Simulation of pre-cooling filling process of liquid oxygen system based on parameter optimization of Kriging
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摘要:
针对惰性气体吹除作用下的低温液体火箭发动机液氧系统预冷充填过程，建立了一种两组分两相充填模型。由于包含7个控制方程，模型参数复杂度提升，直接开展参数优化存在优化效率低、参数矩阵非线性强的制约因素。基于Kriging代理模型采用粒子群优化算法，高效寻得两组分两相充填模型在多因素耦合影响下的全局最优参数组合，有效提升了模型的仿真精度。对某型发动机液氧系统预冷充填的仿真研究表明：仿真结果与试验数据的相对误差仅2.75%；喷注器氧容腔内的压力爬升曲线呈现台阶上升特征，且随入口压力的增大液氧充填速率加快。
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关键词:
- Kriging代理模型 /
- 预冷充填 /
- 液氧 /
- 粒子群优化 /
- 两相
Abstract:For the pre-cooling filling process of liquid oxygen system of cryogenic liquid rocket engines under the action of inert gas blowing, a two-component two-phase filling model was established. Due to the inclusion of 7 control equations, the complexity of the model parameters increased, and there were constraints on the low optimization efficiency and strong nonlinearity of the parameter matrix for direct parameter optimization. Based on the Kriging surrogate model, the particle swarm optimization algorithm was used to efficiently find the global optimal parameter combination of the two-component two-phase filling model under the influence of multi-factor coupling, which effectively improved the simulation accuracy of the model. The simulation study on the pre-cooling and filling of the liquid oxygen system of a certain type of engine showed that the relative error between the simulation results and the test data was only 2.75%. The pressure climb curve in the liquid oxygen dome of injector showed the characteristics of step rise, and the liquid oxygen filling rate accelerated with the increase of inlet pressure.
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Key words:
- Kriging surrogate model /
- pre-cooling filling /
- liquid oxygen /
- particle swarm optimization /
- two-phase
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图 5 优化后仿真结果与试验数据对比
Figure 5. Comparison of the optimized simulation results with the experimental data
图 7 不同入口压力条件下的喷注器氧容腔压力曲线
Figure 7. History of pressure in the oxygen dome under different inlet pressures
图 8 不同入口压力条件下的喷注器氧容腔充填曲线
Figure 8. Filling rate in the oxygen dome under different inlet pressures
图 9 不同入口压力条件下管路4中充填曲线
Figure 9. Filling rate in pipe 4 under different inlet pressures
表 2 参数范围
Table 2. Range of parameters
参数 数值范围 nref /m−2 5000 ～500000 ΔTrefsup/K 2～50 ΔTrefsub/K 2～50 c 0.1～5 
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表 3 最优参数组合
Table 3. Optimal combination of parameters
参数 数值 nref/m−2 309884 ΔTrefsup/K 9.24 ΔTrefsub/K 40.4 c 2.13
下载: 导出CSV
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