In tropical climates, mixed-mode ventilation (MMV) is essential for optimizing thermal and energy performance in office buildings. This study investigates the impacts of wind-driven natural ventilation (NV) strategies and window frame design on the thermal and energy performance of MMV office buildings. A database of office buildings in São Paulo was used to develop a representative model to simulate various NV strategies and window frame configurations. artificial neural networks were employed to generate metamodels for annual cooling loads and cooling-degree hours, identifying optimal theoretical scenarios. Findings demonstrate that a holistic design integrating window-to-wall ratio (WWR), window frame design, and solar orientation is critical. In São Paulo's context, cross-ventilation on adjacent facades outperformed single-sided ventilation, reducing cooling loads by up to 25% and increasing air changes per hour (ACH) fourfold. The results emphasize treating WWR and orientation as integrated variables, notably, increasing WWR can serve as a deliberate cooling strategy if the resulting boost in NV potential offsets the higher thermal loads of larger glazed areas. This research underscores the significance of optimized envelope and window design in achieving energy-efficient MMV office buildings
The outdoor environment of campuses in high-humidity areas greatly affects personnel comfort and health. An optimized analysis model based on the Chen–Kim k – ɛ turbulence model, integrated with the IMMERSOL radiation model and Foliage vegetation model, to characterize the outdoor thermal-humidity environment of a Nanchang campus, with its reliability verified by experiments. Firstly, the Universal Thermal Climate Index (UTCI) and related environmental parameters are simulated and analyzed during key periods of a typical summer day. Then, multiple linear regression is used to explore the relationship between UTCI and its influencing factors. The results show that UTCI, ambient temperature and mean radiation temperature in building pedestrian zones are significantly higher than in other areas, peaking at 40.6 °C, 41.3 °C and 43.73 °C respectively at 14:00. In contrast, relative humidity in these zones is lower, reaching the minimum of 44.9% at 11:00. Furthermore, the proposed UTCI regression model for the Nanchang campus only requires outdoor temperature and wind speed for estimation, greatly simplifying calculations. This research provides a theoretical basis for evaluating outdoor thermal comfort in actual campus settings.
Wind-driven rain (WDR) creates highly nonuniform moisture loads on building façades, challenging waterproofing design and durability assessment. Existing WDR studies have emphasized overall exposure and spatial patterns, with limited attention to predicting local exposure across varying wind and rain conditions. This study conducted controlled indoor experiments on a reduced-scale façade model to characterize local WDR exposure. Analysis of 684 windward façade data points showed consistently high catch ratios in the upper and corner regions. Wind speed dominated variation in catch ratio, wind direction redistributed WDR between façades, and rainfall intensity mainly controlled water input. Within the experimental design, wind speed, wind direction, and rainfall intensity explained 74.30%, 20.13%, and 1.44% of the variance in mean catch ratio, respectively. A local WDR intensity model was developed by incorporating a position correction coefficient into an established semiempirical relationship. Validation yielded an RMSE of 0.371 mm/h, an MAE of 0.286 mm/h, and a relative bias of +1.06%. By extending WDR intensity prediction from façade-averaged to location-specific values, the model captures local exposure peaks and provides spatially resolved rain inputs for zoned waterproofing and hygrothermal simulations. It may also support targeted protection of traditional buildings exposed to long-term WDR.
Condensation heat recovery provides an energy-saving approach for air reheating in air-conditioning systems, but its dynamic performance depends strongly on the regulation of refrigerant distribution. The electronic expansion valve (EEV) controls the refrigerant flow entering the heat-recovery branch, and accurate short-horizon prediction of EEV opening can support predictive operation and supply-air state regulation. In this study, a VMD-GRU-Attention framework was proposed for direct multi-step prediction of EEV opening in an air-conditioning system with a condensation heat-recovery unit. Variational mode decomposition (VMD) was first used to decompose the original EEV opening sequence into modal components with different frequency characteristics. A gated recurrent unit (GRU) network was then used to extract temporal dependencies, and an attention mechanism was introduced to enhance the contribution of informative historical states. Experimental data collected from an actual system were used for model evaluation. Compared with RNN, TCN, LSTM and GRU, the proposed model achieved lower prediction errors and a more concentrated absolute percentage error distribution. At the 10th prediction step, MSE, RMSE, MAE and MAPE were reduced by 57.78%, 35.02%, 35.75% and 35.78%, respectively, compared with GRU. The results demonstrate the framework's effectiveness for EEV opening prediction and provide a basis for future control-oriented studies.
Sustainable buildings play a central role in reducing environmental impacts while improving resource efficiency and occupant well-being. To evaluate and promote sustainable building practices, green building rating systems have become widely adopted worldwide, with the Leadership in Energy and Environmental Design (LEED) framework being one of the most influential. As LEED has evolved from version 2009 to version 4, its lighting-related credits have shifted towards more performance-oriented and climate-responsive assessment methods. However, limited evidence exists on how these revisions have influenced lighting-related certification outcomes, particularly in hot-arid regions. This study evaluates lighting-related credit achievement following the transition from LEED v2009 (LV09) to LEED v4.0 (LV4) using a mixed-methods approach. A verified dataset of 100 LEED-certified projects was compiled, including a directly comparable subset of 69 New Construction projects (38 LV09 and 31 LV4), complemented by a qualitative review of 25 selected projects. The results show substantial improvements in Daylight (DL) credit achievement (5.3% to 45.2%) and Light Pollution Reduction (LPR) (13.2% to 61.3%) under LV4, while Quality Views (QV) remained broadly unchanged. The qualitative review identified recurring strategies involving climate-responsive daylighting, façade and solar-control measures, efficient electric-lighting systems, automated controls, and exterior-lighting management. Overall, the findings indicate that the transition to LV4 was associated with credit-specific improvements rather than uniform enhancement across all lighting categories. This study provides one of the first comprehensive evaluations of lighting-related LEED certification outcomes in a hot-arid context and offers practical evidence to support future refinement of green building assessment frameworks. The findings represent certification outcomes and documented design strategies rather than direct measurements of operational lighting performance.
