摘要详情

ID / 提交时间

69 / 2024-07-13 14:44:56

标题

FLOW DISTRIBUTION PREDICTION MODEL OF ANNULAR FUEL BASED ON GA-BP NEURAL NETWORK

关键字

GA-BP Neural Network,Flow Distribution,Annular Fuel

主题及专题

TRACK 4: MODELING & SIMULATION

状态

全文录用

作者

Yu Zou / Harbin Engineering University

Shouxu Qiao / Harbin Engineering University

Jinyang Li / Harbin Engineering University

SICHAO Tan / 哈尔滨工程大学

RuiFeng Tian / Harbin Engineering University

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%.