Document: NRC Regulatory Guide
Document ID: e0d690ec-277f-4fe2-b92f-7f95d0f589a7
Document Type: regulatory_guide
Title: Preparing Probabilistic Fracture Mechanics (Rev. 0)
Source: NRC Regulatory Guide Division 1
Source URL: https://www.nrc.gov/docs/ML2133/ML21334A158.pdf
Revision Date: 2023-05
Chapter: 
Section ID: RG-1.245
CFR Part: 
CFR Title: 

Content:
s of model realizations will result in different estimates. This type of uncertainty contributes to uncertainty in the true value of the quantity of interest and is often summarized using the sampling variance. sensitivity analysis The study of how uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model input. sensitivity studies PFM analyses that are conducted under credible alternative assumptions. simulation The execution of a computer code to mimic an actual system. Typically, comprises a set of model realizations. RG 1.245 Revision 0, Page 29 software quality assurance A planned and systematic pattern of all actions necessary to provide adequate confidence that a software item or product conforms to established technical requirements; a set of activities designed to evaluate the process by which the software products are developed or manufactured. surrogate A function that predicts outputs from a model as a function of the model inputs. Also known as response surface, metamodel, or emulator. uncertainty propagation Quantifying the uncertainty of a model’s responses that results from the propagation through the model of the uncertainty in the model’s inputs. validation The process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. variance The second moment of a probability distribution, defined as E(X-μ)2, where μ is the first moment of the random variable X. A common measure of variability around the mean of a distribution. verification The process of determining whether a computer program (“code”) correctly solves the mathematical-model equations. This includes code verification (determining whether the code correctly implements the intended algorithms) and solution verification (determining the accuracy with which the algorithms solve the mathematical-model equations for specified quantities of interest).