[1] Boyer K.M., O’Brien W.F., An improved streamline curvature approach for offdesign analysis of transonic axial compression systems. Journal of Turbomachinery, 2003, 125(3): 475–481.
[2] Konig W., Hennecke D., Fottner L., Improved blade profile loss and deviation angle models for advanced transonic compressor bladings: Part 1: A model for subsonic flow. Journal of Turbomachinery, 1996, 118(1): 73–80.
[3] Deb K., Pratap A., Agarwal S., et al., A fast and elitist multiobjective genetic algorithm: Nsga-II. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182–197.
[4] Deb K., Jain H., An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: solving problems with box constraints. IEEE Transactions on Evolutionary Computation, 2013, 18(4): 577–601.
[5] Jin Y., Wang H., Tinkle C., et al., Data-driven evolutionary optimization: An overview and case studies. IEEE Transactions on Evolutionary Computation, 2019, 23(3): 442–458.
[6] Chugh T., Sindhya K., Hakanen J., et al., Handling computationally expensive multiobjective optimization problems with evolutionary algorithms a survey. Reports of the Department of Mathematical Information Technology, 2015, No. 4, ISSN 1456-436X; ISBN: 978-951-39-6352-1.
[7] Jin Y., Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation, 2011, 1(2): 61–70.
[8] Santana-Quintero L.V., Montano A.A., Coello C.A.C., A review of techniques for handling expensive functions in evolutionary multi-objective optimization. Computational Intelligence in Expensive Optimization Problems, Adaptation Learning and Optimization, Springer, Berlin, Heidelberg. 2010, 2: 29–59. https://doi.org/10.1007/978-3-642-10701-6_2
[9] Song Z., Wang H., He C., et al., A Kriging-assisted two-archive evolutionary algorithm for expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 2021, 25(6): 1013–1027.
[10] Jones D.R., A taxonomy of global optimization methods based on response surfaces. Journal of Global Optimization, 2001, 21(4): 345–383.
[11] Ma S.-B., Afzal A., Kim K.-Y., et al., Optimization of a two-stage transonic axial fan to enhance aerodynamic stability. Turbo Expo: Power for Land, Sea, and Air, 2016, Paper No. GT2016-56261.
[12] Zhang L., Wu K., Liu Y., Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method. Journal of Thermal Science, 2017, 26(6): 533–539.
[13] Jaron R., Moreau A., Guerin S., et al., Multidisciplinary design optimization of a low-noise and efficient next-generation aero-engine fan. Journal of Turbomachinery, 2022, 144(1): 011004.
[14] Li J., Chen H., Liu Y., et al., Aerodynamic design and optimization of a high-loaded axial fan stage using a curvature control method. Journal of Mechanical Science and Technology, 2019, 33(8): 3871–3883.
[15] Zhang S., Li R., Zhang Y., et al., Aerodynamic optimization and noise reduction of a two-stage series compact fan. Journal of Aerospace Engineering, 2021, 34(5): 04021057. https://doi.org/10.1061/(ASCE)AS.1943-5525.0001304
[16] Lee K.J., Park I.W., Bang K.S., et al., Optimal design of a plenum fan with three-dimensional blades. Applied Sciences, 2020, 10(10): 3460.
[17] Chen H., Qin Y., Wang R., The optimization and flow diagnoses for a transonic fan with stage flow condition. Aerospace Science and Technology, 2018, 80: 247–260.
[18] Cuciumita C.Q.N., Shahrokh S., Adjoint based aero-structural design optimisation of a transonic fan blade. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2023, 237(6): 1141–1157.
[19] Luo J., Fu Z., Zhang Y., et al., Aerodynamic optimization of a transonic fan rotor by blade sweeping using adaptive gaussian process. Aerospace Science and Technology, 2023, 137: 108255.
[20] Mehmood K., Shahzad A., Akram F., et al., Design optimization of bladeless ceiling fan using design of experiments. Journal of Wind Engineering and Industrial Aerodynamics, 2023, 233: 105313.
[21] Hocine A.E.B.L., Poncet S., Fellouah H., Optimization of a double-intake squirrel cage fan using openfoam and metamodels. International Journal of Heat and Fluid Flow, 2023, 101: 109129.
[22] Xiong J., Tang J., Guo P., et al., Flow capacity optimization of a squirrel cage fan with a new rounded rectangle volute under size limitation. Machines, 2023, 11(2): 283.
[23] Lopez D.I., Ghisu T., Shahpar S., Global optimization of a transonic fan blade through ai-enabled active subspaces. Journal of Turbomachinery, 2022, 144(1): 011013.
[24] Ding Y., Wang J., Jiang B., et al., Multi-objective optimization for the radial bending and twisting law of axial fan blades. Processes, 2022, 10(4): 753.
[25] Xiao Q., Wang J., Jiang B., et al., Multi-objective optimization of squirrel cage fan for range hood based on kriging model. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022, 236(1): 219–232.
[26] Jin W., Mao Z., Zhou S., et al., Research on multi-optimal project of outlet guide vanes of nuclear grade axial flow fan based on sensitivity analysis. Applied Sciences, 2022, 12(6): 3029.
[27] Zhou S., Hu Y., Lu L., et al., IGV optimization for a large axial flow fan based on MRGP model and Sobol’ method. Frontiers in Energy Research, 2022, 10: 823912.
[28] Zhang H., Wang Z., Yang H., et al., Blade shape optimization and internal-flow characteristics of the backward non-volute centrifugal fan. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2022, 236(4): 673–688.
[29] Wang Z., Qu F., Wang Y., et al., Research on the lean and swept optimization of a single stage axial compressor. Engineering Applications of Computational Fluid Mechanics, 2021, 15(1): 142–163.
[30] Xiao Q., Shi X., Wu L., et al., Squirrel-cage fan system optimization and flow field prediction using parallel filling criterion and surrogate model. Processes, 2021, 9(9): 1620.
[31] Zhou S., Yang K., Zhang W., et al., Optimization of multi-blade centrifugal fan blade design for ventilation and air-conditioning system based on disturbance CST function. Applied Sciences, 2021, 11(17): 7784.
[32] Zhou S., Dong H., Zhang K., et al., Optimal design of multi-blade centrifugal fan based on partial coherence analysis. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022, 236(2): 894–907.
[33] Wang K., Ju Y., Zhang C., Aerodynamic optimization of forward-curved blade centrifugal fan characterized by inclining bionic volute tongue. Structural and Multidisciplinary Optimization, 2021, 63(5): 2493–2507.
[34] Almasi S., Ghorani M.M., Haghighi M.H.S., et al., Optimization of a vacuum cleaner fan suction and shaft power using kriging surrogate model and miga. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2022, 236(3): 519–537.
[35] Yang K., Zhou S., Hu Y., et al., Energy efficiency optimization design of a forward-swept axial flow fan for heat pump. Frontiers in Energy Research, 2021, 9: 700365.
[36] Jaron R., Moreau A., Guerin S., et al., Multidisciplinary design optimization of a low-noise and efficient next-generation aero-engine fan. Journal of Turbomachinery, 2022, 144(1): 011004.
[37] Kong C., Wang M., Jin T., et al., An optimization on the stacking line of low-pressure axial-flow fan using the surrogate-assistant optimization method. Journal of Mechanical Science and Technology, 2021, 35(11): 4997–5005.
[38] Deng F., Qin N., An exploitation-enhanced multi-objective efficient global optimization algorithm for expensive aerodynamic shape optimizations. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2022, 236(7): 1408–1421.
[39] Yang X., Jiang B., Wang J., et al., Multi-objective optimization of dual-arc blades in a squirrel-cage fan using modified non-dominated sorting genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2020, 234(8): 1053–1068.
[40] Zhou H., Zhou S., Gao Z., et al., Blades optimal design of squirrel cage fan based on hicks-henne function. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2021, 235(19): 3844–3858.
[41] Kim M.S., Park J.H., Lee K.S., et al., Optimum design of cooling fan considering experimental method for three-phase induction motor. 2020 23rd International Conference on Electrical Machines and Systems (ICEMS), 2020, pp. 1220–1224.
[42] Aydin A., Yigit C., Engin T., et al., Optimisation of a mixed flow fan with NACA profiled blades using computational fluid dynamics. Progress in Computational Fluid Dynamics, an International Journal, 2020, 20(5): 263–272.
[43] Chai X., Xu L., Sun Y., et al., Development of a cleaning fan for a rice combine harvester using computational fluid dynamics and response surface methodology to optimise outlet airflow distribution. Biosystems Engineering, 2020, 192: 232–244.
[44] Ding T., Fang L., Ni J.Q., et al., Optimization design of agricultural fans based on skewed-swept blade technology. Applied Engineering in Agriculture, 2019, 35(2): 249–258.
[45] Yan C., Yin Z., Shen X., et al., Axisymmetric hub-endwall profile optimization for a transonic fan to improve aerodynamic performance based on an integrated design optimization method. Structural and Multidisciplinary Optimization, 2019, 60(3): 1267–1282.
[46] Park S.M., Ryu S.Y., Cheong C., et al., Optimization of the orifice shape of cooling fan units for high flow rate and low-level noise in outdoor air conditioning units. Applied Sciences, 2019, 9(23): 5207.
[47] Zuhal L.R., Palar P.S., Shimoyama K., A comparative study of multi-objective expected improvement for aerodynamic design. Aerospace Science and Technology, 2019, 91: 548–560.
[48] Seo H.J., Kang Y.J., Lee H.C., et al., Optimization of the configuration of the laidback fan-shaped film cooling hole with a lateral expansion angle of 10 degrees. Applied Thermal Engineering, 2019, 153: 379–389.
[49] Jin Y., Wang H., Sun C., Data-driven evolutionary optimization. Springer, London, 2021.
[50] Chandrashekar G., Sahin F., A survey on feature selection methods. Computers & Electrical Engineering, 2014, 40(1): 16–28.
[51] Hardoon D.R., Szedmak S., Shawe-Taylor J., Canonical correlation analysis: An overview with application to learning methods. Neural computation, 2004, 16(12): 2639–2664.
[52] Smith L.I., A tutorial on principal components analysis, 2002. Computer Science Technical Report No. OUCS-2002-12. http://hdl.handle.net/10523/7534
[53] Habib A., Singh H. K., Chugh T., et al., A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive multi/many objective optimization. IEEE Transactions on Evolutionary Computation, 2019, 23(6): 1000–1014.
[54] Cheng R., Jin Y., Olhofer M., et al., A reference vector guided evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 2016, 20(5): 773–791.
[55] Zhang Q., Li H., MOEA/D: A multi-objective evolutionary algorithm based on decomposition. IEEE Transactions on Evolutionary Computation, 2007, 11(6): 712–731.
[56] Zitzler E., Deb K., Thiele L., Comparison of multi-objective evolutionary algorithms: Empirical results. Evolutionary Computation, 2000, 8(2): 173–195.
[57] Deb K., Thiele L., Laumanns M., et al., Scalable test problems for evolutionary multi-objective optimization. Evolutionary Multi-objective Optimization, 2005, pp. 105–145.
[58] Xiong J., Zhang Y., Guo P., et al., Inlet box structure optimization of a large axial-flow fan using response surface methodology. ASME International Mechanical Engineering Congress and Exposition, 2020, Paper No. IMECE2020-23566.
