Research on the lean and swept optimization of a single stage axial compressor

Wang, Zhongyi; Qu, Feng; Wang, Yanhua; Luan, Yigang; Wang, Meng

doi:10.1080/19942060.2020.1862708

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…Li 6 parameterized the influence of blade angle and radial blade angle by using the numerical thermal fluid model verified previously. Wang et al 7 combined artificial neural networks and genetic algorithms to optimize the calculation. The calculation results show that the isentropic efficiency and stall margin of the system could be effectively improved by this method.…”

Section: Subscriptsmentioning

confidence: 99%

Air volume flow rate optimization of the guide vanes in an axial flow fan based on DOE and CFD

Chen

Zhu

et al. 2023

Sci Rep

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The unreasonable design of guide vanes in the axial fan could have negative effects. In order to enhance the performance, the relationship between the air volume flow rate of the selected axial fan and geometric parameters of guide vanes is firstly analysed by DOE and CFD, and optimal parameters are found by the Gaussian Process method. Results show that the number and total chord of guide vanes have a nonlinear effect on the air volume flow, and the total chord of vanes is the main factor in affecting calculation results. For the particular configuration studied here, the optimal design of guide vanes shows that lessening the chord of vanes by 38 mm and increasing the number of the vanes to 18 could produce more airflow under the same rotation speed.

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Section: Subscriptsmentioning

confidence: 99%

Air volume flow rate optimization of the guide vanes in an axial flow fan based on DOE and CFD

Chen

Zhu

et al. 2023

Sci Rep

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“…The intersection interface transports data between the two domains. After the RMS residuals of the continuity and momentum equations are less than 10 -4 , numerical simulations are deemed to converge [26,27].…”

Section: Boundary Conditionsmentioning

confidence: 99%

Experiment and optimization of axial air-suction roller seed metering device

Zhang

Yang

Zhang

et al. 2023

Preprint

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The seed metering device construction is adjusted to improve the negative pressure at the seed metering device type hole and hence the seed suction efficiency. To explore the link between the structural parameters of the seed metering device and the negative pressure of the type hole, the Response Surface Methodology (RSM) is integrated with Computational Fluid Dynamics (CFD). Grid independence was tested to assure the solution's dependability. The internal flow field of the seed metering device was investigated, and the negative pressure at the type hole's input was 56.71 Pa. The Central Composite Design (CCD) in the response surface method was employed to generate a more perfect negative pressure at the suction of the type hole. The diameter of the air chamber channel, the draft angle of the type hole, and the number of fan blades were employed as design factors, and the major target function was the negative pressure at the entrance of the type hole. According to regression research, the optimal point occurs when the air chamber channel diameter is 59.26mm, the draft angle of the type hole is 14.28°, and the number of fan blades is 9. The objective function predicts a negative pressure of 69.41 Pa at the type hole's inlet. The Central Composite Design (CCD) in the response surface method was employed to generate a more perfect negative pressure at the suction of the type hole. The diameter of the air chamber channel, the draft angle of the type hole, and the number of fan blades were employed as design factors, and the major target function was the negative pressure at the entrance of the type hole. According to regression research, the optimal point occurs when the air chamber channel diameter is 59.26mm, the draft angle of the type hole is 14.28°, and the number of fan blades is 9. The objective function predicts a negative pressure of 69.41 Pa at the type hole's inlet.

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“…Therefore, genetic algorithm is a better choice. 5,6 In order to solve the computational cost problem of genetic algorithm, 5,7,8 the surrogate-aided optimization proposed by researchers is widely used in the 3D blade optimization, 9,10 which uses the cheap surrogate model instead of the CFD calculation.…”

Section: Introductionmentioning

confidence: 99%

Research on infilling strategy in surrogate-aided optimization for axial compressor blades

Liu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part A:

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The hybrid Voronoi-Latin Hypercube Sampling (Voronoi-LHS) method is proposed for the surrogate-aided optimization of the axial compressor blades. The hybrid method is first applied to the fundamental test cases. The analytical results show that, compared with the Voronoi and LHS strategies, the hybrid method generally improves the robustness and convergency. Then the multi-objective genetic algorithm (MOGA) in conjunction with the artificial neural network (ANN) is applied to optimize the aerodynamic performance of an axial compressor rotor. Before the optimization process, the hybrid Voronoi-LHS sample infilling method is employed to refine the ANN surrogate model. Considering the typical intake distortion, the sweep and lean distributions of this rotor are optimized to pursue the maximum total pressure ratio and adiabatic efficiency. The results show that the optimization significantly improves the pressure ratio, efficiency and surge margin of the compressor with low computing cost.

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Research on the lean and swept optimization of a single stage axial compressor

Cited by 10 publications

References 20 publications

Air volume flow rate optimization of the guide vanes in an axial flow fan based on DOE and CFD

Air volume flow rate optimization of the guide vanes in an axial flow fan based on DOE and CFD

Experiment and optimization of axial air-suction roller seed metering device

Research on infilling strategy in surrogate-aided optimization for axial compressor blades

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