Environmental wind tunnels for high-speed trains play a significant role in their development. The cooling system of the wind tunnel poses a challenge as it requires lower temperatures and a higher cooling capacity during operation. The conventional approach to wind tunnel refrigeration uses evaporative cooling, which is less efficient at low temperatures and comes with environmental and safety risks. In this study, we propose an innovative air compression refrigeration method based on the Brayton cycle. This method converts high-pressure air into low-temperature air at atmospheric pressure for wind tunnel refrigeration. The new cooling system has reduced energy usage by 3.72 MW, leading to a 13.15% improvement. The return cooler of the system is modeled using the effective number of heat transfer units and the mean temperature difference design method. Additionally, the turbine within the system is analyzed using one-dimensional flow characteristic analysis and the principle of similarity. This method has been validated by comparing it to other published papers. Subsequently, we perform a thorough sensitivity analysis on the key design parameters of the system. We observe that with a sufficient heat transfer area of the recooler, the cooling efficiency of the system exhibits a gradual decline from 64% to 60% as the mass flow rate of the system rises. For a fixed turbine, the cooling efficiency of the system rises from 20% to 62% and subsequently declines to 37%, with an increase in the mass flow rate. As a result, we conclude that the design parameters of the turbine have a more significant influence on the cooling efficiency of the system than the recooler. Our study will establish a foundation for selecting parameters to optimize the refrigeration system in the future.

Researches have focused on the thermal protection system (TPS) of hypersonic vehicles under severe aerodynamic heat. According to the second law of thermodynamics, heat transfer needs to consume a heat sink, but the cold energy provided by the airborne heat sink is limited. Therefore, it is necessary to explore new available heat sinks during hypersonic cruise. This paper numerically calculated the wall temperature distribution of hypersonic vehicle X-51A with different Mach numbers, altitudes and angles of attack using ANSYS Fluent 19.0. A dimensionless parameter, relative temperature coefficient r_t, was proposed to characterize the relative value of local wall temperature in the whole wall temperature range. The distribution regularity and influencing factors of wall temperature were summarized. The low-temperature region which is less affected by flight conditions was divided as the heat sink and its heat dissipation capacity (Q) and characteristics were studied. The angle of attack has great influence on the temperature distribution. In XY view the rear side of leeward surface is least affected by flight conditions and its r_t is less than 0.2, which can be used as a low-temperature region. Taking this region as a heat sink to dissipate heat, it is found that the Q of the new heat sink is 30 kW/m² at Ma 3, 90 kW/m² at Ma 4 and 200 kW/m² at Ma 5. The Q increases greatly with the increase in Mach number, and the convective heat transfer coefficient (h) also increases. At the same Q, the h decreases with the increase in Mach number. The exploration of low-temperature region as heat sink has an important reference for reducing the dependence on consumable heat sink and alleviating the energy shortage of the hypersonic vehicle.

Pneumatic cabin pressure control system (PCPCS), with its exceptional electromagnetic compatibility, is expected to become the major equipment on a high-performance airplane again in the future. Although the PCPCS has been mature for a long time, the broad popularization of the digital cabin pressure control system (DCPCS) has left the PCPCS in the cold for decades. This makes the PCPCS unable to meet the severe cabin pressure regulation requirements of high-speed aircraft today. For this purpose, a more precise PCPCS modeling method is proposed. Through this method, the relation between different parts in the PCPCS can be accurately characterized. Moreover, the impact of the ambient environment on the PCPCS is taken into consideration. This method can be used to accurately analyze the PCPCS under maneuvering flight. And it also assists in the verification of the system improvements of dynamic performance in the future. Simulation results show that the aircraft acceleration disturbs the PCPCS slightly, and the cabin air inflow fluctuation has a significant impact on the cabin air pressure.

Environmental wind tunnels play a crucial role in the research and development of high-speed railways. However, constructing and operating these wind tunnels requires significant resources, especially with respect to the cooling system, which serves as a vital subsystem. The cooling system utilizes an air compression refrigeration cycle and consists of multiple components. The efficient operation of these components, along with the adoption of appropriate strategies, greatly enhances the efficiency of the wind tunnel refrigeration system. Despite this, the existing methods for evaluating the refrigeration system do not fully capture the energy consumption of an air compression refrigeration system during practical use. To address this issue and effectively evaluate the wind tunnel refrigeration system, we propose using an exergoeconomic evaluation coefficient with experimental cycles to establish the system. This method incorporates the use of frequency coefficients and related parameters. By employing the newly developed evaluation coefficient as an objective function, we utilize the adaptive value-sharing congestion genetic algorithm to optimize the wind tunnel for high-speed trains. Furthermore, we compare the advantages and disadvantages of different optimization schemes. Traditional optimization methods prove inefficient because of the system’s numerous variables and the presence of multiple peaks in the objective function. Inspired by the biogenetic breeding method, we introduce an optimization approach based on a specific gene mutation. This innovative method significantly reduces optimization time and improves efficiency by approximately 17%.