In the context of normalized epidemic prevention and control, the impact of masks and protective clothing on personal thermal comfort cannot be overlooked. To investigate the thermal comfort of outdoor personnel under various protective conditions, this study took Wuhan as an example and evaluated the outdoor thermal comfort of subjects under different protection and activity conditions through thermal environment monitoring, physiological measurements, and thermal comfort questionnaires. The results show significant differences in the PET thermal comfort baseline under various protective conditions. To address the problem that most areas have not yet established state-specific thermal comfort baselines, a State Outdoor Comfort Index (SOCI) model was developed to correct the insensitivity of PET indicators to clothing thermal resistance and metabolic rate. Finally, the performance of the SOCI model was evaluated through statistical indicators, demonstrating its good predictive capability. This study provides appropriate quantitative indicators to improve the thermal comfort of outdoor personnel.

Currently, people in crowded indoor spaces are required to wear a variety of personal protective equipment to curb the spread of COVID-19. This study aimed to investigate the effects of wearing four types of personal protective equipment (unprotected, wearing masks, wearing face shield and wearing medical protective clothing) on human thermal perception and physiological responses in indoor crowded spaces in summer. The experiment was conducted in a climate chamber designed to simulate the indoor crowded spaces. Environmental parameters of climate chamber (air temperature, relative humidity and wind speed), physiological parameters of subjects (wrist skin temperature and pulse rate), and subjective perceptions (thermal sensation and thermal comfort) were collected during the experiment. The experimental results showed that medical protective clothing has the most obvious blocking effect on heat exchange between human and environment. Thermal sensation in state 4 (wearing medical protective clothing) was significantly (p < 0.05) higher than that in other states. The study of physiological parameters showed that the wrist skin temperature and pulse rate under different protection states increased with the increase of room temperature. Through regression analysis, the thermal sensation estimation model of protective personnel in indoor crowded spaces based on wrist skin temperature and pulse rate was established. The adjusted R² and RMSE of all models were above 82% and less than 1, indicating that the established thermal sensation model had a good prediction effect.

As most residents spend more than 90% of their time in buildings, acceptable and reasonable control of both indoor thermal comfort and air quality is imperative to ensure occupants’ health status and work productivity. However, current control strategies generally take either thermal comfort or indoor air quality as a single loop, rather than the concurrent control of two. To analyze their mutual influence, this study investigated the performance of three multi-control approaches, i.e., proportional integral derivative (PID) control of thermal comfort and a fixed outdoor air ratio, PID control of thermal comfort and design outdoor air rate, and PID control of thermal comfort and occupancy-based demand-controlled ventilation. As a pilot study, three typical control methods were implemented to a multi-zone building via OpenModelica modeling. The results indicate that indoor air temperature can be well-maintained under three control methods, however, the CO₂ concentration under the fixed outdoor air ratio was over 1000 ppm, leading to poor indoor air quality. The control strategy with the design outdoor air rate could not properly ensure the CO₂ concentration, due to the over-ventilated or under-ventilated phenomena, subsequently resulting in unnecessary energy waste. The occupancy-based demand controlled ventilation could maintain the CO₂ concentration under the set-point with an intermediate power energy utilization.

A cruise ship, which has large-scale open spaces, has an uneven cabin thermal environment in the cruise public space, leading to overcooling or poor cooling issues. Therefore, optimizing the thermal environment of public spaces during a cruise should be the priority. According to the space functions of the cruise ship, the large public space is divided into three subzones: the entertainment area (Subzone I), the round-table dining area (Subzone II), and the square-table dining area (Subzone III). To create a uniform, stable, and comfortable thermal environment, this study proposes a subzone-based temperature setting approach to independently adjust the thermal environment of each subzone. Coupling simulation of building energy modeling (BEM) and computational fluid dynamics (CFD) was adopted in this study to determine proper temperature setpoints of the subzones under different occupancy rates. The results indicate that, compared with a single-temperature setpoint for the entire public space, the subzone-based temperature setpoints could achieve a uniform thermal environment. The average temperature difference among the three subzones was 0.68 °C. Moreover, the airflow between two adjacent subzones considerably affected the BEM results of energy consumption of the air-conditioning system.

Aiming at the issues of unreasonable cooperation schemes and inappropriate setting of parameters of the refrigeration system with multi-chiller plants, this paper presents a cooperative optimization method to improve the energy performance of the system composed of water-cooled chillers and air-cooled heat pumps. The cooperative optimization process includes scheme optimization and parameter optimization. To content the dynamic cooling load, the working sequence of air-cooled heat pumps and water-cooled chillers with variable frequency chilled water pumps is first optimized. Based on the optimal scheme, a back-propagation neural network (BPNN) coupled with particle swarm optimization (PSO) is implemented to explore the preferred operating parameters of multiple chiller plants corresponding to the best coefficient of performance (COP). Compared with the performance of the initial operation module, the energy consumption of the water pump and fan decreases by over 50%, and the COP of the refrigeration system is improved by 16% (COP = 3.85) through the scheme operation. After parameter optimization, the total energy consumption is reduced by 21.7%, and COP is increased by 26.5% (COP = 4.20). Therefore, the proposed cooperative optimization method can provide useful operation guidance for the refrigeration system with multi-chiller plants.

With the increasing of building energy consumptions, the related issues of energy crisis and environmental pollution become more and more prominent. As an effective energy-saving technology, the passive house (PH) has been widely applied in China to reduce the building energy utilization. However, the design and application of PH vary with different climate conditions. Therefore, it is significant to conduct the parameterization of PH and propose a suitable design zoning of PH in China. In our study, a comprehensive feasibility analysis of the implementation of PH is performed, which chooses 31 representative cities covering 5 climatic regions. The sensitivity analysis firstly filters the key parameters that heavily affect energy consumption. The results indicate that the key parameters include external wall heat transfer coefficient (WU), basement ceiling heat transfer coefficient (BCU), solar heat gain coefficient (SHGC), glass G value (UG), heat recovery efficiency (HERE) and humidity recovery efficiency (HURE). Then, with the multiple regression approach, the values of key parameters are optimized. Based on the determined values of sensitive parameters, the design zoning of PH in China is finally proposed, which can guide the design of PH as well as enhance the application of PH in China.