Traditional settlements have received increasing attention because of China’s rural revitalization. Traditional settlements with excellent thermal comfort in rural areas can attract urban residents, so it is vital to explore the thermal comfort of traditional settlements. For this paper, we studied Linpan settlements, which are scattered traditional settlements that are mainly composed of buildings and trees. Firstly, we visually interpreted Linpan settlements by ArcGIS. A total of 1194 Linpan settlements were classified to obtain the spatial components. The statistical results of Linpan were used in the subsequent experimental design. Then ENVI-met was used to simulate 25 different spatial forms of Linpan obtained by statistical results and orthogonal experiment to explore the most comfortable Linpan layout. The results showed the following: (1) Linpan could improve thermal comfort in both winter and summer. Adjusting the spatial arrangement could maximally increase the mean physiological equivalent temperature (PET) of the whole Linpan area by 1.03 °C in winter and reduce it by 3.02 °C in the summer. (2) At different time points, the influence of different space factors on thermal comfort was also different. The overall significance of each factor on thermal comfort was addressed as follows: vegetation coverage (highly significant) > building number (highly significant) > building form (highly significant) > vegetation distribution (significant), but the building distribution was not significant. (3) The best spatial arrangement scheme was high vegetation coverage, a large number of buildings, tri-courtyard buildings, surrounding vegetation distribution, and surrounding building distribution. The innovation of this paper lies in introduced thermal comfort into the traditional Linpan settlement, extracted spatial features of buildings and vegetation by visual interpretation combined with GIS software, and the fact that we conducted the experimental design of microclimate and thermal comfort based on spatial features. The research results can guide the outdoor thermal environment renewal design of Linpan and other traditional settlements.

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Natural ventilation is a way to reduce the energy consumption of building operations and improve the indoor living environment comfort. The venturi cap is designed with a roof, grille and wind deflector to intensify the natural ventilation of buildings. The structural parameters of the venturi cap were designed using an orthogonal design. Fluid analysis software was used for numerical simulation, and variance analysis was used to study the importance of seven influence factors: the width of the roof opening, the roof slope, the height of the wind deflector, the horizontal width of the wind deflector, the angle of the wind deflector, the angle of the grille, and the spacing of the grille slices. The results show that the most significant influencing factor is the width of the roof opening, while significant influence factors include the angle of the grille and the horizontal width of the wind deflector. Additionally, the optimum parameter combination for ventilation performance at the research level was put forward, with the proposed combination achieving a volume flow rate of 5.507 m3/s. The average temperature of the horizontal plane at a height of 1.2 m above the ground was 3.002 K lower than that without a venturi cap, which provides a reference for the optimization of indoor ventilation design in buildings in the Xichang area.

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The Trombe wall (T-wall) system is one of the most effective systems for passive solar energy utilization technology, which is of great significance for the alleviation of the energy crisis and the protection of the environment. Taking as an example Tibetan dwellings in the Sichuan–Tibet alpine valley which have installed T-walls for heating, the effects of the length of the room (Factor A), the width of the room (Factor B), the width of the opening on the north wall of the room (Factor C), and the distance from the lower edge of the opening to the floor (Factor D) on the indoor air temperature and room energy consumption are studied by orthogonal experiment and numerical simulation. Results show that the four factors all have a significant effect on the two analysis indicators. The rankings of the factors are consistent for their impact on the two analysis indicators, as, in both cases, Factor A > Factor B > Factor C > Factor D. Therefore, the influence of room configuration cannot be ignored in the optimization of T-wall design. Additionally, the optimal parameter combination for the highest indoor temperature and low energy consumption in winter is also proposed. This research can further improve the study of T-walls, and provide a reference for the thermal environment design of buildings.