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In air conditioning systems, air curtains play a crucial role in reducing the exchange of hot and cold air between the interior and exterior environments. Nevertheless, the majority of current air curtains suffer from limited airtightness and real-time performance due to their complex jet trajectory, relying on traditional control methods. Thus, this paper introduces an angle control algorithm for air curtains based on a GA-optimized quadratic BP neural network. Initially, the BP neural network is trained using the Hayes dataset to develop the prediction model for temperature-jet angle. Subsequently, the optimization model for jet angles-windshield angle is constructed, and the optimal angles set meeting the fitness function is identified using GA global search. Later, the prediction model and the optimal angles set are once again trained using the BP neural network to generate prediction model for temperature-jet angles and windshield angle. Following CFD simulation, the airtightness indicator demonstrated a 26.5% improvement with the proposed control method compared to traditional ones, highlighting the superior airtightness. In comparison to other algorithms, the proposed algorithm demonstrates a remarkable 89% enhancement in real-time performance and stronger robustness. This study presents a novel approach for the intelligent control of air curtains, holding significant importance in advancing the intelligent development of air curtain technology and facilitating energy efficiency and emission reduction.

In this paper, the microstructure of an alloy was regulated by means of strengthening solution aging, and microstructure observation and composition analysis were carried out by means of an optical microscope and X-ray diffractometer. Combined with the Vickers hardness tester, electronic universal testing machine and high-temperature persistent creep testing machine, the mechanical properties and high-temperature properties of the alloy were tested, and the strengthening mechanism of the alloy was explored. The results showed that the dendritic morphology and structure of the alloy decreased with an increase in temperature during the solution process, and the γ′ phase morphology also changed with the solution temperature: oval → cross → cubic. The γ′ phase after solid solution at 1295 °C was closest to the cubic form. Therefore, it is believed that the 1295 °C solution treatment had the best effect. In the aging process, the uniform cubic degree of γ′ phase distribution was the highest at 1090 °C. On the basis of fixed aging temperature (1090 °C), it was found that the volume fraction of the γ′ phase increased significantly after 8 h. The γ′ phase, which was closest to the cubic form, had the largest proportion of precipitation, and the volume fraction increased to 70.3%. The minimum carbide volume was 1.0%. The hardness of the alloy reached 435.8 HV; the yield strength increased to 280.1 MPa; and the durability of the alloy under the conditions of 1000 °C/230 MPa and 870 °C/655 MPa was 99.7 h and 42.7 h, respectively, which achieved the purpose of alloy design.

In order to improve the mechanical properties and phase transition temperature, the influence of Gd doping on the microstructure, phase transition temperature and mechanical properties of Co35Ni32Al33 alloy was investigated. The results show that the γ+β phase was observed in the microstructure of the sample with less Gd doping and the γ phase+martensite was found with more Gd content. The phase transition temperature apparently increases with Gd doping and the phase transition temperature goes over room temperature when the Gd is 3 at.% or more. With increasing Gd doping, more γ phase appears in the sample which results in decrease in hardness. The compressive strength decreases from 2274 to 1630 MPa and the ductility increase from 4.2 to 12.9% with increasing Gd content.

Housler based magnetic controlled shape memory alloys are characterized by a large magnetic field induced strain. The strain was dependent on the twin martensite structure rearrangement, and the rapid solidification technology had a significant influence on the microstructure, physical, and chemical properties of the alloy. Thus, the structure and the martensitic transformation changes of Co33Ni31Al27Fe9 during the rapidly solidified process were studied. The microstructure of Co33Ni31Al27Fe9 with furnace cooled and rapid solidification (RS) constitutes a dual-phase structure, β phase and γ phase in a low cooling rate and martensite and γ phase in a high cooling rate. The γ phase at the grain boundaries reduced and became more fragile by raising the RC value. The one-step austenite-martensite phase transformation occurred during the process of heating and cooling. The phase transition temperature presents an increasing trend by rising the cooling rate, even to over the room temperature. Moreover, the martensite structure in Co33Ni31Al27Fe9 constitutes a typical L10-type twinning structure.