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The computation of turbulent natural convection flows - Turbulence ...

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199<br />

Nu<br />

60<br />

40<br />

20<br />

LES<br />

AWF<br />

LRN<br />

SWF<br />

0<br />

0 0.2 0.4 0.6 0.8 1<br />

Y<br />

Figure 6.67 – Local Nusselt numbers along hot wall within 5◦ stable tilted tall<br />

cavity.<br />

6.7 Closing remarks<br />

In this Chapter, three different test cases have been numerically investi-<br />

gated regarding <strong>turbulent</strong> <strong>natural</strong> <strong>convection</strong>. <strong>The</strong> test cases were selected so<br />

that they cover various physical phenomena such as single and multiple cell<br />

circulation and stable and unstable stratified flow. <strong>The</strong> comparisons in this<br />

Chapter showed that the k-ε model using the AWF near-wall strategy pro-<br />

duces reliably accurate predictions for the 5 ◦ stable, 60 ◦ stable and 60 ◦ unsta-<br />

ble. Introduction <strong>of</strong> the RSM models over-estimates <strong>turbulent</strong> kinetic energy<br />

near the top and the bottom <strong>of</strong> tall cavity in the 60 ◦ stable inclined case. <strong>The</strong><br />

over-prediction is significant in the case <strong>of</strong> the RSM-TCL using AWF. <strong>The</strong> in-<br />

troduction <strong>of</strong> the θ 2 and εθ transport equations, with more complex algebraic<br />

thermal flux models improves the RSM-basic and TCL predictions near the<br />

top and the bottom <strong>of</strong> the tall cavity. <strong>The</strong> improvement is more significant<br />

in RSM-θ 2 -εθ-TCL case. In the 60 ◦ stable case these extended stress transport<br />

models then produce better predictions than the corresponding eddy viscosity<br />

schemes.

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