  We report a development of probabilistic framework for parameter inference of
cryogenic two-phase flow based on fast two-fluid solver. We introduce a concise
set of cryogenic correlations and discuss its parameterization. We present
results of application of proposed approach to the analysis of cryogenic
chilldoown in horizontal transfer line. We demonstrate simultaneous
optimization of large number of model parameters obtained using global
optimization algorithms. It is shown that the proposed approach allows accurate
predictions of experimental data obtained both with saturated and sub-cooled
liquid nitrogen flow. We discuss extension of predictive capabilities of the
model to practical full scale systems.
