Significance of external wind conditions on the convective heat transfer coefficients (CHTC) and energy performance in multi-zone high-rise buildings

The study investigates the impact of external wind conditions on the convective heat transfer coefficients (CHTC) and overall energy performance in multi-zone high-rise buildings. The research employs a coupling method between building energy simulation (BES) and computational fluid dynamics (CFD) tools to enhance the accuracy of CHTC calculations. The methodology integrates meteorological and microclimate data, emphasizing detailed wind direction captured through Building Controls Virtual Test Bed (BCVTB) and MATLAB scripts. The high-rise building model was tested across various global cities with distinct climatic conditions. The coupling method improves CHTC predictions compared to conventional algorithms such as DOE-2, TARP, MoWiTT, and the Adaptive Convection Algorithm. Notably, the coupling method revealed underestimations in traditional models, particularly in winter scenarios, with CHTC values up to 102.26 % higher. This discrepancy highlights the importance of dynamic modeling approaches that incorporate detailed wind data and fa & ccedil;ade orientations. Among various algorithms, the Simple Combined algorithm calculates 4.30 % higher energy demand on average compared with the coupling method, while others estimate lower, DOE-2 has a 5.76 % average underestimation, followed by MoWiTT with 6.77 %, TARP with 9.37 %, and the Adaptive Convection Algorithm with 12.63 %. This study provides robust data and insights that could inform design optimization and energy conservation strategies, making it crucial for advancing high-rise building energy modeling. The research highlights the necessity for improved BES tools to optimize thermal performance, reduce energy consumption, and enhance comfort in high-rise buildings under diverse climatic conditions.