大破口LOCA事故ASTRUM最佳估算分析方法优化研究

Study on ASTRUM optimization for large break LOCA analysis

ASTRUM(Automated Statistical Treatment of Uncertainty Method)分析方法是美国西屋公司开发的能够自动执行不确定性计算的最佳估算方法。在该方法中,对于部分对大破口LOCA(Loss of Coolant Accident)事故计算结果具有重要影响的参数,采用了参数保守性确认分析的办法,以确定其保守的取值组合。然后,在此基础上执行对其它参数抽样的ASTRUM最佳估算。这种做法对于不同的事故工况或抽样工况得到的保守性参数取值组合可能不同,具有一定的偶然性,在固定这些参数保守组合的基础上再对其余参数抽样进行最佳估算,可能会导致ASTRUM计算结果出现一定程度的偏差。本文取消了原ASTRUM方法中参数保守性确认分析这一环节,通过开发自编的BE_SAMPLE抽样程序,对原参数保守性确认分析中的重要参数进行抽样,执行了全参数的抽样统计分析,并给出了优化结论,它可以为后续ASTRUM方法的优化和研究提供参考。

Background： The ASTRUM （Automated Statistical Treatment of Uncertainty Method） methodology is developed by Westinghouse. In this method, some important parameters for large break loss of coolant accident （LBLOCA） analysis are treated conservatively to get a conservative set, which is called confirmatory study. And the value set of parameters is then used to generate the reference transient input deck of ASTRUM calculation. The value set may be varied in different sampling cases. However, the ASTRUM is executed based on one value set of some parameters, although other parameters are sampled. The result of the ASTRUM calculation may be not very exact. Purpose： The aim of this study is to reduce the uncertainty and conservatism, and optimize the ASTRUM. Methods： The parameters concerned in the confirmatory study of ASTRUM were sampled by BE_SAMPLE code developed by this paper for each ASTRUM case. The optimized ASTRUM is executed in company with other sampled parameters. Results： The results of the original and optimized ASTRUM calculations are compared, and the peak cladding temperature （PCT） calculated by new ASTRUM is lower than the original result. Conclusion： The study on ASTRUM optimization reduces the uncertainty caused by confirmatory study, which makes the ASTRUM calculation much more precise.