UNCERTAINTY AND SENSITIVITY
4.5 Chapter Summary
This chapter describes the three forms of uncertainty related to fire modeling: parameter, model, and completeness uncertainty. Model and completeness uncertainty are closely related, and it would be impractical to evaluate them separately. The most practical way to quantify their combined effect is to compare model predictions with as many experimental measurements as possible in order to develop a robust statistical description of the model’s accuracy. The five models considered in this repor underwent a validation study (NUREG-1824 (EPRI 1011999)) in which their predictions were compared with measurements from a variety of full-scale
experiments. It is possible to take a given model’s prediction of a given quantity and determine a distribution for the “true” value of this quantity. Rather than reporting the result of a calculation as a single value, it is preferable to report the probability that the true value of a predicted quantity will exceed a given critical value.
Treatment of parameter uncertainty is dependent on the application. Some analyses, probabilistic risk assessments (PRAs) for example, employ relatively simple techniques to propagate the distribution of the HRR through the model. More complex forms of PRAs can involve a broad statistical sampling of input parameters from specified distributions. From a fire modeling perspective, some modeling tools are more amenable to the evaluation of parameter uncertainty given the complexity and computational times of some of these tools.
Deterministic applications usually consider “worst case” or “bounding” analyses, in which extreme, yet plausible, input parameters are used. In mathematical terms, all of these applications involve selecting parameters from relatively narrow or broad regions of the parameter “space.” It is often prohibitive to consider all possible combinations of input
parameters, which is why a simple form of sensitivity analysis, outlined in this chapter, can be used to extend the range of outcomes. Algebraic models may initially be used to indicate the extent to which all of the output quantities of interest are sensitive to changes in the specified HRR, reducing the need to re-run model simulations for an extensive number of values.
Over time, the V&V effort, documented in NUREG-1824 (EPRI 1011999), will be expanded to include comparisons with additional test data and new versions of the models. These updates will expand the validation range shown in Table 2-5 and ensure the availability of V&V
information for the latest versions of the models documented in this report. Model users should refer to the latest version of the V&V when conducting their fire modeling analyses. In general, the techniques documented in this chapter for analyzing uncertainty and sensitivity will remain applicable regardless of the V&V version being used for the analysis.
UNCERTAINTY AND SENSITIVITY
5
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