Document: NRC Regulatory Guide
Document ID: da2e0703-3488-44b0-b6d0-089aac7cae3d
Document Type: regulatory_guide
Title: Format and Content of Plant-Specific Pressurized Thermal Shock Safety Analysis Reports for Pressurized Water Reactors
Source: NRC Regulatory Guide Division 1
Source URL: https://www.nrc.gov/docs/ML0037/ML003740028.pdf
Revision Date: 2023-06
Chapter: 
Section ID: RG-1.154
CFR Part: 
CFR Title: 

Content:
dered a 68th percentile value. I n those cases i n which something other than a 68th percentile value i s chosen, discussion should center around the reasons f o r choosing the value used. Sensitivity factors should be obtained by dividing the through-wal 1 crack frequency obtained with the changed variable by the through-wall crack frequency obtained with each variable a t i t s mean value. Supply the s e n s i t i v i t y factors obtained f o r both positive and negative changes i n each o f the variables. The s e n s i t i v i t y factors obtained f o r changes made i n the PTS-adverse direction should be ranked according t o magnitude and provided i n table form. Uncertainty Analysis 7.2.1 Parameter Uncertainties Each step i n the p r o b a b i l i s t i c analysis should include an uncertainty anal- ysis. This should include uncertainty i n frequency o f occurrence o f a sequence, uncertainty i n temperatures and pressures reached during the sequence, including t h a t resulting from the nodal i z a t i o n scheme chosen as discussed i n Section 4.5, and uncertainty i n the fracture mechanics model for vessel f a i l u r e given the transients. For the following reasons, a Monte Carlo simulation i s appropriate for ,I portions of the PTS uncertainty analysis. O The temperature and pressure error di s t r i buti ons are not symmetric. O The fracture mechanics results are nonlinear with respect to variations i n input parameters, particularly the temperature and pressure time hi stories. O The results of the Monte Car10 analysis can indicate the shape of the output distribution. The Monte Carlo approach would involve four steps as described below: 1. Develop a statistical distribution for each variable used in the calculation - T h i s step will involve the representatioh of each variable as a distribution w i t h 5th and 95th percentiles as previously identified. The shapes of the distributions selected should be discussed. 2. Select a random value from each