E3S Web Conf.
Volume 180, 20209th International Conference on Thermal Equipments, Renewable Energy and Rural Development (TE-RE-RD 2020)
|Number of page(s)||9|
|Published online||24 July 2020|
Development of thermal bridge numerical model, based on conjugate heat transfer and indoor and outdoor environment parameters
Technical University – Sofia, FPEPM, Department:” Hydroaerodynamics and Hydraulic Machines”, Sofia 1000, Bulgaria
2 SoftSim Consult Ltd., Consultant at Technical University of Sofia, FPEPM, Department:” Hydroaerodynamics and Hydraulic Machines”, Sofia 1000, Bulgaria
* Corresponding author: m email@example.com
The presented study reveals the development of a 3D numerical model for thermal bridge assessment, based on conjugate heat transfer and CFD methods. With the developed model, thermal simulations are performed, in order to analyse the interaction between different ambient conditions and material properties. The results show that the wall boundary layer profiles are depended on the attached air flow velocity magnitude and implemented wall roughness. The parametric analysis, of the varying ambient air temperatures, confirm the linear dependence to the internal wall surface temperatures. The demonstrated correlations, in regard of the attached air flow velocity magnitude and wall roughness heights, are non-linear. The most characteristic result, achieved in the simulation study, is the impact of the wall roughness, over the internal wall temperature. The increase of the roughness leads to significant increase of the internal wall temperature. Explanation may be found in the boundary layer flow velocity magnitude near the external wall, which decreases the heat energy transfer between the solid and cold fluid medias.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Initial download of the metrics may take a while.