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Homogeneous non-equilibrium two-phase choked flow modeling
Authors:Alexandros G Venetsanos
Affiliation:Environmental Research Laboratory, National Centre for Scientific Research Demokritos, Aghia Paraskevi, Athens, 15341, Greece
Abstract:The estimation of the release conditions is critical input to subsequent risk assessment accident analysis. To this respect a new homogeneous non-equilibrium two-phase model is proposed to simulate the depressurization from stagnation conditions leading to the bubbly flow regime. The proposed model, being intermediate between HEM (homogeneous equilibrium) and HFM (homogeneous frozen) models, presents no discontinuity in the liquid phase depressurization path gradient and therefore no discontinuity in sound speed. The proposed model is successfully validated against the NASA hydrogen critical flow experiments and compared against predictions from both HEM and HFM, using hydrogen physical properties from NIST. An increase of the pressure difference between stagnation and the intersection of isentropic with saturation line leads to increase of the choked mass flux, decrease of the throat to stagnation pressure ratio, decrease of the liquid superheat and decrease of the vapor quality. The proposed model was found to overestimate the experimental throat mass fluxes by no more than 10% and underestimate the experimental throat to stagnation pressure ratios by no more than 50%, while predicted liquid superheat values range from 3.8 to 11% of the saturation temperature. Deviations between models were found to increase for low values of the pressure difference parameter, where non-equilibrium effects become more important. Under these conditions the throat mass flux is underestimated by maximum 20% by HEM and overestimated up to 32% by HFM, while the throat to stagnation pressure ratio is overestimated by up to 72% and underestimated by 80% respectively.
Keywords:Hydrogen release  Homogeneous non-equilibrium model  Homogeneous frozen model  Liquid superheat  Sound speed modeling  Choked flow modeling
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