Aerodynamic Optimization Design of Compressor Blades Based on Improved Artificial Bee Colony Algorithm

Cheng, Jian; Jiang, Chen; Xiang, Hang

doi:10.2514/6.2018-4825

Cited by 4 publications

(7 citation statements)

References 4 publications

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“…The IABC [31] algorithm involves employed bees, onlooker bees, and detector bees. At the beginning, the employed and onlooker bees constitute the entire bee colony, and the number of bees is divided equally between these types.…”

Section: International Journal Of Aerospace Engineeringmentioning

confidence: 99%

“…Another important part of the optimization process is the optimization algorithm. To avoid falling into a local extremum, this paper adopts an improved artificial bee colony (IABC) algorithm with good global optimization ability [31], which does not depend on the initial solution. In addition, due to the improvements in initialization, food source exploration, and exploitation mechanisms from the standard artificial bee colony [32] (ABC) algorithm, its convergence speed is improved.…”

Section: Introductionmentioning

confidence: 99%

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Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy

Cheng

Zhao

Dong

et al. 2021

International Journal of Aerospace Engineering

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A new design optimization method is proposed for the problem of high-precision aerodynamic design of multistage axial compressors. The method mainly contains three aspects: full-blade surface parametrization can significantly reduce the number of control variables per blade row and increase the degrees of freedom of the leading edge blade angle compared with the traditional semiblade parametric method; secondly, the artificial bee colony algorithm improved initialization and food source exploration and exploitation mechanism to enhance the global optimization ability and convergence speed, and a distributed optimization system is built on the supercomputing platform based on this method; finally, a phased optimization strategy based on the “synchronous change in multirow blades” is proposed, and expert experience is introduced to achieve a better balance between exploration and exploitation. The optimization method is applied to the AL-31F four-stage low-pressure compressor. As a result, the adiabatic efficiency is improved by 0.67% and the surge margin is improved by 3.1% under the premise that the total pressure ratio and mass flow rate satisfy the constraints, which verifies the effectiveness and engineering practicality of the proposed optimization method in the field of multistage axial flow compressor aerodynamic optimization.

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Section: International Journal Of Aerospace Engineeringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy

Cheng

Zhao

Dong

et al. 2021

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

show abstract

“…It essentially uses initialization, exploration of employed bees, onlooker bees, and detector bees to recognize global and local information. As an improvement of the standard artificial bee colony algorithm (for a detailed introduction of the ABC algorithm, refer to [44]), it is mainly implemented from three aspects: (1) an initialization method, (2) a food source exploration mechanism of employed bees, and (3) a food source exploitation mechanism of onlooker bees. e detailed explanation is as follows:…”

Section: Optimization Algorithm and Optimization Platformmentioning

confidence: 99%

“…Compared with GA and ABC algorithms, IABC algorithm has better global optimization accuracy and convergence speed, and more details can be found in [44].…”

Section: Optimization Algorithm and Optimization Platformmentioning

confidence: 99%

Research on Aerodynamic Optimization Method of Multistage Axial Compressor under Multiple Working Conditions Based on Phased Parameterization Strategy

Cheng

Dong

Zhao

et al. 2021

Mathematical Problems in Engineering

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Multistage axial compressor is the key component of aeroengine and gas turbine to realize energy conversion. In order to avoid the “curse of dimensionality” problem in the global optimization process of AL-31F four-stage low-pressure compressor under multiple working conditions, an optimization method based on phased parameterization strategy is proposed. The method uses the idea of “exploration before exploitation” for reference and divides the optimization process into two phases. In the first phase, the traditional parametric modification method based on stacking line is adopted; in the second phase, the full-blade surface parametric modification method with significant low-dimensional characteristics is adopted. Based on the improved artificial bee colony algorithm, a multitask concurrent optimization system is built on the supercomputing platform, and the engineering optimization solution is obtained within 91 hours. The optimization results are as follows: under the condition of meeting the constraints, the adiabatic efficiency is increased by 0.3% and the surge margin is 4.0% at the design speed; the adiabatic efficiency is increased by 0.8% and the surge margin is 2.3% at the off-design speed. These results verify the usefulness and reliability of the optimization method in the field of aerodynamic optimization of a multistage axial flow compressor.

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“…The evolutionary algorithm is a widely used method in the field of engineering optimization [33][34][35], which has good robustness and global convergence. For a better global search, the optimization process uses the IABC algorithm proposed in the literature [36]. The IABC algorithm is used because it has the following three advantages: (1) the IABC algorithm is global, robust, and does not depend on the initial solution; (2) each generation of individuals is independent of each other, which allows for multitask concurrency and shortens optimization time by taking advantage of the enormous computational power of commercial supercomputing platforms [37]; (3) compared to general-purpose genetic algorithms and standard artificial bee colony (ABC) algorithms, the IABC algorithm has better global search and fast convergence capability.…”

Section: Optimization Algorithmmentioning

confidence: 99%

A Novel Surface Parametric Method and Its Application to Aerodynamic Design Optimization of Axial Compressors

et al. 2021

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A novel parametric control method for the compressor blade, the full-blade surface parametric method, is proposed in this paper. Compared with the traditional parametric method, the method has good surface smoothness and construction convenience while maintaining low-dimensional characteristics, and compared with the semi-blade surface parametric method, the proposed method has a larger degree of geometric deformation freedom and can account for changes in both the suction surface and pressure surface. Compared with the semi-blade surface parametric method, the method only has four more control parameters for each blade, so it does not significantly increase the optimization time. The effectiveness of this novel parametric control method has been verified in the aerodynamic optimization field of compressors by an optimization case of Stage35 (a single-stage transonic axial compressor) under multi-operating conditions. The optimization case has brought the following results: the adiabatic efficiency of the optimized blade at design speed is 1.4% higher than that of the original one and the surge margin 2.9% higher, while at off-design speed, the adiabatic efficiency is improved by 0.6% and the surge margin by 1.3%.

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Aerodynamic Optimization Design of Compressor Blades Based on Improved Artificial Bee Colony Algorithm

Cited by 4 publications

References 4 publications

Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy

Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy

Research on Aerodynamic Optimization Method of Multistage Axial Compressor under Multiple Working Conditions Based on Phased Parameterization Strategy

A Novel Surface Parametric Method and Its Application to Aerodynamic Design Optimization of Axial Compressors

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