双层壁冷却结构综合冷却效率和相对压力损失多目标优化

Multi-Objective Optimization of a Double-Wall Cooling Structure for Overall Cooling Effectiveness and Relative Pressure Drop

在典型燃烧室工作环境下,针对特定双层壁冷却结构,以综合冷却效率和相对压力损失为优化目标,采用径向基神经网络构建数学模型,通过遗传优化算法实现多目标优化,旨在提高其气动和传热性能。在给定的双层壁冷却结构参数范围内,优化后双层壁冷却结构的最大综合冷却效率为0.89,而相对压力损失可降至0.17%。

In a typical combustion chamber environment,the overall cooling effectiveness and relative pressure drop of a specific double-wall cooling structure were set as the optimization indicators,and the mathematical model was built by radial basis function neural network.Through a genetic optimization algorithm,multi-objectives optimization were achieved to improve its aerodynamic and heat transfer performance.Within the given parameter range of the double-wall cooling structure,the overall cooling effectiveness of double-wall cooling structure is optimized to 0.89 for the maximum comprehensive cooling efficiency index,and the relative pressure drop of double-wall cooling structure can be reduced to 0.17%for the minimum relative pressure drop index.