In multi-parameter optimization of indoor environments, achieving a balance between the number of constructed samples and optimization efficiency remains challenging, and optimization performance is often dependent on large datasets. Therefore, achieving satisfactory optimization results with a limited number of samples remains a major challenge in the field of indoor environmental optimal design. To address this, this study proposed a sample construction method integrated with proper orthogonal decomposition (POD), which is further coupled with the Kriging surrogate model to develop two surrogate modeling approaches: multi-fidelity Kriging surrogate model based on POD (MFK-POD) and single-fidelity Kriging surrogate model based on POD (SFK-POD). These two approaches achieve three key improvements. First, MFK-POD attains predictive accuracy comparable to the classical ordinary Kriging (OK) model while reducing computational time by 12.4%, and SFK-POD achieves a 21.7% reduction in computational time, thereby enabling rapid optimization. Second, the study identifies the “moderation principle” in POD-based sample expansion, where setting the expansion ratio n = 1 (i.e., doubling the initial sample size) achieves an optimal balance between efficiency and accuracy. Finally, in the optimization design of a typical indoor environment, MFK-POD achieves a 54.6% reduction in CO₂ target concentration, a 17.3% reduction in energy consumption when compared with the optimization results of existing methods, and a prediction deviation of less than 2%. In addition, the Spacing value of the Pareto solution set is reduced by 70.2%, and the hypervolume (HV) value is increased by more than 1 time. The SFK-POD model is suitable for time-sensitive scenarios requiring lower precision and rapid iteration, while the MFK-POD model is better suited for engineering optimization tasks that demand a balance between accuracy and efficiency. This framework provides a novel methodological basis for high-efficiency and high-precision multi-parameter optimization in complex thermal-humid environments.

Accurate thermal comfort simulation methods can significantly enhance both the effectiveness and efficiency of cabin thermal comfort design. However, current thermal comfort simulation methods often overlook the interaction between environmental factors and human physiological responses, particularly in the context of cabin thermal comfort simulations under solar radiation conditions, where there is a lack of standardized approaches. This study establishes a bidirectional coupling simulation framework that incorporates the interaction between environmental factors and human physiological regulation. The proposed method integrates CFD, thermophysiological models, and thermal psychological models. Specifically, the thermophysiological component of the framework compares three models: the JOS-3 model, the Fiala model, and the TCM model. The thermal psychological model utilizes the Berkeley model. The computational accuracy of the proposed bidirectional coupling simulation framework is evaluated under both steady-state office environments and transient outdoor parking cases. Furthermore, the simulation results are compared with those obtained from three uncoupled thermal comfort evaluation models—PMV, DTS, and Lai's model—under transient environmental conditions. The results demonstrate that the CFD-JOS3-Berkeley bidirectional coupling simulation method achieves the lowest prediction error for both local and mean skin temperatures. Its overall thermal sensation prediction accuracy is superior to other thermal comfort evaluation methods, improving by 5.16, 3.91 and 3.75 times compared to non-coupled thermal comfort evaluation models PMV, DTS, and Lai's. The study further highlights that coupled simulation calculations should prioritize the use of local thermal insulation values as inputs to human thermophysiological models, with special emphasis on core body regions and exposed skin areas such as the head, hands, and lower legs in summer conditions. This research establishes a high-precision thermal comfort simulation method suitable for transient cabin environments under solar radiation, offering a reliable tool for evaluating cabin thermal comfort.

The two-stage electrostatic precipitator is widely used to purify oil mist particles. However, there is limited research on the influences of relative humidity, particle deposition characteristics, and the generation of gaseous pollutants. Therefore, this paper established a numerical model of the electrostatic oil mist purifier and applied it to a two-stage electrostatic precipitator. Then the model was used to investigate the corona discharge characteristics under different relative humidity conditions in the charged zone, the particle deposition characteristics, the purification efficiency, the ozone concentration distribution, and the oil vapor concentration distribution in the collection zone. The results indicate that, with a constant temperature, the corona current decreases as relative humidity increase, and there is a quadratic relationship between relative humidity and current. The variation in relative humidity has little impact on the purification efficiency. The maximum ozone concentration occurs near the electrode line, and its concentration is influenced by the discharge current and inlet airflow velocity. The oil vapor concentration reaches its maximum value at the side plates, with a value of 19 ppb, while it reaches the minimum value at the collecting zone electrode plate, with a value of 2 ppb. The temperature is the main factor affecting the volatilization of the oil film, with higher temperatures resulting in higher oil vapor.

The cabin air pressure remains lower than the horizontal atmospheric pressure when the airplane is in flight. Air pressure is one of the parameters that must be taken into consideration while studying the thermal environment of an airplane cabin. There are still no reference values for aircraft cabins despite the fact that numerous studies on low pressure heat transfer have demonstrated the connection between convective heat transfer coefficient (CHTC) and air pressure. In this paper, a correction method for CHTC under low pressure conditions was established by using the dummy heat dissipation in the low-pressure cabin experiment. On this basis, a thermal environment simulation model was developed, then was applied to the simulation of a seven-row aircraft cabin containing 42 passengers, and the CHTC and heat loss of dummy surface in the cabin were obtained. Finally, the results of PMV calculated by using heat dissipation and air parameters at sampling points were compared. The results show that the modified CHTC can accurately reflect the cabin thermal environment under low pressure conditions, and the correction of CHTC can be realized by adjusting the turbulent Prandtl number, which is nonlinear correlated with the pressure. The simulation results of the thermal environment in the seven-row cabin show that the CHTC changes by about 42% before and after modification. The air pressure decreases during take-off, which reduces the average CHTC of the crew surface from 5.09 W/(m²·K) to 4.56 W/(m²·K), but the air temperature rises by about 0.2 ℃ as a whole. The deviation of PMV results calculated by using simulated heat loss data and using air parameters of measuring points in space is up to 0.5, but the latter is representative for calculating the thermal comfort level of the whole cabin.

High-concentration oil mists can cause serious health problems to workers, which are generally mitigated by ventilation and purification systems. However, the coupling relationship between these systems is not clear. In this study, the effects of purifier outlet direction, purification air volume, installation height, and purification efficiency on indoor oil mist distribution were investigated by numerical simulation using an actual machining factory. The mitigation of oil mist in various combinations of ventilation and purification systems was also discussed. The results show that the outlet direction of the purifier has a great influence on the distribution of oil mist in the factory, and the maximum difference of oil mist concentration in the breathing zone under different orientations is 17%. The best purifier outlet direction is vertically upward. When the purifier outlet direction is upward, a larger purification air volume is beneficial for contaminant removal, and a lower purifier exhaust installation height is helpful for oil mist discharge from the bottom of the factory and reducing the concentration of oil mist in the breathing area. The oil mist concentration of purifier exhaust increases from 0 to 2 mg/m³ and the oil mist concentration in the breathing zone increases by 67%. The combined system of purification system with the roof exhaust system and displacement ventilation system has the optimal pollution removal efficiency and the lowest concentration of oil mist in the breathing zone compared to other systems. The research results can provide a reference for the design, installation, and operation of ventilation and purification systems in machining factories.