Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

Abstract

A ABSTRACTIn addition to a validation data plan for quantification of data needs and strategy for data collection and characterization [1] [2], development of advanced techniques for calibration and validation of complex multiscale, multiphysics nuclear reactor simulation codes are a major component of the CASL VUQ plan.Advanced modeling of LWR systems normally involves a range of physicochemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which occur over a wide range of spatial and temporal scales. To a large extent, the accuracy of (and uncertainty in) overall model predictions is determined by the correctness of various sub-models, which are not conservation-laws based, but empirically derived from measurement data. Such sub-models normally require extensive calibration before the models can be applied to analysis of real reactor problems.This work demonstrates a case study of calibration of a common model of subcooled flow boiling, which is an important multiscale, multiphysics phenomenon in LWR thermal hydraulics. The calibration process is based on a new strategy of model-data integration, in which, all sub-models are simultaneously analyzed and calibrated using multiple sets of data of different types. Specifically, both data on large-scale distributions of void fraction and fluid temperature and data on smallscale physics of wall evaporation were simultaneously used in this work's calibration.In a departure from traditional (or common-sense) practice of tuning/calibrating complex models, a modern calibration technique based on statistical modeling and Bayesian inference was employed, which allowed simultaneous calibration of multiple sub-models (and related parameters) using different datasets. Quality of data (relevancy, scalability, and uncertainty) could be taken into consideration in the calibration process.This work presents a step forward in the development and realization of the CIPS Validation Data Plan [3] [1] at the Consortium for Advanced Simulation of LWRs to enable quantitative assessment of the CASL modeling of Crud-Induced Power Shift (CIPS) phenomenon, in particular, and the CASL advanced predictive capabilities, in general.This report is prepared for the Department of Energy's Consortium for Advanced Simulation of LWRs program's VUQ Focus Area. E EXECUTIVE SUMMARYThis milestone supports a case study of calibration and validation of a realistic and relatively complex subcooled flow boiling model, with the objective to develop recommendations on CASL-wide Model Calibration, Validation, and Uncertainty Quantification efforts. The SFB model utilized a common description of multiphase flow as inter-penetrating continua with conservation laws applied to each phase as a separate field. Small-scale physics related to thermal hydrodynamic inter-phase and flow-wall interactions were represented by various empirical/semi-empirical closure sub-models. In this SFB modeling, the sub-model of wall evaporation, which relied on...

Scalable Inverse Uncertainty Quantification by Hierarchical Bayesian Modeling and Variational Inference

“…The precision and reliability of model predictions largely depend on how well these closure models are calibrated, a process that is traditionally carried out step-by-step. Initially, empirical or semi-empirical submodels undergo calibration and validation using separate-effect test (SET) data, after which the entire model is validated against integral-effect test (IET) data [3]. SETs, commonly executed at a scale smaller than real reactors, primarily concentrate on specific experimental QoIs, minimizing the interference with other phenomena [4].…”