Model uncertainty is a relatively new topic of discussion in TH code calculations, despite being often the major contributor to the overall uncertainty and a challenging practice in uncertainty analysis. The Integrated thermal-hydraulics uncertainty analysis (IMTHUA) methodology, developed by the authors, treats the TH code structural uncertainties (generally known as model uncertainty) explicitly by treating internal sub-model uncertainties, and by propagating such model uncertainties in the code calculations, including uncertainties about input parameters. This paper presents systematic model uncertainty of thermal-hydraulics system codes as part of IMTHUA methodology. The objective is to demonstrate effectiveness and practicality of the methodology on complex thermal-hydraulics system codes calculations and discuss the challenges dealing with these types of uncertainty sources. TH codes are an assembly of models and correlations for simulation of physical phenomena and behavior of system parameters in temporal domain. In some cases, there are alternative sub-models, or several different correlations for calculation of a specific phenomenon of interest. There are also “user options” for choosing one of several models or correlations in performing a specific code computation. Dynamic characteristics of TH calculations add more complexity to the code calculation, meaning for example, that specific code models and correlations invoked are sequence-dependent, and based certain (dynamic) conditions being satisfied. Structural uncertainty assessment (model uncertainty) for a single model will be discussed by considering “correction factor”, “bias”, and also through Bayesian sub-model output updating with available experimental evidence. In case of multiple alternative models, several techniques including dynamic model switching, user controlled model selection, model mixing, will be discussed. This paper discusses the challenges in treatment of the structural uncertainties in Thermal-Hydraulics system codes. Subjectivity and dependency on expert judgment in some of the solutions leaves some concerns on context of such systematic solutions to utilize imperfect and partially relevant data and information.

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