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Cooling energy use of residential buildings in Hong Kong has been increasing in the past two decades. Natural ventilation is an effective means to reduce cooling energy use. To encourage wider and more efficient use of natural ventilation, previous works have been focused on window designs and the influence of window opening on the discharge coefficient. There is virtually no works on identifying the window opening degree for efficient natural ventilation. In this study, walk-through surveys, site measurements, CFD simulations and statistical analyses were adopted to ascertain Hong Kong households' window opening habits and to identify the optimum window opening degree. Three window types, operating under nine sets of representative wind conditions in Hong Kong, four possible window orientations and two ventilation modes (single-sided and cross ventilation), to become 1944 cases, were studied. Air change per hour (ACH) was used to quantity the indoor natural ventilation performance. Regression analysis was employed to quantify the influence of different operating characteristics on ACH. The results concluded that Hong Kong households had limited and inefficient use of natural ventilation, while the optimum window opening degree, taking into account seasonal wind conditions and all design options, should be in the range of 0.6 to 0.9. [ABSTRACT FROM AUTHOR]

Natural ventilation and the type of window used are closely related. Many works have already been done on identifying the window types that can enhance ventilation performance in residential buildings. However, window performance has been investigated either independently, without considering the interactive effects of other apertures (relative positions of windows and window orientations) or it has been examined based on very limited wind data sets. To fill this research gap, this study aims to evaluate the influence of window types on indoor ventilation performance of residential units in Hong Kong, taking into account the interactive effect and based on representative wind data sets. Air change per hour (ACH) was used to quantify natural ventilation. In this study, site measurement was conducted at a carefully selected residential unit to provide data for validation of the Computational Fluid Dynamics (CFD) settings. The validated settings were used for further CFD simulations. The Central Composite Design method and the Squeeze Theorem were used to determine the representative wind data sets. The Response Surface Regression method was used to develop a mathematical model for quantifying the interactive influence of different apertures on indoor ventilation and to enable quick estimation of ACH. The results lead to the conclusion that for all apertures, side hung (SH) window is the most effective design, followed in descending order by top hung (TH) window and sliding (SLD) window. The maximum achievable ACH for SH and TH windows were 124% and 97% higher than the SLD window. It was also found that if windows can be located only on the same side of a residential unit, SH windows and south facing TH windows should be preferred. • The most preferred window type for Hong Kong residential units was investigated. • Investigation has considered the interactive effect and based on representative wind data sets. • Interactive effect with other apertures was examined by response surface regression method. • Wind data sets were formulated by the central composite design method and the squeeze theorem. • A mathematical model was developed for estimation of ACH for different apertures design. • It was concluded that side hung window is the most effective design. [ABSTRACT FROM AUTHOR]