Through their open space layout, rich green configuration and low floor area ratio (FAR), low-density commercial blocks show significant advantages in creating high-quality outdoor thermal comfort (Universal Thermal Climate Index, UTCI) environment, reducing regional energy consumption load (building energy consumption, BEC) potential, providing pleasant public space experience and enhancing environmental resilience, which are different from traditional high-density business models. This study proposes a workflow for morphological design of low-density commercial blocks based on parametric modeling via the Grasshopper platform and the NSGA-II algorithm, which aims to balance environmental benefits (UTCI, BEC) and spatial efficiency (FAR). This study employs EnergyPlus, Wallacei and other relevant tools, along with the NSGA-II algorithm, to perform numerical simulations and multi-objective optimization, thus obtaining the Pareto optimal solution set. It also clarifies the correlation between morphological parameters and target variables. The results show the following: (1) The multi-objective optimization model is effective in optimizing the three objectives for block buildings. When compared to the extreme inferior solution, the optimal solution that is closest to the ideal point brings about a 33.2% reduction in BEC and a 1.3 °C drop in UTCI, while achieving a 102.8% increase in FAR. (2) The impact of design variables varies across the three optimization objectives. Among them, the number of floors of slab buildings has the most significant impact on BEC, UTCI and FAR. (3) There is a significant correlation between urban morphological parameters–energy efficiency correlation index, and BEC, UTCI, and FAR.

University dormitories in cold climate regions face the dual challenges of high heating energy consumption and poor outdoor pedestrian comfort during winter. Existing studies on university dormitories have primarily focused on individual building performance optimization, while insufficient attention has been paid to the optimization of dormitory cluster layouts and their multi-objective performance. To address this gap, this study establishes a parametric multi-objective optimization framework to simultaneously minimize building energy use intensity, minimize wind speed at pedestrian height, and maximize outdoor thermal comfort. Based on three floor area ratio scenarios, 24 dormitory prototypes are extracted from three building typologies: row-type buildings, detached buildings, and enclosed buildings. The optimization process was implemented on the Grasshopper platform using the NSGA-II algorithm. Cluster analysis is conducted on the Pareto front, and Pearson correlation analysis is applied to investigate the relationships between six urban morphological parameters and the three optimization objectives. The results indicate that: (1) enclosed buildings (E-1 type) and detached buildings (D-1 type) dominate the Pareto-optimal solution set; (2) high-FAR buildings are predominantly distributed in the northeastern part of the site, while public spaces are concentrated in the central-southern area; (3) correlation analysis indicates that shape coefficient (SC) exhibits the strongest correlations with the three objectives; and (4) compared with dominated solutions, Pareto-optimal solutions reduce WS by 10.46% and EUI by 6.57%, while improving UTCI by 0.05 °C. This study provides quantitative decision-making support for efficient planning and low-carbon design of university dormitory clusters in cold climate regions.

College student military training is an organized, high-intensity, short-term militarized activity in China; this study aims to explore the differences in thermal perception between different intensities of military training. Questionnaires and microclimate measurements were conducted during summer military training in cold regions, including the Protective and Rescue Training and Assessment (PRTA), Formation Training (FT), the Shooting and Tactical Training and Assessment (STTA), the Route March (RM), and Dagger Practice (DP). The results indicated that (1) there was no significant correlation between the intensity of the activity and votes on thermal perception. The strongest thermal sensations, the lowest comfort, and the lowest thermal acceptability were experienced during FT, with a lower activity intensity. (2) Air temperature (T_a), globe temperature (T_g), relative humidity (RH), mean radiant temperature (T_mrt), and solar radiation (G) had significant effects on the TSV. (3) FT involved the lowest neutral temperatures (NUTCI/NPET), while DP and RM training had the highest NUTCI and NPET values, respectively. The neutral temperature range during military training was narrower compared to that in other aerobic activities. This study reveals, for the first time, the non-traditional correlation between military training intensity and thermal perception, confirming the specificity of thermal sensations in mandatory training and providing a theoretical basis for optimizing military training arrangements and developing thermal protection strategies.