A data-driven Reynolds-number-dependent model for turbulent mean flow prediction in circular jets
نویسندگان
چکیده
This paper proposes a data-driven turbulence model for predicting the mean flow in turbulent circular jets over wide range of Reynolds numbers (Re). The main formulation is adapted from well-known k–ε (where k kinetic energy, and ε dissipation rate) with set Re-dependent variation constants. Tam–Thies correction applied constants optimized using data assimilation based on ensemble Kalman filter to minimize deviation between prediction experimental data. converging at Re = 10 700, 20 100, 95 500 are fitted logarithmic curves respect obtain universal jet under various conditions. constants, named k–ε–Re model, can accurately predict both orifice Re. While directly pipe jets, much better be obtained high (Re ≥ 21 000 presently) compared default model. However, certain discrepancy observed 5 ≤ x/D 15 6000 16 000. Further improvement achieved by assimilating fitting coefficients adequately generalizable different moderate or (≥ 000), while further recalibration specific nozzle type small
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ژورنال
عنوان ژورنال: Physics of Fluids
سال: 2023
ISSN: ['1527-2435', '1089-7666', '1070-6631']
DOI: https://doi.org/10.1063/5.0160410