Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Heat and Mass Transfer. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Heat and Mass Transfer, 114, 2017 DOI:
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Inferential framework for two-fluid model of cryogenic chilldown
AU - Luchinsky, D. G.
AU - Khasin, M.
AU - Timucin, D.
AU - Sass, J.
AU - Brown, B.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - 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 chilldown 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.
AB - 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 chilldown 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.
KW - Chilldown
KW - Cryogenic flow
KW - Flow boiling
KW - Heat transfer
KW - Optimization
KW - Two-phase flow
U2 - 10.1016/j.ijheatmasstransfer.2017.06.097
DO - 10.1016/j.ijheatmasstransfer.2017.06.097
M3 - Journal article
VL - 114
SP - 796
EP - 808
JO - International Journal of Heat and Mass Transfer
JF - International Journal of Heat and Mass Transfer
SN - 0017-9310
ER -