Li, Han (2018-12). Computational Study of Interaction of Twin Rectangular Jets. Doctoral Dissertation. Thesis uri icon

abstract

  • Turbulent jet interactions play a significant role in terms of momentum and heat transfer. Interactions of multiple turbulent jets occurs in next-generation nuclear reac- tors, where high-temperature flow mixing in the lower plenum and mixing fluctuations in the coolant may influence power oscillations and flow-induced vibrations. Thus, the estimation of mixing condition needs to be accurate. Recent benchmark experiments using the particle image velocimetry (PIV) technique provided high-fidelity experi- mental data that could be used in verification studies. Computational fluid dynamics (CFD) simulations are extensively employed in the study of mixing phenomenon of parallel jets. Therefore, the validation of various turbulence models is of great impor- tance for ensuring that the numerical results are reliable and can serve as a guide for future designs. In this study, an open source CFD library, i.e., OpenFOAM, was utilized to con- duct numerical simulations of twin jets. This work consists of two parts: one part focuses on steady-state simulations and the other on transient simulations. In the first part, the steady state Reynolds-averaged Navier-Stokes (RANS) models, such as the realizable k - ? and the shear stress transport k - ?, were used for the steady-state val- idation study. Steady-state simulations showed that with proper boundary conditions at the inlets, the mean velocity data agreed well with the experimental data within engineering accuracy (14%). In the second part, the partially averaged Navier - Stokes (PANS) models were implemented in the code and were utilized to conduct transient simulations. Fluctuating inlet boundary conditions from experiments were employed. The results obtained from PANS and the unsteady RANS (URANS) models were com- pared with experimental data. The PANS model showed a good agreement with the experimental data in terms of the merging point (4.3%). In addition, the k - ? PANS model was compared with the k - ? URANS model. A power spectrum density (PSD) analysis was performed based on the velocity at four sample locations to compare the resolved frequencies between the PANS and URANS models. It was observed that the PANS model showed better capabilities of resolving higher turbulence flow frequencies compared to the URANS based on the PSD analysis. Another part of this study included the use of large eddy simulation numerical methodology on a parallel jet system and the computational results were validated against the benchmark PIV experiments. The results indicated a good agreement in terms of the merging point and time-averaged velocity profile. Spectral analyses via Welch's power spectral density functions were used to analyze frequency information in turbulent jets. The proper orthogonal decomposition (POD) analysis method was applied using a snapshot method. The POD analysis showed vortex structures similar to those in the benchmark PIV experiment.
  • Turbulent jet interactions play a significant role in terms of momentum and heat
    transfer. Interactions of multiple turbulent jets occurs in next-generation nuclear reac-
    tors, where high-temperature flow mixing in the lower plenum and mixing fluctuations
    in the coolant may influence power oscillations and flow-induced vibrations. Thus, the
    estimation of mixing condition needs to be accurate. Recent benchmark experiments
    using the particle image velocimetry (PIV) technique provided high-fidelity experi-
    mental data that could be used in verification studies. Computational fluid dynamics
    (CFD) simulations are extensively employed in the study of mixing phenomenon of
    parallel jets. Therefore, the validation of various turbulence models is of great impor-
    tance for ensuring that the numerical results are reliable and can serve as a guide for
    future designs.
    In this study, an open source CFD library, i.e., OpenFOAM, was utilized to con-
    duct numerical simulations of twin jets. This work consists of two parts: one part
    focuses on steady-state simulations and the other on transient simulations. In the first
    part, the steady state Reynolds-averaged Navier-Stokes (RANS) models, such as the
    realizable k - ? and the shear stress transport k - ?, were used for the steady-state val-
    idation study. Steady-state simulations showed that with proper boundary conditions
    at the inlets, the mean velocity data agreed well with the experimental data within
    engineering accuracy (14%). In the second part, the partially averaged Navier - Stokes
    (PANS) models were implemented in the code and were utilized to conduct transient
    simulations. Fluctuating inlet boundary conditions from experiments were employed.
    The results obtained from PANS and the unsteady RANS (URANS) models were com-
    pared with experimental data. The PANS model showed a good agreement with the
    experimental data in terms of the merging point (4.3%). In addition, the k - ? PANS
    model was compared with the k - ? URANS model. A power spectrum density (PSD)
    analysis was performed based on the velocity at four sample locations to compare the
    resolved frequencies between the PANS and URANS models. It was observed that the
    PANS model showed better capabilities of resolving higher turbulence flow frequencies
    compared to the URANS based on the PSD analysis.
    Another part of this study included the use of large eddy simulation numerical
    methodology on a parallel jet system and the computational results were validated
    against the benchmark PIV experiments. The results indicated a good agreement in
    terms of the merging point and time-averaged velocity profile. Spectral analyses via
    Welch's power spectral density functions were used to analyze frequency information
    in turbulent jets. The proper orthogonal decomposition (POD) analysis method was
    applied using a snapshot method. The POD analysis showed vortex structures similar
    to those in the benchmark PIV experiment.

publication date

  • December 2018