Propagation of Model Form Uncertainty for Thermal Hydraulics using RANS Turbulence Models in Drekar
This document summarizes the results from a level 3 milestone study within the CASL VUQ effort. It demonstrates the propagation of model form uncertainty that arises from the presence of multiple turbulence models within the context of thermal hydraulics analyses. The lack of knowledge associated with an inability to a priori identify an appropriate turbulence model is modeled as discrete epistemic uncertainty. This approach provides an alternative to model selection processes, for use when data is unavailable or inadequate for reducing the model form uncertainty. In this case, the alternative is to propagate the model form uncertainty and report UQ results that include this epistemic uncertainty source alongside other parametric sources. The study calculates epistemic intervals on aleatory statistics for several quantities of interest, where the epistemic intervals are computed using mixed continuous-discrete optimization methods and the aleatory statistics are computed using polynomial chaos expansions. We first investigate two simple algebraic test problems with multiple model forms and then deploy the methods to the Drekar thermal hydraulics application. The Drekar study employs a set of Reynolds-averaged Navier-Stokes (RANS) turbulence models, including Spalart-Allmaras and k-ε. Results highlight the utility of employing efficient mixed continuous-discrete optimizers based on surrogate emulation.