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THE TREATMENT OF ISI UNCERTAINTY IN EXTREMELY LOW PROBABILITY OF RUPTURE

机译:在极低的破裂概率中处理ISI不确定性

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The U.S. Nuclear Regulatory Commission (NRC) in cooperation with the nuclear industry is constructing an improved probabilistic fracture model for piping systems that in the past have not been susceptible to known degradation processes that could lead to pipe rupture. Recent operating experience with primary water stress corrosion cracking (PWSCC) has challenged this prior position of leak-before-break and which has now become known as "extremely Low Probability of Rupture" (xLPR). This paper focuses on the xLPR model's treatment of uncertainty for in-service inspection. In the xLPR model, uncertainty is classified as either aleatory or epistemic, and both types of uncertainty are described with probability distributions. Earlier PFM models included aleatory, but ignored epistemic, uncertainty, or attempted to deal with epistemic uncertainty by use of conservative bounds. Thus, inclusion of both types of uncertainty in xLPR should produce more realistic results than the earlier models. This work shows that by including epistemic uncertainty in the xLPR ISI module, there can be a significant effect on rupture probability; however, this depends upon the specific scenarios being studied. Some simple scenarios are presented to illustrate those where there is no effect and those having a significant effect on the probability of rupture.
机译:美国核监管委员会(NRC)与核工业合作正在构建一种改进的管道系统的概率骨折模型,这在过去尚未易于易受可能导致管道破裂的降解过程。最近具有初级水分腐蚀裂缝(PWSCC)的经营经验已经挑战这种前后泄漏的前位,现在已被称为“破裂的极低概率”(XLPR)。本文重点介绍了XLPR模型对服务在役检查的不确定性的处理。在XLPR模型中,不确定性被归类为杀菌或认识症,并且两种类型的不确定性都用概率分布描述。早期的PFM模型包括梯级,但忽略了认识,不确定性,或试图通过使用保守范围来应对认知不确定性。因此,在XLPR中包含两种类型的不确定性应该产生比早期模型更逼真的结果。这项工作表明,通过在XLPR ISI模块中包括认知不确定性,对破裂概率可能有显着影响;但是,这取决于所研究的具体情景。提出了一些简单的情景以说明那些没有影响的人和对破裂概率产生显着影响的那些。

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