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Research Article

Influence of turbulent structure on the heat transfer of Rayleigh–Bénard convection with triangular roughness element

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Pages 549-566 | Received 29 May 2022, Accepted 06 Nov 2022, Published online: 15 Nov 2022
 

ABSTRACT

There is a widely accepted conclusion that the wall roughness do not always enhance the heat transport of the turbulent thermal convection. In this paper, the heat transfer efficiency is statistically investigated from the perspective of turbulent structure. The effect of turbulent structure on the heat transfer of Rayleigh–Bénard convection with triangular rough element on the top and bottom plates is numerically simulated by a lattice Boltzmann method. We use a clustering method to identify complex turbulent structures associated with intense events. The reduction of the Nusselt number is obtained for small roughness height H/L, while the enhancement of heat transport appears for large H/L. For the large H/L case, the positive temperature structures Tcp occupying the negative heat transfer events Tvn reduce the efficiency of the heat transfer. On the contrary, the negative temperature turbulent structures Tcn boost the heat transfer. By analyzing the conditional average field, we found that the enhancement of the heat transfer for large H/L cases is due to that the negative temperature structures play a dominant role. For small H/L cases, the positive temperature structures Tcp inhibit the heat transfer. Furthermore, the more positive and negative temperature structures for large H/L cases are generated near the solid wall and the corner of the box. The physical explanation for the Nu enhancement is that the more secondary vortices are generated by the interaction of these turbulent structures and the rough wall, leading to more plumes ejected from the boundary layers to the bulk.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research is supported in part by the Shanghai Education Development Foundation and Shanghai Municipal Education Commission in China 18SG53; National Key R&D Program of China (No. 2018YFB0204404); Double Innovation Program of Jiangsu Province, China, 2018; National Nature Science Foundation of China project nos. 12032016 and 91952102.

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