Prediction of Interfacial Area Transport in a Coupled Two-Fluid Model Computation
A computer code has been written to predict interfacial area transport within the framework of the two-fluid model. The suitability of various constitutive models was evaluated from a scientific and numerical standpoint, and selected models were used to close the two-fluid model. The resulting system was then used to optimize the empirical constants in the interfacial area transport equation for large diameter pipes. The optimized model was evaluated based on comparison with the data of Shen et al. and Schlegel et al. The optimization shows agreement with previous research conducted by Dave et al. and Talley et al. using TRACE-T, and reduced the RMS error in the interfacial area concentration prediction for the large diameter pipe data from 52.3% to 34.9%. The results also highlight a need for additional high-resolution data at multiple axial locations to provide a more detailed picture of the axial development of the flow. The results also indicate a need for improved modeling of the interfacial drag, especially for Taylor cap bubbles under relatively low void fraction conditions.
J. P. Schlegel et al., "Prediction of Interfacial Area Transport in a Coupled Two-Fluid Model Computation," Journal of Nuclear Science and Technology, vol. 54, no. 1, pp. 58-73, Taylor & Francis, Jan 2017.
The definitive version is available at https://doi.org/10.1080/00223131.2016.1205530
Nuclear Engineering and Radiation Science
Center for High Performance Computing Research
Keywords and Phrases
Aluminum; Flow of fluids; Forecasting; Light water reactors; Optimization; Two phase flow; Void fraction; Computer codes; Empirical constants; High resolution data; Interfacial area concentrations; Interfacial area transport equation; Interfacial area transports; Large diameter pipes; Two fluid model; Transport properties; Fluid flow; Two-fluid model
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Taylor & Francis, All rights reserved.
01 Jan 2017