During severe accidents in nuclear power plants, the Main Control Room (MCR) Emergency Habitability System (VES) maintains a suitable thermal environment for operators and equipment to prevent accident escalation. However, existing VESs often fail to provide sufficient cooling capacity for the required 72-hour period. Considering the complexity and importance of the VES, this study integrates passive components to establish a passive cooling system that enhances cooling performance with minimal structural modification. Experimental and numerical analyses are conducted to evaluate the effects of operational and structural parameters on system cooling capacity and to determine the optimal configuration. Results indicate that the active chilled beam (ACB) contributes over 70% of the total cooling capacity, while the vortex tube accounts for less than 30%. Increasing the ACB entrainment ratio is an effective approach to enhance system performance, and the ejector works synergistically with the ACB to promote temperature reduction. Raising the initial room temperature is more effective in increasing total cooling output than reducing water temperature or increasing water flow rate, primarily because shortcircuiting airflow occurs around the ACB, leading to poor indoor air circulation. To address this, the ACB should be installed flush with the ceiling, and a 30 degrees supply angle under the vertical supply mode provides the optimal setup. Moreover, excessively high supply water temperature, low water flow rate, or insufficient compressed air pressure significantly reduces cooling performance. The findings offer a low-intervention and adaptable method to improve the emergency habitability of the VES.

Non-uniform airflow is common in laminar flow operating rooms, but its effect on workstation-level thermal exposure and PMV–TSV deviation remains unclear. This study combined field measurements and computational fluid dynamics (CFD) simulations to investigate airflow characteristics, thermal sensation, and PMV–TSV deviation at different staff workstations. Field measurements quantified the local thermal environment and subjective thermal responses, while CFD simulations supported the interpretation of spatial airflow patterns. The results showed that air temperature was relatively uniform across the occupied zone, whereas airflow distribution varied markedly among workstations. The operating-table region generally showed moderate-to-high air velocity and smaller velocity fluctuations, whereas peripheral workstations showed lower mean velocity, larger fluctuations, and more irregular airflow exposure. TSV values were consistently higher than PMV predictions, with PMV–TSV differences ranging from 0.20 to 0.38. The deviation was generally larger at peripheral workstations, where airflow fluctuation and temporal variability were stronger. These findings suggest that airflow intensity, fluctuation, and temporal structure should be considered when evaluating thermal comfort in laminar flow operating rooms.

The natural gas supply chain exhibits substantial opportunities for reducing methane emissions. However, sources from end users─particularly household natural gas stoves─remain undercharacterized. To address this gap, we measured methane emissions from 62 household stoves in China. The average emission factor reached 0.20 (95% confidence interval (CI): 0.18, 0.22) kg of methane per stove per year, with 63% of emissions originating from incomplete combustion during stove operation. The measured emission rates during high-power use were positively correlated with both stove age and historical usage frequency. Nationally, household stoves are projected to emit 66 (95% CI: 59, 74) Gg of methane annually by 2025. The opening of the burner stove inlet valve (SIV) is the primary cause of methane emissions from stoves when they are turned off. Closing the SIV during inactive periods could lower emissions by one-third, avoiding up to 0.13 (95% CI: 0.09, 0.18) Tg of methane emissions between 2026 and 2030. These results help to refine the emission profile of household stoves and highlight practical mitigation strategies for methane reduction.

This study proposes a multi-level spiral pipe U-shaped borehole heat exchanger (MLS-U-BHE) to enhance geothermal energy utilization by replacing equal-diameter straight pipes with spiral pipes in horizontal wells. MLS-U-BHE extends fluid heating length without increasing number of boreholes, reducing drilling costs compared to traditional U-BHEs (T-U-BHE) with multi-level. A coupled heat transfer numerical model between BHEs and the reservoir was developed and validated by experimental and literature data. Using the single-level spiral pipe U-BHE (SLS-U-BHE) as a base model, effects of operating parameters, horizontal well length, number of levels, spiral coil radius (r), pitch (h) and vertical spacing on heat extraction power (HEP) were analyzed. Results show stable long-term operation and recommend spacing above 73.07 m for multiple units. Spiral pipe U-BHE outperforms T-U-BHE under various conditions. The optimal SLS-U-BHE parameters with the maximum effective heat extraction power are r = 0.2 m and h = 0.2 m, which improve outlet temperature and HEP by 6.48% and 13.58%, respectively. Variation in r affects heat extraction performance more than h. HEP value of MLS-U-BHE (with five levels) is 2.67 times that of T-U-BHE, with a 48.39% rise in outlet temperature. 70 m vertical spacing for three levels has maximum HEP. New design offers a valuable guidance for future U-BHEs development.

The coaxial borehole heat exchanger (CBHE) is a crucial component of the mid-deep geothermal energy extraction process, which has been extensively utilized for building heating. However, the effects of soil properties at varying depths on the characteristics of the CBHE have seldom been investigated. In light of this, we employed a semi-analytical model to examine the impact of the thermal conductivity and thermal capacity of soil at different depths on the heat extraction capability of the CBHE. The findings demonstrate that the increasing thermal conductivity and thermal capacity of each soil layer is beneficial for elevating the outlet temperature and heat extraction of the CBHE, with a more pronounced effect observed in deeper soil layers. Furthermore, an increase in thermal conductivity and thermal capacity in the first layer results in a deeper reverse heat transfer, while similar increases in other layers lead to a reduction in this transfer depth. Additionally, the influence of the thermal capacities of the pipe walls and grout on the performance of the CBHE was examined using the constructed model. The results indicate that neglecting the thermal capacities of the pipes and grout will lead to an underestimation of the outlet fluid temperature of the CBHE. These research findings hold significant implications for the design and construction of CBHE systems tailored to specific geological conditions.

In solar air heater systems, a strong coupling exists between flow and temperature fields, where even minor adjustments to flow boundary conditions or structural parameters can markedly affect overall heat transfer efficiency. This study introduces a novel multi-inlet cylindrical double-pass solar air heater, analyzed using computational fluid dynamics to explore its internal flow and heat transfer behavior. Results demonstrate that the multi-inlet configuration significantly improves flow field uniformity, while the central hole structure enhances inter-pass heat exchange. A systematic investigation was conducted on the effects of inlet aspect ratio, central hole area, and central hole shape under various flow conditions. Response surface methodology was applied to capture parameter interactions and identify optimal conditions. The best performance was achieved at a Reynolds number of 13,698, an inlet aspect ratio of 9.145, and an equilateral triangular central hole with a side length of 136.6 mm. Under these conditions, the solar air heater attained thermal and thermo-hydraulic efficiencies of 92.1% and 85.2%, respectively, surpassing reported designs. The findings provide valuable guidance for developing high-efficiency solar air heaters and hold ecological significance in promoting solar energy utilization, reducing dependence on fossil fuels, and advancing environmental sustainability.

Wastewater heat recovery has emerged as a vital strategy for building energy conservation, due to its significant potential and the inherent thermal stability of sewage as a heat source. Enhancing synergy between such waste heat and other clean energy sources is a key research focus. This study developed a solar-assisted sewage-source coupled heating system for a Chinese university dormitory and established a multiobjective optimization framework integrating economic, environmental, and energy efficiency indicators via a combined weighting approach of the Analytic Hierarchy Process and Entropy Weight Method. Optimization was conducted using the Hooke–Jeeves algorithm, Particle Swarm Optimization algorithm, and the Hooke–Jeeves–Particle Swarm Optimization hybrid algorithm (shorten as HJ–PSO), with subsequent comparative performance analysis. The HJ–PSO hybrid performed best: 24% lower operating costs, a 4.8-year shorter dynamic payback period, 26.35% fewer carbon dioxide emissions, 38.65% lower overall energy consumption, and an 11.18% higher system coefficient of performance. Supported by relevant policies, the system is low-carbon and economically viable, enabling grid peak shaving. This research provides theoretical and engineering references for renewable energy heating systems.

With the advancement of intelligent medical building systems, accurately predicting and dynamically regulating individual thermal comfort in hospitals has emerged as a key strategy to enhance patient experience and optimize energy consumption. However, developing effective thermal comfort models remains challenging due to complex hospital indoor environments, substantial inter-individual variability, uneven distribution of thermal sensation data, and the limitations of traditional methods in capturing personalized and dynamic responses. In this study, we collected multimodal data from the outpatient waiting area of a hospital over a three month, resulting in 11,088 valid samples. To improve model generalization and adaptability, we proposed a thermal comfort prediction framework that integrates convolutional neural networks (CNN), long short-term memory networks (LSTM), and model-agnostic meta-learning (MAML). Experimental results show that the proposed CNN-LSTM MAML model achieves high short-term prediction accuracy, with a MAE of 0.30-0.50 and a RMSE of 0.60-0.80 for 30-minute forecasts. Compared to baseline models (SVM, ANN, RF), CNN-LSTM MAML consistently achieves higher accuracy (90% vs. 65-83%), F1 score (0.89), and AUC-PR (0.91), and requires only one-sixth the training time of conventional deep models to reach convergence. SHAP based interpretability analysis identifies air temperature, CO2 concentration, and back of hand skin temperature as critical features, facilitating lightweight sensor deployment and improving model transparency. Furthermore, a comparative analysis with the traditional PMV index demonstrates the superior consistency and adaptability of our model in dynamic hospital environments. The proposed model demonstrates strong predictive accuracy, rapid deployment capability, and high robustness under small-sample conditions and complex dynamic environments, offering an accurate, efficient, and scalable solution for personalized thermal comfort prediction and intelligent HVAC control in healthcare settings.

In solar air heater systems, a strong coupling exists between the flow field and the temperature field. Minor adjustments to either the flow boundary conditions or the structural parameters of the airflow channel can significantly alter the flow field distribution, consequently impacting the temperature field characteristics and overall heat transfer efficiency. This study aims to design an innovative structure of solar air heater by incorporating baffle plates beneath the perforated absorber plate, including cylindrical baffles with lateral openings and a novel Gong-shaped baffle. Through systematic investigation, the effects of key parameters, such as baffle height, perforation opening ratio, and flat-to-concave ratio, on the solar air heater's thermal performance under varying flow conditions were evaluated. Based on the results of single-variable analysis, the response surface method was used to obtain the optimal parameters considering the interaction effects between factors. The optimal configuration parameters of the Gong-shaped baffle are: height 1.44 mm, opening ratio 0.48, flat-toconcave ratio 1.25, corresponds to the thermal performance factor of 3.96 at a Reynolds number of 10,000. In comparison, the baffle-perforated solar air heater developed in this study demonstrates superior performance, with maximum thermal and effective efficiencies of 88.7% and 85.5%, respectively. These results provide valuable technical insights for developing next-generation high-efficiency solar air heaters.

Introducing vortex generators into heat transfer channels is an effective passive technique for enhancing convective heat transfer. In this study, a novel combined-wing vortex generator is alternately arranged on the upper and lower walls of a heat exchanger channel. Numerical simulations are performed to investigate the effects of the combined-wing configuration, rear wing attack angle (gamma), tip distance from the convergence center point (g), integral rotation angle (beta) and longitudinal spacing (S1) on the flow and heat transfer characteristics over Re = 200-2000. Based on the results of the univariate analysis, the response surface method is adopted to evaluate the interactions among key parameters and optimize the comprehensive performance factor JF. The results show that integral rotation angle (beta) is the most influential parameter affecting JF, which indicate that the overall orientation of the vortex generator plays a dominant role in balancing heat transfer enhancement and flow resistance. The rear wing attack angle (gamma) strongly affects the development of longitudinal vortices and secondary flow. An appropriate gamma promotes near wall fluid mixing, disturbs the thermal boundary layer, and expands the high heat transfer region. Within the investigated design space, the optimized configuration increases the Nusselt number by 7.96-227.62% compared with the smooth channel, while the friction factor increases by 40.96-326.42%. Nevertheless, the comprehensive performance factor is improved, with an average JF superiority of 28.84% compared with published reference structures. These results demonstrate that the proposed combined-wing vortex generator improves overall thermo-hydraulic performance by strengthening longitudinal vortices and optimizing the balance between heat transfer enhancement and pressure drop penalty.

Subway operations generate substantial heat, and inadequate dissipation can progressively degrade tunnel thermal conditions. The thermal distribution within the surrounding rock is critical for calculating the load on subway environmental control systems. However, the heat transfer patterns in the surrounding rock for intersecting tunnels remain poorly understood. Therefore, this study employs COMSOL software to numerically analyze the impact of intersecting line layouts on the temperature field distribution within the surrounding rock. Results indicate that when tunnels intersect, heat accumulates in the surrounding rock near the intersection. Compared to the single-tunnel structure, intersecting tunnels exhibit higher peak temperature when reaching dynamic thermal equilibrium, and the time required to achieve equilibrium is longer. Reducing the vertical spacing between intersecting tunnels concentrates heat within the intersection zone, leading to elevated temperature in that area. However, when the vertical spacing exceeds 12 m, the numerical value no longer exhibits significant variation with vertical spacing. The intersection angle also influences the temperature distribution characteristic and numerical value. The smaller intersection angle causes heat to concentrate within the crossing zone, leading to an overall increase in surrounding rock temperature within that area. Additionally, the rate of temperature increase in the rock mass at the intersection zone and the magnitude of temperature at dynamic equilibrium are significantly influenced by geographical factors. The lower the ambient temperature in the climate zone where the intersecting subway tunnels are located, the faster the temperature rise rate at the intersection zone. When heat transfer in the rock mass reaches dynamic equilibrium, the temperature difference at the same monitoring point can reach approximately 10 circle C between severely cold and temperate regions.

To enhance the computational efficiency of capacity configuration optimization for multi-energy complementary systems, this paper proposes a hybrid optimization algorithm that integrates the Hooke-Jeeves (HJ) algorithm and the Particle Swarm Optimization (PSO) algorithm. A typical single-family rural residential building in Lanzhou was selected as the research object, and a solar-assisted ground-source heat pump heating system (SGSHPS) was designed using TRNSYS. The weights of various influencing factors in the multi-objective optimization function were determined by combining the Analytic Hierarchy Process (AHP) with sensitivity analysis. The optimization effects of the hybrid algorithm were quantitatively compared with those of the individual algorithms, and the optimization performance of the system capacity configuration was further verified through a case study in Shijiazhuang. The results indicate that the hybrid optimization algorithm significantly improves computational efficiency while ensuring sufficient accuracy, reducing the optimization duration by 23.5% and 87% compared to the PSO algorithm alone and the HJ algorithm alone, respectively. In terms of system performance, the domestic hot water supply reliability increased by 20.0%, and the system coefficient of performance (COPsys) improved by 20.8%. Regarding economic aspects, the annualized dynamic cost was reduced by 10.3%, the annual total cost savings rate increased by 36.7%, and the payback period was shortened by 4.6 years. In terms of environmental benefits, the CO2 emission reduction increased by 20.6%. This study provides theoretical references for the optimal design of multi-energy systems in rural areas.

This study aims to develop a plate-fin heat exchanger equipped with vortex generators, which features high heat transfer capacity and low pressure drop. The curved vortex generators are installed on the upper and lower walls of the heat exchanger as staggered mode. Numerical simulations were conducted to compare the effects of vortex generator shape and various structural parameters, including the dimensions of a planar right-angled triangular vortex generator, longitudinal spacing between one vortex generator wing pair upstream tip, transverse spacing between the vortex generator upstream tip and the attack angle of the curved vortex generators on the flow and heat transfer characteristics of the plate-fin heat exchanger with rectangular cross-section. The results indicate that the curved vortex generator plate-fin heat exchanger designed in this study significantly enhances heat transfer capacity while the flow resistance is not large. Based on the univariate analysis findings, the response surface method was employed to analyze the interactive effects of vortex generators arrangement parameters on flow and heat transfer characteristics. This approach identified the optimal arrangement parameters corresponding to the maximum comprehensive evaluation factor of the heat exchanger: attack angle alpha = 40.2 degrees, longitudinal spacing between one vortex generator wing pair upstream tip C = 3 mm and transverse spacing between the vortex generator upstream tip A = 3 mm. The variation in the comprehensive performance of vortex generators plate-fin heat exchanger with the optimal layout under different Reynolds numbers is analyzed. Compared with the published results, the average value of the JF factor obtained by the optimized structure in this paper is increased by 25.3%. Consequently, the heat exchanger structure proposed in this study effectively addresses the challenge of increased pressure drop while enhancing heat exchange efficiency.

This study investigates the impact of fin parameters on natural convection heat transfer in the closed cavity with a heat source. The analysis focuses on the comparison of the thermal performance between solid and porous fins. Firstly, the influence of individual parameter changes is analyzed. Based on these findings, the response surface optimization method is applied to explore the heat transfer characteristics when multiple fin parameters vary simultaneously. The results of single parameter variation show that the installation angle of porous fins has the most significant influence on the average Nusselt number of the heat source surface. For solid fins, the fin length has the greatest impact. The interaction between the installation angle and the length of the porous fin has the most significant effect on the average Nusselt number of the heat source surface, reaching a maximum value of 11.65. Compared to the cavity without fins, the optimal configuration enhances the average Nusselt number by 12.02

To address the challenges of low energy efficiency, high costs, and significant carbon emissions in rural heating systems across cold regions, this study investigates an optimized integrated multi-energy heating solution for single-family residences in northwestern China. We propose a systematic design approach based on multiobjective optimization, balancing economic viability, environmental sustainability, and energy performance. Under the constraint condition that the assurance rate for domestic hot water supply from solar collectors is not less than 90 %, a multi-objective optimization function has been formulated. The Hooke-Jeeves (HJ) algorithm and the hybrid optimization algorithm (HJ-PSO) were subsequently employed to analyze the system's adaptability across five representative cities in cold regions comparatively. The results demonstrate significant performance improvements in the optimized system: a 30.03 % increase in the solar collector hot water supply rate, a 20.05 % enhancement in the system's coefficient of performance (COPsys), a 14.30 % reduction in annual dynamic costs, a 27.42 % improvement in annual total cost savings, a 4.8-year reduction in the dynamic payback period, and a 25.39 % decrease in CO2 emissions. Notably, the HJ-PSO algorithm outperformed the HJ algorithm in terms of the COPsys in five cities, with the values exceeding 4.4. Moreover, the HJ-PSO algorithm accurately identified the optimal temperature differences of 10 degrees C and 3 degrees C for the start/stop of heat collection and heat storage, respectively, which further enhanced the overall efficiency of the system. Compared with single algorithm, the hybrid algorithm developed in this study has improved the optimization efficiency and further validated the applicability of the system.

To improve the prediction accuracy of heat gain in deep coaxial well heat exchanger (DCBHE), a fast calculation method based on the Proper Orthogonal Decomposition (POD) is proposed. This method analyzes the thermal conductivity distribution and temperature variations across different rock and soil layers. However, this algorithm only extracts the feature information from the original data, potentially introducing errors by not retaining all the data. To address this issue, a modification scheme is proposed. After modification, the relative error decreases from 3.5 % to 0.5 %, while the calculation speed increases by 3.7 %. The temperature distribution in layered rock and soil is then analyzed. It is found that the dimensionless temperature in layered conditions is higher than in uniform conditions, particularly near the heat source, with the maximum deviation ranging from 0.08596 to 0.56375. The modified POD method is 51.8 times faster than the Finite Difference Method (FDM) and provides higher accuracy, with a relative error of about 1.81 %. The study also examines the impact of rock and soil stratification on heat transfer. It finds that increased thermal conductivity inhomogeneity reduces heat transfer capacity, whereas a higher temperature gradient improves heat transfer efficiency, with a maximum increase of 15.25 %. While the inlet fluid temperature has a minimal effect on local heat removal capacity, it significantly enhances overall heat removal efficiency. Finally, by optimizing and predicting the fluid temperature at the borehole outlet, the optimal solution is achieved when the correlation coefficient (R2 >= 0.99). The predicted range of soil thermal conductivity is 3.26 to 3.38 W/(m & sdot;K). This rapid prediction method offers a valuable reference for engineering design and optimization of heat exchangers, enhancing their application efficiency.

As a critical infrastructure of urban rail transit, the thermal environment of subway tunnels significantly impacts passenger comfort, energy efficiency, and operational safety. This study focuses on a shallow-buried subway tunnel in a cold region in northwest China, establishing a tunnel air temperature prediction model and formulating equations for soil hydrothermal transfer. The research reveals the tunnel air temperature and surrounding soil hydrothermal patterns in the tunnel during typical winter and summer days, over the course of the year, and in the long term under the influence of vertical seepage. Furthermore, it analyzes the impact of various factors on the thermal environment of the tunnel. The findings indicate that the tunnel air temperature exhibits periodic fluctuations in sync with outdoor temperatures, albeit with a noticeable lag. During summer, the tunnel air temperature is higher than the wall surface temperature, with significant daily fluctuations, while the opposite phenomenon occurs in winter. During the operation of the subway system, the average temperature inside the tunnel gradually increases over time. By the 10th year of operation, the annual average air temperature in the tunnel rises from 16.51 degrees C to 17.79 degrees C, eventually reaching a stable state. Seepage has a significant impact on the thermal environment of the tunnel, followed by train frequency, while the effects of soil thermal conductivity and volumetric heat capacity are relatively minor.