The proper application of machine learning and genetic algorithms in the early stage of library design can obtain better all-around building performance. The all-around performance of the library, such as indoor temperature, solar radiation, indoor lighting, etc., must be fully considered in the initial design stage. Aiming at building performance optimization and based on the method of “generative design”, this paper constructs the library’s comprehensive performance evaluation workflow and rapid prediction combined with the LightGBM algorithm. A library in a cold region of China is taken as the research object to verify its application. In this study, 5000 scheme samples generated in the iterative genetic optimization process were taken as data sets. The LightGBM algorithm was used to classify and predict design schemes, with a precision of 0.78, recall rate of 0.93, and F₁-Score of 0.851. This method can help architects to fully exploit the optimization potential of the building’s all-around performance in the initial stage of library design and ensure the timely interaction and feedback between design decisions and performance evaluation.

Wall-mounted solar chimneys use solar radiation to heat the air inside the chimney cavity and use thermal pressure to create natural convection. Applying this principle allows for the indoor ventilation of a building without energy consumption. However, in wall-mounted solar chimney designs, different air inlet and outlet design dimensions can have varying degrees of impact on the effectiveness of wall-mounted solar chimney ventilation. In order to analyze the internal airflow state and airflow temperature field distribution of wall-mounted solar chimneys, physical models of wall-mounted solar chimneys with six different air outlet-to-inlet cross-sectional area ratios were developed in this research work. Before numerical simulation analysis, heat transfer analysis of the wall-mounted solar chimney’s structural components and airflow channels was carried out, and corresponding mathematical heat transfer models were established. The internal flow state and temperature distribution characteristics of a wall-mounted solar chimney were analyzed by steady-state simulations using the computational fluid dynamics software, Ansys Fluent. Finally, transient simulation calculation analysis was conducted under six different S-value models to investigate the variation in the natural ventilation of a single-story building’s wall-mounted solar chimney for a whole day. The study showed that under the same simulation conditions, 80% ≤ S < 100% effectively avoided the formation of vortices in the internal airflow of the wall-mounted solar chimneys and kept the ventilation effect of wall-mounted solar chimneys at a high level. The results of this study provide a reference for the optimization of research on the design of the air inlet and outlet structures of wall-mounted solar chimneys for single-story buildings.

Net-zero energy buildings (NZEB) have received widespread attention for their excellent energy and carbon reduction potential in various countries. However, relatively little research has been conducted on the life performance of its primary form: the ultra-low energy building (ULEB). This paper proposes an optimization method combining meta-models to investigate the carbon reduction potential of ultra-low energy buildings in severely cold regions of China. The XGBoost algorithm is used to construct a meta-model of building performance, and the grid search method is used to obtain a high-precision meta-model with an R² of 0.967. Secondly, NSGA-II is used to find passive technical solutions based on the meta-model that minimize the global warming potential (GWP), global cost (GC), and operation energy consumption (OE). Finally, the variables affecting the life-cycle performance of buildings were ranked by sensitivity analysis. The results show that GWP, GC, and OE are reduced by 12.7%, 6.7%, and 7.4% compared with the original building through the optimization process proposed. Sensitivity analysis showed that for GWP, the top four sensitivities are window type (TW) > WWR of south wall (WWRS) > roof insulation thickness (IR) > WWR of north wall (WWRN). For GC, the top four sensitivities are: TW > WWRS > IR > WWR of west wall (WWRW); for OE, the top four sensitivities are: TW > IR > WWRS > WWRN. This paper’s optimization framework and research results can effectively guide the design of the ULEB in severely cold regions.

As a type of passive architectural structure, wall-mounted solar chimneys enhance the natural ventilation volume of a building’s interior, and maximize reductions in the building’s operational energy consumption. They are indispensable in the building’s energy conservation and emission reduction. Therefore, measuring the wall-mounted solar chimney’s flow characteristics and relevant index parameters is particularly important. This paper uses a combination of full-scale experiments and numerical simulation to conduct a detailed analysis of the wall-mounted solar chimney. Four different radiation models, namely DO (discrete ordinates), S2S (surface-to-surface), MC (Monte Carlo), and Rosseland are used for comparison, and the results of the numerical simulation are compared with the experimental data. The results show that the maximum turbulent viscosity of the fluid predicted by the S2S radiation model is higher than that of the MC and DO models by 16.87% and 8.44%, respectively. The errors of the DO radiation model in the midline and glass cover plate direction concerning the experimental results are only 0.33% and 0.15%, respectively. The mistakes of the MC radiation model in these two directions are 0.51% and 0.47%, respectively. The DO radiation model is more suitable in numerical simulation predictions related to the wall-mounted solar chimney.

In the context of global warming, the focus on applying and researching double–skin facade (DSF) systems to reduce energy consumption in buildings has significantly increased. However, researchers have not thoroughly examined the performance and applicability of DSFs in severe cold regions with high winter heating demands. This study aims to evaluate the potential application of DSFs in the harsh cold cities of Northwest China and investigate their role in enhancing energy efficiency in large public buildings. Through energy consumption simulation and a comprehensive evaluation using the TOPSIS entropy weight method, the effects of applying 20 DSF schemes in four cold cities in Xinjiang (Kashgar, Urumqi, Altay, and Turpan) were analyzed. The experimental results indicate that the average EUI energy–saving rates in Kashgar, Urumqi, Altay, and Turpan are 64.75%, 63.19%, 56.70%, and 49.41%, respectively. South–facing orientation is deemed optimal for DSF in Xinjiang cities, with the highest energy–saving rate reaching 15.19%. In Kashgar, the energy–saving benefits of west–facing DSF surpass those of north–facing DSF. Conversely, the order of orientation benefits for other cities is south, north, west, and east. An analysis of heating, cooling, and lighting energy consumption reveals that Box Windows exhibit superior heating energy efficiency, while Corridors are more effective for cooling. This characteristic is also evident in the optimal installation orientation of various types of curtain walls. Given the relatively higher demand for heating compared to cooling in urban areas, Box Windows yields significant benefits when facing south, west, or north; conversely, if there is a high demand for urban cooling, Corridors should be considered in these three directions. Multistorey DSF systems are suitable for east–facing buildings in Xinjiang cities. Selecting suitable DSF schemes based on specific conditions and requirements can reduce building energy consumption. The research findings offer theoretical guidance for designing and implementing DSF in diverse cities in cold regions.