  In this paper, a validation and uncertainty quantification (VUQ) framework
for the Eulerian-Eulerian two-fluid-model based multiphase-computational fluid
dynamics solver (MCFD) is formulated. The framework aims to answer the
question: how to evaluate if a MCFD solver adequately represents the underlying
physics of a multiphase system of interest? The proposed framework is based on
total data-model integration (TDMI) approach that uses Bayesian method to
inversely quantify the uncertainty of the solver predictions with the support
of multiple experimental datasets. The framework consists of six steps with
state-of-the-art statistical methods, including: 1). Solver evaluation and data
collection; 2). Surrogate model construction; 3). Sensitivity Analysis; 4).
Parameter selection; 5). Uncertainty quantification with Bayesian inference;
and 6). Validation metrics calculation. Those steps are formulated in a modular
manner and using non-intrusive methods. Such features ensure the applicability
of the flexible framework to different scenarios and modeling of multiphase
flow and boiling heat transfer, as well as the extensibility of the framework
to support VUQ of different MCFD solvers.
