An enhanced k-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si167.svg" display="inline" id="d1e1218"><mml:mi>ω</mml:mi></mml:math> SST model to predict airflows around isolated and urban buildings

The goal of this research is to improve and validate a Reynolds Averaged Navier–Stokes (RANS) turbulence model perform accurate Computational Fluid Dynamics (CFD) simulations the urban wind flow. k-ω SST selected for calibration since its blended formulation holds remarkable optimization potential has increased relevancy in recent studies field. A simulation-based approach recalibrates closure constants by minimizing prediction error pressure coefficients on an isolated cubical building because scenario contains many salient features observed flow actual areas. procedure ensures both coherence calibrated involved wall function formulations relationship between them satisfy horizontal homogeneity atmospheric boundary layer. tuned increase momentum diffusion wake, resulting shorter more predictions reattachment lengths. Validation case with tunnel measurement data from various scenarios were addressed comprehensively assess adaptability optimal set reached. results confirm that CFD optimized are consistently closer agreement experimental than standard version SST. root mean square errors reduced about 75% pressure, 40% velocity, 20% turbulent kinetic energy.