacement process for engineering verification. The experiment shows that the replacement process time of the launcher by nitrogen charging equipment is reduced, the nitrogen consumption is reduced and increased to some extent.