基于机器学习的螺旋流动过冷沸腾CHF预测研究  

Research on Prediction of Subcooled Flow Boiling CHF for Spiral Flow Based on Machine Learning

作　　者：颜建国 郑书闽 郭鹏程[1] 赵莉 王帅[1] 刘坤 朱旭涛 Yan Jianguo;Zheng Shumin;Guo Pengcheng;Zhao Li;Wang Shuai;Liu Kun;Zhu Xutao(State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China,Xi’an University of Technology,Xi’an,710048,China;School of Energy&Architecture,Xi’an Aeronautical Institute,Xi’an,710077,China)

机构地区：[1]西安理工大学西北旱区生态水利国家重点实验室,西安710048 [2]西安航空学院能源与建筑学院,西安710077

出　　处：《核动力工程》2023年第3期65-73,共9页Nuclear Power Engineering

基　　金：国家自然科学基金项目(51909213);陕西省教育厅科研计划项目(21JY029);陕西高校青年科技创新团队(2020-29);陕西省自然科学基础研究计划项目(2022JM-211)。

摘　　要：过冷沸腾广泛应用于以国际热核聚变实验堆(ITER)为代表的高热流冷却场合。本文聚焦高热流、螺旋流动条件下水的过冷沸腾临界热流密度(CHF)的预测方法,建立了该类工况下的过冷沸腾CHF实验数据库。选用了4种典型机器学习模型:反向传播(BP)神经网络、遗传算法(GA)-BP神经网络、径向基函数(RBF)神经网络和极限学习机(ELM);利用传统的经验关联式和新兴的机器学习方法对螺旋流动过冷沸腾CHF进行预测研究。经与实验数据库对比,结果表明,相关机器学习模型能够有效预测螺旋流动过冷沸腾CHF,其预测性能相较于传统的经验关联式有大幅提升,其中ELM模型预测效果最优,平均绝对误差和均方根误差分别为2.79%和4.22%。研究成果为高热流螺旋流动过冷沸腾CHF的准确预测提供了新途径。Subcooled boiling is widely used in cooling applications with high heat fluxes represented by International Thermonuclear Experimental Reactor(ITER).In this paper,predictions on the critical heat flux(CHF)of subcooled water boiling under high heat flux and swirl flow conditions are focused and a database of subcooled boiling CHF is established.Machine learning methods are applied,in which four typical machine learning models are adopted,namely Back Propagation(BP)neural network,Genetic Algorithm(GA)-BP neural network,Radial Basis Function(RBF)neural network and Extreme Learning Machine(ELM).The results indicate that machine learning models can effectively predict subcooled boiling CHF with swirling flow,and the prediction performances are obviously promoted,comparing with traditional empirical correlations.Among typical machine learning models,the ELM model possesses the best performance,with the MAE and RMSE are equal to 2.79%and 4.22%,respectively.The results provide a new path to making accurate predictions on the CHF for subcooled boiling under high heat flux and swirling flow conditions.

关 键 词：临界热流密度(CHF) 过冷沸腾 机器学习 传热 两相流 

分 类 号：TL331[核科学技术—核技术及应用] TK124[动力工程及工程热物理—工程热物理]