A POD-Galerkin reduced order model of a turbulent convective buoyant flow of Sodium over a backward-facing step. (English) Zbl 1479.76049
Summary: A Finite-Volume based POD-Galerkin reduced order modeling strategy for steady-state Reynolds averaged Navier-Stokes (RANS) simulation is extended for low-Prandtl number flow. The reduced order model is based on a full order model for which the effects of buoyancy on the flow and heat transfer are characterized by varying the Richardson number. The Reynolds stresses are computed with a linear eddy viscosity model. A single gradient diffusion hypothesis, together with a local correlation for the evaluation of the turbulent Prandtl number, is used to model the turbulent heat fluxes. The contribution of the eddy viscosity and turbulent thermal diffusivity fields are considered in the reduced order model with an interpolation based data-driven method. The reduced order model is tested for buoyancy-aided turbulent liquid sodium flow over a vertical backward-facing step with a uniform heat flux applied on the wall downstream of the step. The wall heat flux is incorporated with a Neumann boundary condition in both the full order model and the reduced order model. The velocity and temperature profiles predicted with the reduced order model for the same and new Richardson numbers inside the range of parameter values are in good agreement with the RANS simulations. Also, the local Stanton number and skin friction distribution at the heated wall are qualitatively well captured. Finally, the reduced order simulations, performed on a single core, are about \(10^5\) times faster than the RANS simulations that are performed on eight cores.
MSC:
| 76F35 | Convective turbulence |
| 76M12 | Finite volume methods applied to problems in fluid mechanics |
| 80A19 | Diffusive and convective heat and mass transfer, heat flow |
Keywords:
finite volume scheme; proper orthogonal decomposition; Galerkin projection; Reynolds-averaged Navier-Stokes equations; low-Prandtl number flow; heat fluxReferences:
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