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A self-consistent,physics-based boiling heat transfer modeling framework for use in computational fluid dynamics
Institution:1. Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA;2. Heat Transfer Research Department, Mitsubishi Heavy Industries, Ltd., Takasago, Hyogo 676-8686, Japan;1. University of Ljubljana, Faculty of Mechanical Engineering, Aškerčeva 6, 1000 Ljubljana, Slovenia;2. Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia;3. Chimie ParisTech, PSL Research University, Institut de Recherche de Chimie Paris, 75005 Paris, France;1. School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC, 3083, Australia;2. Key Laboratory of Ministry of Education for Advanced Reactor Engineering and Safety, Institute of Nuclear and New Energy Technology, Tsinghua University, PO Box 1021, Beijing, 100086, China;1. School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom;2. Department of Mechanical Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
Abstract:Computational Fluid Dynamics (CFD) offers the opportunity to investigate physically and geometrically complex systems with high fidelity. Its applicability to multiphase flow, and particularly boiling heat transfer, is currently limited by the lack of appropriate closure models to describe all relevant phenomena. In this paper, we present an original subcooled flow boiling modeling framework for CFD, which aims at consistently and accurately characterizing the key physics that affect heat transfer at the boiling surface. The new framework introduces a fully mechanistic representation of heterogeneous boiling that improves numerical robustness and reduces sensitivity to closure coefficients. The proposed formulation is inspired by new experimental insight, and significantly extends the existing boiling models by capturing the effects of (i) the microlayer on surface evaporation, (ii) the boiling surface, and (iii) bubbles sliding along the boiling surface. A new statistical treatment of the location and mutual interactions of bubbles on the surface allows for mechanistic prediction of the dry surface area, an important quantity that affects the boiling heat transfer coefficient. This approach lends itself naturally to extension to very high heat fluxes, potentially up to the critical heat flux. An assessment and sensitivity study of the model is presented for a range of mass fluxes (500–1250 kg/m2/s), heat fluxes (100–1600 kW/m2), inlet subcoolings (5, 10, 15 K), and pressures (1, 1.5, 2 bars), demonstrating improved robustness and predictive accuracy at all tested conditions in comparison to traditional heat partitioning approaches, including high heat fluxes, where classic models often fail to converge. Lastly, the framework proposed here should not be viewed as another heat partitioning model, but rather as a general platform that allows incorporation of advanced models for each physical phenomenon considered, leveraging the growing insight generated by modern experimental diagnostics for boiling heat transfer.
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