报告详情
HIGH ACCURAY CHF PREDICTION USING NEWEST AI STRATEGIES
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更新：2024-09-04 21:19:50 浏览：89次
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摘要
One of the most important and challenging job in the two-phase thermohydraulic filed is the prediction of Critical Heat Flux (CHF) as it serves a critical role in preventing the heater surface form burnout, thus ensuring the safety of the system. As the phenomena itself is so complex, a universal theory to explain all the CHF related topic is still not feasible. Thus, different methods such as empirical or semi-empirical correlations, look-up tables (LUT), CFD methods are proposed to predict CHF. Though people have tried to improve the accuracy of the CHF prediction, traditional methods always face the problem of low accuracy and universalness. AI strategies, which are developed in the recent years, have shown the great potential in accurate prediction of CHF. Compared to traditional methods like LUT, AI can greatly enhance the accuracy, showing the tremendous potential of the method. In this study, we used three different AI strategies to predict CHF, it was found that transformers outweigh among the three methods, achieving the best performance.
关键词
Critical heat flux; Heat transfer; Deep learning; Neural network
报告人
KAI WANG
Associate Professor THE SUN YA-SEN UNIVERSITY稿件作者
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重要日期
-
会议日期
09月23日
2024
至09月25日
2024
-
09月24日 2024
报告提交截止日期
-
09月25日 2024
注册截止日期
主办单位
Harbin Engineering University (HEU)
联系方式
- Prof. WANG Xiang
- xi******@hrbeu.edu.cn
历届会议
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2016年09月26日 中国 Chengdu,China
8th International Symposium on Symbiotic Nuclear Power Systems for 21st Century -
2016年09月26日 中国 Chengdu,China
第八届21世纪和谐核电系统国际会议 -
2010年08月23日 中国 哈尔滨市
第三届21世纪和谐核电系统国际会议（ISSNP2010）
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