多种参数不确定性分析方法在AP1000 LBLOCA中的适用性研究

参数不确定性分析是利用合理的方法来建立输入参数不确定性和输出结果不确定性之间的响应关系，以能更真实地模拟电厂状态，在兼顾安全性的前提下，提高电厂的经济性。本文通过对AP1000 LBLOCA分析，发现随机取样统计方法、敏感性分析数值方法、传统误差传递分析方法均能提供较大的燃料包壳峰值温度（PCT）安全裕度，对核电厂经济性提高过程中参数不确定性量化方法的选择具有参考意义。此外，随机取样统计方法利用数理统计理论分析，减少了分析过程中的保守性，故在3种方法之中可提供最大的安全裕度。相较传统的参数包络分析方法，随机取样统计方法可额外提供的PCT裕度约100 K，而敏感性分析数值方法和传统误差传递分析方法额外提供的PCT裕度则约50～60 K。

Application of Status Uncertainty Analysis Methods for AP1000 LBLOCA Calculation

Parameter uncertainty analysis is developed by using the reasonable method to establish the response relations between input parameter uncertainties and output uncertainties. The application of the parameter uncertainty analysis makes the simulation of plant state more accuracy and improves the plant economy with reasonable security assurance. The AP1000 LBLOCA was analyzed in this paper and the results indicate that the random sampling statistical analysis method, sensitivity analysis numerical method and traditional error propagation analysis method can provide quite large peak cladding temperature （PCT） safety margin, which is much helpful for choosing suitable uncertainty analysis method to improve the plant economy. Additionally, the random sampling statistical analysis method applying mathematical statistics theory makes the largest safety margin due to the reducing of the conservation. Comparing with the traditional conservative bounding parameter analysis method, the random sampling method can provide the PCT margin of 100 K, while the other two methods can only provide 50-60 K.