Abstract
This paper aims to provide a more detailed representation of the scalar flux modeling (SFM) approach for modeling turbulent inclined negatively buoyant jets. The SFM approach addresses the limitations of eddy viscosity models in terms of the mean concentration field and turbulent scalar flux within the context of Reynolds-averaged Navier–Stokes modeling. In this study, the contribution of the involved terms in the transport equation of the turbulent scalar flux vector was evaluated, and the geometrical and mixing parameters of concentration and velocity of 45\(^\circ\) inclined negatively buoyant jets were verified. The SFM approach, along with the required modification for momentum flux modeling, was implemented in OpenFOAM v6. Results showed that the SFM approach can accurately predict mixing parameters due to the complex interactions between different turbulence contributors of the flow involved in the model. In comparison to simpler approaches, such as gradient-type models, that only correlate the gradient of the scalar field with turbulence, the SFM approach’s capability to predict mixing parameters is significantly higher.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- \(\mathbf {b_{ij}}\) :
-
Reynolds stress anisotropy
- \({\textbf {D}}\) :
-
Nozzle diameter
- \({\textbf {Fr}}\) :
-
Densimetric Froude number
- \(\mathbf {G/G_{ij}}\) :
-
Buoyancy production
- \({\textbf {g}}\) :
-
Gravitational acceleration
- \({\textbf {k}}\) :
-
Turbulent kinetic energy
- \(\mathbf {P/P_{ij}}\) :
-
Pressure/stress production
- R :
-
Ratio of dynamic to scalar time scales
- S :
-
Salinity
- \(\mathbf {Sc_{t}}\) :
-
Turbulent Schmidt number
- \(\mathbf {S_m}\) :
-
Centerline peak dilution ratio
- \(\mathbf {S_r}\) :
-
Return point dilution ratio
- \(\mathbf {\overline{S}_{ij}}\) :
-
Mean strain rate
- \(\varvec{S_\phi }\) :
-
Source term
- \(\mathbf {U_0}\) :
-
Initial jet velocity
- \(\mathbf {\overline{u'_i u'_j}}\) :
-
Reynolds stress tensor
- \(\mathbf {\overline{u'_i \phi '}}\) :
-
Reynolds flux vector
- \(\mathbf {\overline{W_{ij}}}\) :
-
Mean rate of rotation tensor
- \(\mathbf {X_m}\) :
-
Horizontal distance of the centerline peak to the origin
- \(\mathbf {X_r}\) :
-
Horizontal distance of the return point to the origin
- \(\mathbf {Y_m}\) :
-
Vertical distance of the centerline peak to the origin
- \(\mathbf {Y_t}\) :
-
Terminal rise height
- \(\varvec{\beta }\) :
-
Saline contraction coefficient
- \(\varvec{\Gamma }\) :
-
Molecular diffusivity
- \(\varvec{\delta }\) :
-
Kronecker delta
- \(\varvec{\epsilon , \epsilon _\phi }\) :
-
Dissipation rate of turbulent kinetic energy
- \(\varvec{\nu }\) :
-
Molecular viscosity
- \(\varvec{\nu _t}\) :
-
Eddy viscosity
- \(\varvec{\Pi _{ij}}\) :
-
Pressure-strain correlation
- \(\varvec{\pi _{i\phi }}\) :
-
Pressure-scalar correlation
- \(\varvec{\rho _0}\) :
-
Jet density
- \(\varvec{\rho _a, \rho _r}\) :
-
Water density
- \(\varvec{\tau _{ij}}\) :
-
Stress tensor
- \(\varvec{\Phi }\) :
-
Scalar quantity, mean scalar quantity
- \(\varvec{\phi '}\) :
-
Scalar fluctuation
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This research was enabled in part by support provided by WestGrid (www.westgrid.ca) and Compute Canada Calcul Canada (www.computecanada.ca).
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Tahmooresi, S., Mohammadian, A., Nistor, I. et al. Reynolds flux modeling; new numerical insights into inclined dense jets. Environ Fluid Mech 23, 551–577 (2023). https://doi.org/10.1007/s10652-023-09919-z
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DOI: https://doi.org/10.1007/s10652-023-09919-z