Wall Temperature Optimization of the Flame Tube Float-wall Based on the NN and GA
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摘要: 为了使得浮动瓦块结构具有更好的冷却效果,开展了浮动瓦块壁温优化研究。在对浮动瓦块结构壁温热-流耦合分析的基础上,利用神经网络建立瓦块结构尺寸参数与瓦块壁温的全局性映射关系,获得瓦块壁温优化问题所需的目标函数值。然后,采用遗传算法对瓦块结构进行优化设计。通过优化分析获得了冷却效果更好的浮动壁结构,使其壁温指数降低了4.19%。结果表明:基于神经网络和遗传算法的优化技术应用在浮动瓦块结构壁温优化设计中是有效、合理的。Abstract: In order to make the float-wall structure has better cooling effect,this paper carried out optimization studies about the float-wall's wall temperature.On the base of heat-flow coupling analysis on the float-wall's temperature,a nonlinear mapping function from float-wall's parameters to float-wall's temperature was constructed with BP neural networks(NN).The genetic algorithm(GA) was used to obtain the objective function values in optimal design of structures.Optimal design of float-wall was put forward by using genetic algorithms to obtain the more effective cooling structure;the temperature index was decreased by 4.19%.The results show that the optimization technology applied in optimal design of float-wall's wall temperature is effective and reasonable.
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Key words:
- float-wall /
- flame tube /
- optimization /
- neural network /
- genetic algorithm
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