Nuclear Techniques ›› 2015, Vol. 38 ›› Issue (7): 70606-070606.doi: 10.11889/j.0253-3219.2015.hjs.38.070606

• NUCLEAR ENERGY SCIENCE AND ENGINEERING • Previous Articles    

Application of BP neural network in DNBR prediction

HUANG Yu LIU Junqiang LIU Le   

  1. (Shanghai Branch, China Nuclear Power Design Co., Ltd. (Shenzhen), Shanghai 200241, China)
  • Received:2015-02-10 Revised:2015-03-09 Online:2015-07-10 Published:2015-07-10

Abstract: Background: In safety analysis of pressurized water reactor (PWR), departure from nucleate boiling ratio (DNBR) is usually calculated by three codes: a system transient analysis code, a heat flux calculation code and a subchannel analysis code, or by simplified model through a partial derivative approximation of the core DNB limit lines, but either procedure has problems of cumbersome or low accuracy. Purpose: The aim of this study is to gain a simple DNBR calculation method with high accuracy. Methods: A 3-layers back propagation (BP) neural network was proposed with a training data set to quickly predict DNBR using four variables of reactor coolant system (nuclear power, core inlet temperature, mass flow rate and pressure). Results: The error of the developed BP network is very small, and has similar results compared with the subchannel code calculations in two typical events. Conclusion: The trained BP network is accurate enough to be used in predicting DNBR, even in transient conditions.

Key words: DNBR, Neural network, BP algorithm, Accident analysis