报告详情
FLOW DISTRIBUTION PREDICTION MODEL OF ANNULAR FUEL BASED ON GA-BP NEURAL NETWORK
编号：38
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更新：2024-09-05 21:08:14 浏览：81次
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摘要
Annular fuel has dual coolant channels, which have the potential to increase the reactor power density while improving the safety margin. The coolant flow distribution between the inner and outer channels directly affects the heat transfer efficiency of the fuel channel. Regarding the measurement of flow distribution ratio (outer channel flux to total flux) is challenging, the development of calculation model is essential for acquiring flow distribution characteristics of annular fuel. In this study, a 5×5 annular fuel assembly was modeled based on computational fluid dynamics. The flow distribution ratio and pressure drop ratio were calculated under steady state, pulsating flow and rolling motion conditions, respectively. A flow distribution prediction model is established based on the GA-BP neural network with simulated data. The prediction results are consistent with that of the experiment, with an overall error of 2%.
关键词
GA-BP Neural Network,Flow Distribution,Annular Fuel
报告人
Yu Zou
PhD Candidate Harbin Engineering 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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