# Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
## 1 Introduction  
The impeller hub of the diagonal flow fan is conical. It is a kind of fan whose gas enters from the axial direction, exports along the inclined direction of the impeller, and discharges from the axial direction after turning through the air duct [1, 2]. It is widely used in chemical industry, metallurgy, energy, construction, agriculture, and other fields because of its high total pressure coefficient, large flow coefficient, high efficiency, and wide working range [3]. With the increasing global energy consumption, the international community is increasingly calling for energy conservation and environmental protection, as well as the huge energy consumption and serious noise pollution of the fan system. It is urgent for the fan industry to have the ability to quickly design and manufacture high-efficiency and low-noise diagonal flow fans. However, the large demand for diagonal flow fans does not match the development of its design methods. The existing design theory of diagonal flow fan or diagonal flow impeller mainly focuses on the application fields of aeroengine and compressor with high speed, a high pressure ratio, and compressible gas. There are a few performance optimization methods for small diagonal flow fans under low speed and incompressible gas conditions [4, 5]. The diagonal flow impeller, with its unique performance advantages, has drawn the attentiond many scholars at home and abroad. For example, [PERSON] et al. [6] carried out numerical simulation and experimental research on the leakage vortex and diffusion development process at the tip clearance of the diagonal flow fan. The results show that the tip leakage vortex rupture occurs at the tail of the fan blade passage, and the leakagevortex rupture directly leads to the vortex core disappearing, an increase in the leakage vortex diffusion degree in the flow passage, and the formation of the low-pressure area. [PERSON] et al. [7] studied the three-dimensional flow stability expansion mechanism of a low-pressure axial fan, and verified the influence of curved blades on boundary layer migration through experiments. [PERSON] et al. [8] revealed the unsteady flow characteristics of the flow field in the diagonal flow pump. Studies have shown that the tip leakage flow was entrained with the mainstream in the blade channel, resulting in the tip leakage vortex. The blade inlet easily formed a separation vortex due to flow separation. Based on a BP neural network and a genetic algorithm, [PERSON] [9] et al. optimized the blade of a low-pressure axial flow fan. The results show that the forward-curved blade can redistribute the airflow along the blade span and reduce the tip load, thus improving the operating performance and total pressure ratio of the fan while expanding the stable operation range of the fan. At present, the design of diagonal flow fan products presents the characteristics of experience, multiple solutions, and comprehensiveness. The solution process is the cross-integration of machinery, computer science, mathematics, and other disciplines. The optimization design process often requires huge computational resources. This problem can be solved by establishing a surrogate model based on limited experiments instead of complex simulation calculations. The traditional single surrogate model does not always obtain the complex nonlinear relationship between variables and objectives, while the combination of multiple surrogate models, without increasing the computational cost of optimization, can integrate the advantages of various surrogate models to improve the possibility of obtaining the optimal solution [10; 11].