Abstract
Computational fluid dynamics (CFD) results generated by the steady Reynolds-averaged Navier-Stokes equations (SRANS) model and large eddy simulation (LES) are compared with wind tunnel experiments for investigating a cross-ventilation flow in a group of generic buildings. The mean flow structure and turbulence statistics are compared for SRANS based on different two-equation turbulence models with LES based on the Smagorinsky subgrid-scale turbulence model. The LES results show very close agreement with the experimental results in the prediction of the time-averaged velocity, wind surface pressure around and inside the building, and crossing flow through the openings. In contrast, SRANS fails to predict the most important features of cross-ventilation. LES reproduces well the anisotropic turbulence property around and inside the cross-ventilated building, which is closely related to the transient momentum transfer caused in street canyon flows and has a significant influence on the mean flow structure. In contrast, SRANS could not inherently reproduce such transient fluctuations and anisotropic turbulence property, which results in low accurate predictions for the time-averaged velocity components, wind surface pressure distribution and crossing airflow rate up to 100% error.
Highlights
This paper comprehensively compares the results of computational fluid dynamics (CFD) simulations based on steady Reynolds-averaged Navier-Stokes equations (SRANS) and large eddy simulation (LES) with those of wind tunnel experiments for a cross-ventilation flow in a group of generic buildings with a regular arrangement
Comparison of the mean flow structure and turbulence statistics generated by SRANS and LES with the wind tunnel experiments results in the following conclusions:
- Accuracy of LES in the prediction of the mean flow structure, wind surface pressure, and crossing airflow rate through the openings is much higher than the SRANS
Summary
Wind induced cross-ventilation has been utilized in traditional and modern buildings for air-quality improvement (Lien and Ahmed 2011; Heracleous and Michael 2019; Aflaki et al 2019; Aydin and Mirzaei 2016) and building energy reduction (Mochida et al 2006; Mohammadreza Shirzadi, Naghashzadegan, and Mirzaei 2019; Zhang, Mirzaei, and Jones 2018; Ohba and Lun 2010; Lo and Novoselac 2013; Li et al 2014). R. Chu, Chiu, and Wang 2010; Tominaga and Blocken 2015; Mohammadreza Shirzadi, Tominaga, and Mirzaei 2019a; S Murakami 1991), and computational fluid dynamics (CFD) Shirzadi, Mirzaei, and Naghashzadegan 2018; Twan van Hooff, Blocken, and Tominaga 2016; Mohammadreza Shirzadi, Tominaga, and Mirzaei 2020; Ramponi and Blocken 2012a; M. Mirzaei 2018; James Lo, Banks, and Novoselac 2013; Kosutova et al 2019; Perén, Van Hooff, et al 2015; Lo 2011; Hua, Ohbab, and Yoshiec 2006; Bazdidi-Tehrani et al 2019)
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