In the age of digitalization and big data, cooling systems in data centers are vital for maintaining equipment efficiency and environmental sustainability. Although many studies have focused on the classification and optimization of data center cooling systems, systematic reviews using bibliometric methods are relatively scarce. This review uses bibliometric analysis to explore the classifications, control optimizations, and energy metrics of data center cooling systems, aiming to address research gaps. Using CiteSpace and databases like Scopus, Web of Science, and IEEE, this study maps the field’s historical development and current trends. The findings indicate that, firstly, the classification of cooling systems, optimization strategies, and energy efficiency metrics are the current focal points. Secondly, this review assesses the applicability of air-cooled and liquid-cooled systems in different operational environments, providing practical guidance for selection. Then, for air cooling systems, the review demonstrates that optimizing the design of static pressure chamber baffles has significantly improved airflow uniformity. Finally, the article advocates for expanding the use of artificial intelligence and machine learning to automate data collection and energy efficiency analysis, it also calls for the global standardization of energy efficiency metrics. This study offers new perspectives on the design, operational optimization, and performance evaluation of data center cooling systems.

Thermosetting polymers offer a wide range of applications in modern industries, including coatings, the automotive and aerospace industries, and furniture manufacturing. The curing process, which is a key step in the application of such materials, has become a research hotspot. More specifically, significant research efforts have been devoted toward shortening the curing cycle and reducing curing energy consumption without affecting product quality. Two common curing methods, namely, infrared (IR) curing and hot air convection curing, have been commonly employed. IR curing technology demonstrates certain advantages, such as high energy efficiency and adaptability, compared to traditional convection curing technology. Moreover, it has achieved desirable results in engineering applications and research. In this review, the current research on IR curing technology is presented in detail based on two fundamental aspects: the heat transfer process and the curing process. This article provides a comprehensive overview of the IR curing heat transfer process in terms of IR heating equipment, heat transfer monitoring devices, heat transfer models, and heat transfer simulation methods. Moreover, it summarizes and compares the basic research methods, equipment, and theoretical models involved in the curing process. In addition, it describes the non-thermal effect and its impact on the properties of cured products. This study describes the author’s perspective and opinions on the research direction in IR radiation-based curing technology. This literature review concludes that IR curing technology has strong research value and application prospects, particularly in fields requiring low-temperature rapid curing of thermosetting polymers.

A fast evacuation from buildings to emergency shelters is necessary and important after the occurrence of a disaster. We investigated the variations in physical behaviors and cognition processes while finding emergency shelter. The on-site emergency-shelter-finding experiments were conducted in Beijing, China. Participants performed the task by using a wearable eye-tracking device. We aimed to assess three eye metrics: fixation counts, mean fixation duration, and visual attention index, to perform cognitive searching analysis for the environmental elements. The results showed that most people spend more fixation time on digital maps (297.77 ± 195.90 ms) and road conditions (239.43 ± 114.91 ms) than signs (150.90 ± 81.70 ms), buildings (153.44 ± 41.15 ms), and plants (170.11 ± 47.60 ms). Furthermore, most participants exhibit hesitation and retracing behaviors throughout the wayfinding process. The participants with relatively rich disaster experience and a proactive personality exhibit better performance in the shelter-finding task, such as a shorter retracing distance (p = 0.007) and nearer destination (p = 0.037). Eye metrics, together with the questionnaire, can mirror the complexity and heterogeneity of evacuation behavior during emergency shelter-finding. In addition, this also provides insights for the optimization of guidance sign systems and improvements in emergency management.

Catalytic combustion can effectively and cleanly convert the chemical energy of fossil fuels into infrared radiation energy. However, there is little research on the use of this technology to cure powder coatings. Therefore, catalytic infrared heating equipment based on a Pt/Al₂O₃ noble metal catalyst was designed, constructed, and tested in this study. The optimal curing parameters for the catalytic infrared curing process for powder coatings were determined via experiments at 220 °C for 3 min and 230 °C for 2 min. As the curing temperature increased and the curing time increased, the mechanical properties of the coating were found to improve. However, the gloss of the coating was reduced and the color darkened. A one-dimensional heat transfer model was developed to investigate the heat transfer process for powder coatings. This study introduced an internal heat source for the first time, and the heat transfer process for polyester-based powder coatings with different substrate thicknesses was numerically simulated. The numerical simulations demonstrated that the efficiency of the heat transfer between the catalytic infrared gas supply and the coating surface was 0.4. When the substrate thickness was 1 mm, the coating was most rapidly cured at 230 °C. When the substrate thickness was ≥2 mm, the most rapid curing occurred at 220 °C.

Nowadays, relevant data collected from hospital buildings remain insufficient because hospital buildings often have stricter environmental requirements resulting in more limited data access than other building types. Additionally, existing window-opening behavior models were mostly developed and validated using data measured from the experimental building itself. Hence, their accuracy is only assessed by the algorithm’s evaluation index, which limits the model’s applicability, given that it is not tested by the actual cases nor cross-verified with other buildings. Based on the aforementioned issues, this study analyzes the window-opening behavior of doctors and patients in spring in a maternity hospital in Beijing and develops behavioral models using logistic regression. The results show that the room often has opened windows in spring when the outdoor temperature exceeds 20 °C. Moreover, the ward windows’ use frequency is more than 10 times higher than those of doctors’ office. The window-opening behavior in wards is more susceptible to the influence of outdoor temperature, while in the doctors’ office, more attention is paid to indoor air quality. Finally, by embedding the logistic regression model of each room into the EnergyPlus software to simulate the CO₂ concentration of the room, it was found that the model has better applicability than the fixed schedule model. However, by performing cross-validation with different building types, it was found that, due to the particularity of doctors’ offices, the models developed for other building types cannot accurately reproduce the window-opening behavior of doctors. Therefore, more data are still needed to better understand window usage in hospital buildings and support the future building performance simulations of hospital buildings.