To meet the core demand for molten salt thermal storage heated by main steam extraction in the flexibility retrofitting of coal-fired power plants, this study numerically investigates a steam-molten salt airfoil-fin printed circuit heat exchanger (PCHE) and reveals the coupled flow and heat transfer mechanisms of steam (hot side) and molten salt (cold side) within the airfoil-fin channels. The effects of variable thermophysical properties of working fluids, fin structure, and operating conditions on heat transfer are clarified, and the underlying mechanisms governing thermal performance variations are further elucidated at the microscopic level using field synergy theory. The results indicate that hot-side heat transfer is primarily governed by the drastic variations in thermophysical properties near the saturation temperature, whereas cold-side heat transfer is dominated by high viscosity effects. The fin structure induces periodic fluctuations in thermal parameters: the contraction section (fin leading edge-maximum fin width) exhibits enhanced thermal performance due to flow acceleration and boundary layer thinning, while the expansion section (fin trailing edge) shows the opposite trend. The differences in thermal-hydraulic parameters at various fin locations are mainly concentrated in the viscous sublayer. Elevating the cold-side inlet mass flow rate enables both sides to achieve their optimal comprehensive thermalhydraulic performance, with the performance evaluation criterion (PEC) increasing by 8.02% and 11.22%, respectively. In addition, elevating the hot-side operating pressure yields the optimal overall thermal performance of the PCHE, with the overall heat transfer coefficient (UA) increasing by 11.23%. The variations in thermal performance under varying operating conditions are essentially governed by the combined effects of thermophysical property variations on both sides, changes in thermal resistance, and the coupling between heat absorption and release. Field synergy analysis further confirms that the thermal performance variations on both sides are fundamentally determined by the degree of synergism between the velocity and temperature gradient fields. Furthermore, thermal-hydraulic correlations for both fluids are developed, with prediction deviations within +/- 25%. The results of this study provide a theoretical basis for the design and performance optimization of steam-molten salt PCHEs.

The air-cooled battery thermal management system (BTMS) is critical for regulating the temperature of lithium batteries in electric vehicles, thereby ensuring their efficient operation. Optimizing the structural design of the air-cooled BTMS can significantly enhance the cooling performance of the heat dissipation system. This paper investigates a U-type air-cooled BTMS and proposes a method that integrates fluid dynamics with a response surface model to optimize its performance. Initially, a heat-flow coupling model of the BTMS is developed to examine how structural parameters-such as air inlet height (A), air inlet angle (B), secondary vent position (C), longitudinal cell spacing (D), transverse cell spacing (E), and fillet radius (F)-affect the cooling performance metrics of the system. Through orthogonal test polarity analysis, three critical structural parameters are identified as having substantial influence on cooling performance and are selected as design variables. The maximum temperature, maximum temperature difference, and average temperature of the battery pack are used as performance metrics to guide the optimization. The response surface method is employed to model the functional relationships between design variables and performance metrics, and two multi-objective optimization algorithms are applied to drive the optimization process. The CRITIC weight method is utilized for the first time to select the optimal solution, addressing the limitations of subjective decision-making in previous studies. The results demonstrate that the optimized structural parameters markedly enhance the cooling performance of the U-type air-cooled BTMS, reducing the maximum temperature, maximum temperature difference, and average temperature of the battery pack by 11.29 %, 60.75 %, and 5.51 %, respectively, while significantly improving temperature uniformity.

Compact heat exchangers play a significant role in the heat transfer process of aircraft cabin air cycle systems (ACSs), and their heat transfer performance significantly influences system refrigeration efficiency. During flight, the inlet conditions of heat exchangers exhibit significant transient characteristics, such as changes in air temperature and mass flow rate. Accurately characterizing the thermal response of heat exchangers is therefore essential for predicting outlet temperatures, as well as for optimizing ACS control strategies. This study proposes a scaling-lumped transient method (SLTM) for plate-fin heat exchangers by improving the scaling law model and time constant lumped model, enabling direct prediction of the transient outlet thermal response of heat exchangers under step or ramp transient input and variable heat exchanger structures. A transient performance testbed for heat exchangers was developed. Three types of transient input condition tests, including inlet flow rate step changes, inlet temperature ramp changes, and simultaneous changes, were conducted for three plate-fin heat exchangers with straight, corrugated, and serrated fins. The results showed that the average error between the experimental data and SLTM did not exceed 1 %, with a maximum error of 3.4 %. The scaling regression of all transient data further revealed the heat-transfer mechanism of the transient thermal response. This study provides an efficient and accurate transient performance prediction method, advancing the design and application of plate-fin heat exchangers.

The thermal management system of power batteries plays a crucial role in regulating the temperature of the battery pack and ensuring efficient operation. By optimizing the design of the thermal management system structure, cooling performance can be significantly enhanced. In this study, a novel structure called novel serpentine cooling plate (NSCP) is designed to improve the cooling performance of the liquid-cooled plate. This study utilizes numerical simulation to investigate the impact of coolant mass flow rate, coolant inlet temperature, coolant flow direction, and the number of flow channels on the performance of the liquid cooling plate under a 2C discharge rate, using a 50 % volume concentration of ethylene glycol solution as the coolant. The results indicate that the cooling performance of the NSCP surpasses that of the traditional SCP. Furthermore, to enhance the cooling performance of the NSCP, we optimize the channel width (A), channel depth (B), and wall thickness (C) utilizing both discrete and continuous variables. Initially, structural parameters A, B, and C are considered as discrete random variables, and significant factors along with optimal combinations are identified through orthogonal test polar analysis and analysis of variance. Subsequently, these parameters are treated as continuous random variables, and sampling is conducted using the optimal Latin hypercube sampling method. The response surface method is employed to establish the functional relationship between design variables and performance indices, while NSGA-II is utilized for optimization, leading to the derivation of Pareto-optimal solutions using the CRITIC weighting method. A comparison of the two optimization methods reveals that the continuous variable optimization is more effective; thus, this method is selected for implementation. The results demonstrate that the BTMS optimized with continuous variables can reduce the maximum temperature, maximum temperature difference, and average temperature of the battery pack by 2.1 degrees C, 1.2 degrees C, and 2.8 degrees C, respectively, compared to the initial structure. Finally, validation under different discharge rates and environmental temperatures demonstrates the robustness of the optimized structure under various operating conditions. These research findings provide effective theoretical basis and practical references for the design and optimization of liquid-cooled lithium-ion battery cooling structures.

The change in the structure of the air-cooling battery thermal management system (BTMS) is demonstrated to improve its cooling performance. In previous research carried out by the authors investigating a 4 x 9 21,700 battery module, several exit areas close to the entrance area were designed and examined. The direction of the entrance area is perpendicular to the cooling channel, while the direction of the exit area is parallel to the cooling channel. A simulation analysis of the BTMS is carried out to optimize the cooling performance. It is found that with the gradual increase in the wind speed, the outlet position is gradually shifted towards the inlet area wall. This can maintain the average temperature, maximum temperature, and maximum temperature difference of the battery module at the lowest levels. The polynomial fitting method is used to establish the mathematical relationship between the distance from the center surface to the leftmost wall of the outlet area of the BTMS, the wind speed, and the main cooling index when the discharge rate is 2C. On this basis, the best fitting function is obtained, and the model is established for verification.The two BTMS models were validated at wind speeds of 8 m/s, and the average temperature of both BTMS was very close to the predicted value, with maximum deviations of 0.57 % and 1.01 %, respectively. This fitting method could help to design a better air-cooling BTMS.

As fighter aircraft become more advanced, traditional air cycle systems have fallen short of meeting the complex environmental control requirements. Advanced fighters such as the F-22 Raptor have responded to these challenges by adopting integrated thermal management systems. These systems feature complex thermodynamic processes and intricate information transmission pathways among various components, creating a sophisticated network structure. To unravel the complexity of such systems, this paper employs a blend of thermodynamics and information theory. We conduct multi-level analysis using structure entropy method and centrality algorithms to explore the information transmission characteristics within these thermodynamic systems. At the system level, we find that variation in environmental parameters have only a 1 % impact on order degree, whereas the influence from the system's own structure is more pronounced. At the component level, within the whole system, the varies components in AFT PAO and fuel loops emerge as critical hubs for information transmission. Among these components, the PAO/Fuel stands out as the most important, with closeness and betweenness centrality exceeding that of all other components by at least 11.5 % and 29.1 %. This study offers a theoretical foundation for the optimization of thermodynamic system structure and layout, viewed through the lens of information theory.

The converter valve of ultra-high-voltage direct current grid requires a large amount of cooling water for heat dissipation. Considering the generated waste heat, this study proposes a heat pump-driven mechanical vapor compression (HP-MVC) desalination system based on traditional power-driven mechanical vapor compression (MVC). Using the scaling-endoreversible thermodynamic model, the analytical solutions of the structural equation and operating boundary of the proposed HP-MVC system were derived, which is the innovation of this study. The effects of different component parameters on the thermodynamic characteristics and operation boundaries of the HP-MVC were determined. The results revealed that the HP-MVC system alternately exhibited heat-drive dominant and power-drive dominant modes, in which the specific power consumption was lower in the former. When the recovery ratio was 0.3, with an increase in the pressure ratio from 1.15 to 1.50, the heat supplemented by the heat pump decreased by 31.9 %, and the specific power consumption increased by 63.1 %. The analytical solutions of the structural equation provide a theoretical basis for the efficient operation of the system, and the operation boundaries demonstrate the difference between HP-MVC and traditional MVC. The HP-MVC reduces heat dissipation requirements and results in a more energy-efficient desalination system, which is a typical mutually beneficial design and worth promoting.

Humidification and dehumidification are among the most important desalination technologies, in which humidifiers and dehumidifiers are the key components. Previous research has mainly focused on overall system improvement, but few studies have focused on the thermodynamic limitations of the humidification and dehumidification processes. By introducing temperature and enthalpy effectiveness, the thermodynamic limits have been explored. It was successfully established that there are three operating states for the humidifier and dehumidifier. The analytical expressions of enthalpy and temperature effectiveness boundary values in each state were obtained. The results of visualizing the influence of mass flow ratio, inlet temperature, inlet and outlet relative humidity, and pressure on the feasible range of enthalpy and temperature effectiveness were presented. This study explores the thermodynamic limits of heat and mass transfer equipment that can be applied to other types of humidification and dehumidification equipment.

A Reverse-Brayton cycle represented by the B787 electrical driven environmental control system is used as the analysis object, including the thermodynamic process of two-stage compression, intercooling, and regeneration. An analytical expression for the thermodynamic performance of the cycle is derived based on the endoreversible thermodynamic analysis model (ETM). Combined with a genetic algorithm, an ETM-based optimization approach (ETM-OA) is proposed. Using this method, it is found that the coefficient of performance is increased by 34.1 % and 48.4 % under two typical flight conditions, respectively, and the corresponding system entropy generation number is reduced by 30.2 % and 51.1 %, respectively. Both ETM-OA and entropy generation analysis show that the electric supercharging module, secondary heat exchanger, and air cycle machine are key components of the system. This study provides a convenient method for obtaining the thermal power conversion mechanism of complex thermal cycles and conducting optimization analysis.

Air cycle systems (ACSs) are primarily used in aircraft environmental control systems (ECSs) to provide a suitable cabin temperature and pressure environment for passengers and avionics. It comprises heat exchangers, compressors, turbines, water separators, and various other components that are interconnected to form an information-transmission network. Traditional research on ACSs has focused primarily on their thermal performance. This study abstracted ACSs into network graphs based on their information-transmission characteristics, determined the weight of each information-transmission route using the fuel weight penalty method, calculated and compared the order degree of different ACSs using the structure entropy method, and measured the importance of each component using centrality for the first time. The results showed that the order degree of the ACSs gradually increased with an increase in the number of wheels in the air cycle machine (ACM), and ACSs with high-pressure water separation had a higher order degree under wet conditions than under dry conditions. Moreover, based on the centrality of each vertex in the graphs, the ACM and secondary heat exchanger in the ACS were fundamentally important and should be focused on during the system design. The methodology proposed in this study provides a theoretical basis for the evaluation of the ACS organizational structure and the design performance of components.

Accurate collection and analysis of ground reaction force (GRF) data are crucial for optimizing the technical movements of speed skaters; however, it has been a challenge for the limitations of experimental equipment and application scenarios. Therefore, we proposed a novel approach for estimating GRF based on kinematics obtained from markerless video tracking systems and achieved low errors compared with the experimental data. Our method allows for further biomechanical analysis, including muscle force and power, during speed skating competitions.

The high power of blade servers inside small data centers (DCs) can cause heat accumulation, which can degrade the performance of DCs. To address the problem of heat dissipation, we performed periodic experiments on a thermal management system based on a phase change material. The effects of time ratio, heating power, and cooling water temperature on the performance of thermal control and periodic stability were investigated. Information entropy reflects uncertainty by transforming a variable changes over time into a single parameter representing inhomogeneity of time. Herein, it was introduced as an evaluation index of thermal control performance. The results verified that the peak temperature of the heating surface can be maintained below 80 degrees C for several periods under specific conditions. Additionally, the information entropy results of the experimental data reflected the thermal control performance of the system and validated the experimental conditions. Based on the experimental results and the corresponding information entropy analysis, we proposed a design strategy for the system parameters and a method for reducing the number of measuring points. The obtained results formed the basis for the thermal management design of the server level of DCs, other electronic equipment, and electric vehicles.

The heat generation rate (HGR) of lithium-ion batteries is crucial for the design of a battery thermal management system. Machine learning algorithms can effectively solve nonlinear problems and have been implemented in the state estimation and life prediction of batteries; however, limited research has been conducted on determining the battery HGR through machine learning. In this study, we employ three common machine learning algorithms, i.e., artificial neural network (ANN), support vector machine (SVM), and Gaussian process regression (GPR), to predict the battery HGR based on our experimental data, along with cases of interpolation and extrapolation. The results indicated the following: (1) the prediction accuracies for the interpolation cases were better than those of extrapolation, and the R2 values of interpolation were greater than 0.96; (2) after the discharge voltage was added as an input parameter, the prediction of the ANN was barely affected, whereas the performance of the SVM and GPR were improved; and (3) the ANN exhibited the best performance among the three algorithms. Accurate results can be obtained by using a single hidden layer and no more than 15 neurons without the additional input, where the R2 values were in the range of 0.89–1.00. Therefore, the ANN is preferable for predicting the HGR of lithium-ion batteries.

This paper presents a forced convection calorimetry method, based on the lumped capacitance model, to measure the continuous noise-free heat generation rate of batteries. The method was verified via reference sample calibration. Battery test results indicated that the discharge current, ambient temperature, and cycle aging significantly affect the heat generation characteristics of batteries. A larger discharge current and lower ambient temperature of 20-45 degrees C caused a greater heat generation rate and faster temperature increase. The average heat generation rate over the discharge period exhibited a quadratic polynomial correlation with the discharge current and a negative quadratic polynomial correlation with the ambient temperature. The cycling process increased the heat generation rate, reflecting battery aging. The cycle charge rate had a significant impact on the battery life. Moreover, the two cells started to display different heat generation characteristics after being cycled by different currents even at a similar state of health, revealing that the cycling process and different cycle rates may aggravate the battery inconsistency.

Plateaus, one of the most important terrain types in China, contain high-quality agricultural and livestock re-sources. However, due to their natural conditions, they host major deficiencies in cold chain logistics. Existing studies have focused on improving the temperature regulation capabilities of cold chain vehicle refrigeration or air conditioning systems, but have neglected the unique low-pressure environment faced by the Plateau cold chain transport vehicles. Using zoning design, air and vapor cycle refrigeration technologies, this study proposed a bootstrap-type integrated environmental control system (BIECS) and simple-type integrated environmental control system (SIECS) to realize vehicle "micro-environmental control." The analytical solution of the thermal characteristics of the system was obtained based on the scaling-endoreversible thermodynamic analysis model. Moreover, the influence of ambient humidity on the thermal performance of the system was evaluated based on the enthalpy method. According to the typical working conditions, the system performances using different refrigerants, R404A, R448A, and R452A, were analyzed at different trailer temperatures, cooling capacities, and altitudes. Our results showed that, under the same design requirements, the coefficient of performance (COP) of the BIECS was slightly higher than that of the SIECS. Higher the trailer temperature and cooling capacity, higher is the COP of the system. Comparing the three refrigerants under the same working conditions, compared with R404A, the COP of the BIECS and SIECS increased by 13.4 % and 10.9 %, respectively, using R484A, and increased by 6.1 % and 5.0 %, respectively, using R452A. The performance of the systems that used R448A was the best. The system could ensure a 2.4-km cab pressure altitude at an ambient altitude of 5 km, but the COP could decrease by 31.8-35.6 %, compared to that on the plains. This study provides and comprehensively evaluates a new technical solution for the environmental control of Plateau cold chain transportation vehicles. It also provides comprehensive health protection measures for drivers and technical support for the promotion and development of Plateau cold chains.

Spacecraft may encounter emergency pressure relief situations during manned space exploration missions, such as when micrometeoroids break through the bulkheads. The pressure emergency is one of the main threats to the missions in low earth orbit or deep space explorations to the Moon and Mars. It is critical to develop a pressure protection scheme for emergency contingencies. In this study, in order to improve the safety and reliability of spacecraft protection, a periodic recompression recovery scheme (PRRS) is proposed for cabin pressure protection. The PRRS adopts a combined mode of cabin emergency recompression, cabin pressure maintenance, gas recovery, and spacesuit protection, which can provide astronauts with a variety of safety protection methods. A mathematical model of cabin pressure control is established by using the lumped parameter method, and the gas consumption of three types of pressure protection systems are compared. The PRRS adopts the mature technologies and could provide the reliable pressure emergency protection. Compared with the traditional continuous gas supply scheme, the PRRS can reduce gas consumption by more than 85%. In the case of limited spacecraft gas resources, the PRRS promises a longer survival time for returning astronauts. This study can provide a design idea for the overall design of manned spacecraft in the future. (c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

The ram-air parafoil, which can be controlled to achieve stable and precise landing, plays an important role in the field of precision airdrop. The overall goal of the paper is to discuss the effectiveness of three methods in trajectory planning and apply them to simulations and predictions under certain random conditions, thereby improving the landing precision and avoid complicated derivations in traditional dynamics. A trajectory planning model based on a back propagation neural network (BPNN) is proposed. Considering the influence of the apparent mass and random wind field, genetic algorithm (GA) is the landing points accuracy optimization algorithm supplying a database verified by Kane equation (KE) model on which the BPNN is trained, verified, and tested. BPNN is the model to predict a large number of airdrop landing points data after training. Simultaneously, the effects of the different control methods and random wind speeds on the dynamic characteristics of the parafoil are analyzed. In KE, GA, and BPNN, the BPNN model features the highest landing point precision among the three methods. The radius that 95% landing points are lied in of BPNN can reach 6.30 m, which is only 77.0% of the GA and 54.6% of the traditional KE model. In addition, the influence of cutting-in angle and transition radius on the landing point error is analyzed. Our results indicate significant potential application of GA and BPNN in the field of precision airdrop.

A water sublimator is a thermal control device that uses the phase change latent heat of water for heat rejection in space. It can allow effective heat dissipation in a microgravity environment. Existing models of water sub-limators mainly focus on numerical simulations and do not calculate the temperature distribution and phase change interface position accurately. Furthermore, very few theoretical studies have been conducted. This study investigates a porous plate water sublimator, establishes the governing equations of each stage of a sublimator working in the periodic mode, and performs discrete calculations using the finite volume method. Additionally, a dimensionless analysis of the governing equations is conducted, and the flow in the evaporation process occurring in the porous plate is solved analytically. The results show that the sublimator enters a stable state after several periods. The effects of the thickness and pore diameter of the porous plate, feedwater pressure, and the type of working fluid on the evaporation process are discussed. It was observed that a large pore diameter and high feedwater pressure resulted in a rapid rise in the liquid level in the porous plate. An adaptive mesh method is used to induce a change in the length and number of meshes in accordance with the interface movement, thereby solving the problem caused by changes in the calculation domain. Moreover, an analytical solution of the evaporation process in the porous plate is provided, and it has universal significance for describing similar phenomena.

针对水升华器在实际航天工程应用中的工作特性,以升华模式下的水升华器为研究对象,应用一维稳态导热、自由分子流动等理论模型,对水升华器内部热质平衡进行分析,得到了升华模式下的冰层厚度、升华温度等理论计算结果,并推导得到升华模式最大热载荷的无量纲特性曲线.利用商用软件ANSYS Fluent进行数值仿真,基于焓-多孔模型描述了水在水升华器给水腔内的结冰过程,求解了不同孔度、孔径等设计参数下水升华器的工作特性,将仿真结果与理论计算对比,发现两者具有较好的一致性.建立的无量纲特性曲线和数值算法对预测不同设计工况下水升华器升华模式的工作特性具有指导意义.