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:
the response. input Data or parameters that users can specify for a model; the output of the model varies as a function of the inputs, which can consist of physical values (e.g., material properties, tolerances) and model specifications (e.g., spatial resolution). local sensitivity analysis A sensitivity analysis that is relative to location in the input space chosen and not for the entire input space. model A representation of a physical process that allows for prediction of the process’ behavior. outputs A value calculated by the model given a set of inputs. parameter A numerical characteristic of a population or probability distribution. More technically, the variables used to calculate and describe frequencies and probabilities. probabilistic A characteristic of an evaluation that considers the likelihood of events. quantity of interest A numerical characteristic of the system being modeled, the value of which is of interest to stakeholders, typically because it informs a decision. Can refer to either a physical quantity that is an output from a model or a given feature of the probability distribution function of the output of a deterministic model with uncertain inputs. random variable A variable, the values of which occur according to some specified probability distribution. realization The execution of a model for a single set of input parameter values. risk-informed A characteristic of decision making in which risk results or insights are used together with other factors to support a decision. sampling The process of selecting some part of a population to observe, so as to estimate something of interest about the whole population. sampling uncertainty The uncertainty in an estimate of a quantity of interest that arises due to finite sampling. Different sets 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