Paper Conference

2020 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA


Numerical Investigation of External Convective Heat Transfer Coefficient for Buildings in Different Land-Use Class

Anwar D. Awol, Girma T. Bitsuamlak, Fitsum A. Tariku
Univeristy of Western Ontario, London, ON, Canada
British Colombia Institute of Technology, BC, Canada

Abstract: Convective heat transfer coefficient (CHTC) is known to play an important role in the evaluation of heat exchange between a building and its surroundings. There are several correlations suggested for the estimation of CHTC from the external surfaces of a building. However, there is a marked difference between values obtained from these correlations under similar set of conditions. Therefore, there is a need for an extensive correlation addressing the discrepancies in some of the existing correlations. In the current study, the impact of built morphology, associated with different land-use classes (e.g., industrial, residential, or downtown, etc.), on the convective heat transfer from buildings is numerically investigated. CFD simulations are conducted in a Navier-Stokes solver with Reynolds stress turbulence model as a closure method. The surrounding buildings are expected to influence the local microclimate (wind speed and turbulence), which in turn will affect the CHTC of the study building. Arrays of building-like bluff bodies from different land-use class with several packing density representing different flow regimes, and a benchmarking isolated cube case, have been investigated. Frontal/planar densities of sections of various parts of cities, based on their land-use class - from literature, are used to relate CHTC findings from simulation to land-use classifications. The results indicate that the behavior of convective heat transfer from building surfaces significantly depends on the landuse class designation of the location of the study building. The development of land-use class based CHTC correlations is expected to reduce the bias resulting from using correlation based exclusively on isolated building studies.
Pages: 214 - 221