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ISSN オンライン: 2642-0554

LARGE EDDY SIMULATIONS OF TURBULENT LIQUID FLOWS WITH CHEMICAL REACTIONS

Takenobu Michioka
Department of Mechanical Engineering, Kyoto University, Kyoto 606-8501; Environmental Science Research Laboratory Central Reseach Institute of Electric Power Industry 1646 Abiko, Abiko, Chiba, 270-1194, Japan

Ryo Onishi
Earth Simulator Center, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-ku Yokohama Kanagawa 236-0001, Japan also Department of Aeronautics, Imperial College London, SW7 2AZ, UK

Satoru Komori
Department of Mechanical Engineering and Science Kyoto University Kyoto daigaku-Katsura, Nishikyo-ku, Kyoto, 615-8140, Japan

要約

A subgrid-scale (SGS) model for the filtered reaction term is presented to develope large eddy simulations (LES) of nonpremixed, turbulent reacting liquid flows. The SGS model is based on the SGS probability density function (PDF) and SGS conditional expectation. The SGS PDF is assumed to have the beta distribution and the SGS conditional expectation was modeled using the filtered data obtained from direct numerical simulations (DNS) of liquid flows with second-order chemical reactions.
To confirm the accuracy of the SGS model, the LES was applied to a liquid mixing layer flow downstream of a turbulence-generating grid with a chemical reaction. The large eddy probability density function (LEPDF) model and the present model were used as the SGS models for a rapid reaction and for a moderately fast reaction, respectively. The predictions of the LES were compared with the measurements by Komori et al. (1993, 1994) to examine the proposed SGS models. The results show that the predictions of the LES are in good areement with the mesurements. Furthermore, to investigate the applicability of the present LES to other reacting liquid flows, both experiment and LES were performed in a turbulent mixing layer with a rapid reaction. The predictions were also in good agreement with the measurements. These results show that the present LES taking account into the SGS distributions can accurately estimate the concentration statistics in various types of reacting liquid flows.