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Quantile Regressions Applied to Pressurized Water Reactor CHF Correlation Safety Criteria

Ross Pivovar, Ole Wieckhorst

Nuclear Technology / Volume 205 / Number 7 / July 2019 / Pages 945-950

Regular Technical Paper / dx.doi.org/10.1080/00295450.2018.1548220

Received:August 18, 2018
Accepted:November 9, 2018
Published:June 11, 2019

All licensable critical heat flux (CHF) correlations/regressions models must determine and demonstrate a “design limit” that bounds the CHF correlation predicted/measured residuals via a 95/95 tolerance limit. This is a quick and straightforward calculation when the residuals are well behaved, exhibiting no trends and no heteroscedasticity. However, as models become increasingly complex and as required parameter ranges become more extended, the likelihood of nonconservative subregions increases. A suggested solution from the open literature is the overly conservative approach of basing the design limit on the subregion with the largest variance. This approach unavoidably overly constrains the overall regression model and often is too conservative for subregions due to a loss in degrees of freedom. Quantile regressions alleviate these issues by smoothly varying the design limit based on covariates and adapting to each subregion. Thus, a quantile regression achieves the objective of appropriately bounding all subregions without overly biasing the overall regression model.

 
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