Implementation of a CFD model for wall condensation in the presence of non-condensable gas mixtures
| Autor: | Wilko Rohlfs, G. Vijaya Kumar, Hans-Josef Allelein, Reinhold Kneer, Eva M. Groß, Stephan Kelm, Liam M. F. Cammiade, K. Arul Prakash |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Materials science
Scale (ratio) business.industry 020209 energy Thermal resistance Condensation Energy Engineering and Power Technology 02 engineering and technology Mechanics Computational fluid dynamics Nuclear reactor Industrial and Manufacturing Engineering Forced convection law.invention Diffusion layer ddc:690 020401 chemical engineering law Robustness (computer science) 0202 electrical engineering electronic engineering information engineering 0204 chemical engineering business |
| Zdroj: | Applied thermal engineering 187, 116546-(2021). doi:10.1016/j.applthermaleng.2021.116546 |
| DOI: | 10.1016/j.applthermaleng.2021.116546 |
| Popis: | In this paper, we discuss a CFD model to predict vapor condensation on walls in the presence of non-condensable gases, with a specific focus on large scale applications, such as accidental flows in a nuclear reactor containment. It is conclusive from the previous works that the heat and mass transport resistance due to the diffusion boundary layer in the gas phase overwhelms the liquid film thermal resistance. Therefore, the two-phase wall condensation phenomenon is treated with a single-phase (gas) model. For the numerical implementation, the containmentFOAM CFD package, based on OpenFOAM is used. For the first time, the model implementation is discussed for arbitrary multi-component mixtures, and performances of two commonly used approaches – Volumetric source terms and Face-fluxes – are compared; the Face-flux model proved to be more accurate, computationally cheaper, and less grid-dependent. Concluding, the Face-flux approach was validated against the experimental database for forced convection flows, obtained at the SETCOM facility in Forschungzentrum Julich, Germany. The results demonstrate the model’s predictiveness and robustness for a wide range of cases in the forced convection regime. |
| Databáze: | OpenAIRE |
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