Nuclear Techniques ›› 2015, Vol. 38 ›› Issue (2): 20605-020605.doi: 10.11889/j.0253-3219.2015.hjs.38.020605

• NUCLEAR ENERGY SCIENCE AND ENGINEERING • Previous Articles     Next Articles

Reliability analysis of passive decay heat removal system of China lead-based research reactor

XIA Shaoxiong1,2 WANG Jiaqun2 PAN Xiaolei1,2 LI Yazhou2 HU Liqin1,2   

  1. 1(University of Science and Technology of China, Hefei 230026, China) 2(Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei 230031, China)
  • Received:2014-10-30 Revised:2014-11-21 Online:2015-02-10 Published:2015-02-02

Abstract: Background: Because of the safety and the competition in economy, Generation IV reactors represent the development tendency of innovative nuclear systems. Lead cooled fast reactor is a variety of Generation IV reactors and many of them around the world adopt passive systems to remove residual heat. Purpose: The driving force of passive system is approximate at the same level of resistance, so an analysis on the reliability of passive system becomes necessary. Methods: This study made some improvements of the response surface method and applied it to Reactor Vessel Air Cooling System (RVACS) of China lead-based research reactor (CLEAR-I). During the analysis, the process of removing residual heat of RVACS was simulated by Fluent in order to find out how inputs would affect the safety of reactor. On the base of a mass of simulations, this study established relationships between inputs and outputs to find failure probability of RVACS. Results: The advanced response surface method raised the sampling efficiency for small-probability events by as much as four times. Through this method, we got the failure probability of RVACS. Conclusion: The results showed that two of four sets RVACS pipes can safely remove residual heat of reactor during loss of power.

Key words: China lead-based research reactor (CLEAR-I), Reactor Vessel Air Cooling System (RVACS), Reliability analysis, Uncertainty