基于三维应力分量的管道热疲劳监测数据分析

Analysis of Thermal Fatigue Monitoring Data of Piping Based on Three-dimensional Stress Component

美国ASME规范第Ⅲ卷和法国RCC-M等规范均基于交变应力强度进行核一级部件疲劳寿命分析。受制于技术发展的限制,管道热疲劳分析中多采用单个方向应力或应力强度进行载荷循环峰谷值探测与载荷循环配对,但交变应力强度峰谷值探测与载荷循环配对情况不应基于任意两个时刻的单个方向应力或应力强度数值之差进行分析,而应基于单元体任意时刻6个应力分量进行评估(尤其对于各应力分量达到峰谷值时存在时间差,或主应力方向发生偏转的情况)。基于核电厂核一级管道的监测数据,探讨建立一套基于格林函数计算热应力和极值窗口进行交变应力强度计算的管道热疲劳详细分析方法,并通过核电厂某一管嘴的热疲劳分析,详细介绍了该分析方法的应用过程。典型案例分析结果表明,峰谷值探测与循环配对中未采用三维应力分量和极值窗口法时,计算获得交变应力强度的非保守度达9.66%。

The fatigue life of nuclear gradeⅠcomponents is assessed based on an alternating stress intensity according to American ASME Code VolumeⅢand the French RCC-M Code.Due to the limitations of technological development,single directional stress or stress intensity was often used for the peak and valley detection and load cycle statistics in early piping thermal fatigue analyses.However,the results of the peak and valley detection and load cycle statistics should not be analyzed based on the difference between the single directional stress or stress intensity values at two moments,instead,it should be assessed based on the six stress components of the unit body at any moment(especially for the case where there is a time difference or direction of main stress deflects when each stress component reaches the peak or valley value).Based on the monitoring data of the nuclear gradeⅠpiping in a nuclear power plant,establishment of a method of the detailed thermal fatigue analysis for calculation of alternating stress intensity based on calculation of thermal stress and extreme value window according to Green′s function was discussed,and the application process of this method was introduced in detail through the thermal fatigue analysis of a nozzle in the nuclear power plant.The analysis results of typical cases show that the non-conservative factor is about 9.66%for the alternating stress intensity in the fatigue analysis when the methods of the three-dimensional stress components and the extreme value window are not used in deriving the peak and valley detection and load cycle statistics.