摘要
对三通管内冷热水的掺混流动过程进行试验研究,得到在30℃温差、不同进口流量比条件下掺混流域的温度场数据;提出基于BP神经网络的温度场预测模型,并将预测结果与实测数据进行对比。结果表明:掺混流域温度场特性的预测结果与试验数据吻合度较高,对温度振荡功率谱密度的分析也得到同样的结果,这对进一步研究管道热波动引起的管道热应力,以及进行管道热疲劳分析与寿命评估具有指导意义。
Test study on the cold and hot mixed flow in three-way pipe is carried out, and the temperature field data of mixing basin under 30 ℃ temperature difference and different inlet flow ratio is obtained; the temperature field prediction model based on BP neural network is proposed,and the prediction results are compared with measured data. The results show that the prediction of temperature field characteristics of mixing basin in mixing process is highly consistent with the test data. The same results of temperature oscillation power spectral density analysis are obtained. It is instructive to further study the thermal stress of pipes caused by thermal fluctuation,as well as thermal fatigue analysis and life evaluation.
作者
李泽伟
蒋彦龙
王合旭
陈冀
王瑞琪
LI Zewei;JIANG Yanlong;WANG Hexu;CHEN Ji;WANG Ruiqi(College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;609 Research Institute of Chinese Aeronautical Establishment, Nanjing 211106, China)
出处
《计算机辅助工程》
2018年第2期30-35,共6页
Computer Aided Engineering
基金
南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20170123)
中央高校基本科研业务费专项基金
关键词
三通管
热掺混
温度振荡
BP神经网络
温度场预测
功率谱密度
three-way pipe
themlal mixing
temperature oscillation
BP neural network
temperature field prediction
power spectral density
