The geometric shape of the roof and the opening position are important parameters influencing the internal cross-ventilation of buildings. Although there has been extensive research on natural ventilation, most of it has focused on flat or sloping roofs with the same opening positions. There is still limited research on the impact of different opening positions and sloping roofs on natural ventilation. In this study, computational fluid dynamics (CFD) was used to investigate the air exchange efficiency (AEE) in general isolated buildings. These buildings encompassed three distinct opening configurations (top–top, top–bottom, and bottom–top) and six varying slope angles for gable roofs (0°, 9°, 18°, 27°, 36°, and 45°). Computational simulations were carried out using the SST k-omega turbulence model, and validation was performed against experimental data supplied by the Japanese AIJ Wind Tunnel Laboratory. Grid independence validation was also conducted to ensure the reliability of the CFD simulation results. The study revealed that the highest AEE was 48.1%, achieved with the top–bottom opening configuration and a gable roof slope angle of 45°. Conversely, the lowest AEE was 31.4%, attained with the bottom–top opening configuration and a gable roof slope angle of 27°. Furthermore, it was observed that when the opening configuration was set to top–top and bottom–top, the slope angle of the gable roof had minimal influence on AEE, with an average AEE of only around 33%. When the opening configuration was top–bottom, it was found that there was a positive correlation between the gable roof slope angle and AEE.

This study proposes a Transformer–NSGA-III multi-objective optimization framework for high-rise residential buildings in Haikou, a coastal city characterized by a hot summer and warm winter climate. The framework addresses four conflicting objectives: Annual Energy Demand (AED), Predicted Percentage of Dissatisfied (PPD), Global Cost (GC), and Life Cycle Carbon (LCC) emissions. A localized database of 11 design variables was constructed by incorporating envelope parameters and climate data from 79 surveyed buildings. A total of 5000 training samples were generated through EnergyPlus simulations, employing jEPlus and Latin Hypercube Sampling (LHS). A Transformer model was employed as a surrogate predictor, leveraging its self-attention mechanism to capture complex, long-range dependencies and achieving superior predictive accuracy (R² ≥ 0.998, MAPE ≤ 0.26%) over the benchmark CNN and MLP models. The NSGA-III algorithm subsequently conducted a global optimization of the four-objective space, with the Pareto-optimal solution identified using the TOPSIS multi-criteria decision-making method. The optimization resulted in significant reductions of 28.5% in the AED, 24.1% in the PPD, 20.6% in the GC, and 18.0% in the LCC compared to the base case. The synergistic control of the window solar heat gain coefficient and external sunshade length was identified as the central strategy for simultaneously reducing energy consumption, thermal discomfort, cost, and carbon emissions in this hot and humid climate. The TOPSIS-optimal solution (C = 0.647) effectively balanced low energy use, high thermal comfort, low cost, and low carbon emissions. By integrating the Energy Performance of Buildings Directive (EPBD) Global Cost methodology with Life Cycle Carbon accounting, this study provides a robust framework for dynamic economic–environmental trade-off analyses of ultra-low-energy buildings in humid regions. The work advances the synergy between the NSGA-III and Transformer models for high-dimensional building performance optimization.

Energy conservation and carbon reduction in the building sector are critical to addressing climate change. This paper presents a building-oriented critical review of wind-driven triboelectric nanogenerators (TENGs), aiming to clarify their research maturity, realistic functional roles, and key limitations in the built environment. Bibliometric analysis reveals a rapid growth of TENG-related studies, with research activity concentrated in East Asia and North America, while work directly connected to architectural applications remains limited. Keyword evolution indicates a shift from fundamental energy-conversion mechanisms toward device optimization and sensing-oriented functions. Based on a structured review, two representative device categories—rotational systems and flutter-based designs—are examined with respect to their operating characteristics and suitability for low-wind building conditions. Reported building-related applications are currently focused on hybrid rooftop harvesting concepts and self-powered sensing components integrated into building systems, particularly for environmental monitoring. However, most demonstrations remain at a laboratory or prototype level, and their architectural integration is constrained by issues including low power output, durability, environmental adaptability, and system-level compatibility. Rather than positioning wind-driven TENGs as near-term power sources for buildings, this review highlights their more realistic short-term potential as supplementary micro-energy units and self-powered sensors, while emphasizing the technical and architectural challenges that must be addressed before broader building adoption can be achieved.

In the context of the energy crisis and the urgency of passive design in contemporary architecture, this study focuses on the Tujia-style Sanheyuan in southeastern Chongqing, China, which is highly adaptable to local climatic conditions. Using field surveys, architectural mapping, computational fluid dynamics numerical simulations, and multi-parameter comparative analysis, this study systematically explores the relationship between the geometric form of the Sanheyuan and its courtyard ventilation performance. Based on the Tujia construction scale modulus, this study summarizes the basic prototype of the Sanheyuan, analyzes the selection paths of its three sets of construction parameters, and constructs 48 typical courtyard models for wind environment simulation. By introducing five evaluation indicators—wind speed uniformity coefficient, proportion of strong wind zone area, proportion of calm wind zone area, and unit area wind rate—this study comprehensively assesses the impact of Sanheyuan design parameters on courtyard wind environment adaptability. This study concludes that specific spatial design parameters of the Tujia-style Sanheyuan significantly influence wind environment adaptability, offering quantitative guidance for climate-responsive and culturally informed architectural design. This study found that the optimal side room width-to-depth ratio is [1.00, 0.86, 0.83]; the optimal ridge height-to-stilt height ratio is [4.29, 8.00, 2.96]; and the optimal building footprint-to-side room area ratio is [3.01, 5.06, 4.75].

Under extreme high-temperature conditions, heat accumulation in rooftop photovoltaic (PV) arrays can substantially reduce PV conversion efficiency and output power. To improve the thermal and power-generation performance of rooftop PV systems, this study developed a computational fluid dynamics (CFD) model for a rooftop PV array and validated it using field measurements from Chongqing, China. The relative root mean square errors (rRMSEs) between simulated and measured backsheet temperatures at the three measurement points were 6.31%, 7.52%, and 8.45%, respectively, indicating acceptable model accuracy. The effects of mounting height, tilt angle, and front-to-rear row spacing on PV backsheet temperature, conversion efficiency, and output power were then investigated. A central composite design (CCD) within response surface methodology (RSM) was used to establish regression models linking the design variables to the objective functions. Finally, an NSGA-III-based multi-objective optimization framework combined with TOPSIS was used to identify the optimal configuration. For the rooftop PV array studied under extreme summer conditions in Chongqing, the TOPSIS-selected compromise solution corresponded to a mounting height of 0.90 m, a tilt angle of 15.63°, and a front-to-rear row spacing of 2.96 m. Compared with the original configuration, the optimized passive installation geometry reduced the peak PV backsheet temperature by 2.3 °C without active cooling, water consumption, or additional energy input. Under the same meteorological and irradiance conditions, this temperature reduction increased conversion efficiency by 0.5% and output power by 0.4%. Detailed inter-row short-wave shading and electrical mismatch were not explicitly modeled. Therefore, the row-spacing effect mainly reflects changes in ventilation and module temperature under the same irradiance input. The proposed framework provides a practical reference for installing and optimizing rooftop PV arrays in hot-climate regions.

Respiratory infectious diseases pose substantial transmission risks in enclosed public-transport environments. Under a defined fully seated reference scenario, this study examines whether the same HVAC supply parameter governs two respiratory-particle control objectives in a subway carriage: whole-carriage particle removal and local seated breathing-zone exposure. Computational fluid dynamics (CFD) simulations, single-factor analyses, an L16 orthogonal design, analysis of variance (ANOVA), and grey relational analysis (GRA) were used to evaluate supply velocity, temperature, and angle. The results reveal an objective-dependent control hierarchy. Supply velocity is the leading factor for whole-carriage removal (contribution rate, 40.14%; p = 0.047), whereas supply angle contributes most to the seated breathing-zone particle proportion (59.30%), although the corresponding ANOVA result does not reach statistical significance at the 0.05 level (p = 0.056). The two single-objective optima share the same velocity and angle but differ in temperature, indicating a partial rather than complete mismatch. GRA identifies 2.0 m/s, 24 °C, and 0° as the best compromise among the investigated cases. This combination is specific to the modeled carriage, passenger arrangement, source location, and operating conditions. The more generalizable finding is that global clearance and local breathing-zone exposure are governed by different control variables.