Optimization of Suction Control on an Airfoil Using Multi-island Genetic Algorithm

Zhao, Da; Wang, Y.K.; Cao, Wei; Zhou, Ping

doi:10.1016/j.proeng.2014.12.591

Cited by 31 publications

(21 citation statements)

References 14 publications

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“…Thus, MIGA can prevent the problem of being 'premature' by maintaining the diversity of the population. In addition, the calculation speed of MIGA can be faster than those of traditional genetic algorithms (Zhao et al, 2015). NLPQL is a sequential quadratic programming (SQP) method which can solve problems by continuous smoothing.…”

Section: Optimization Methodsmentioning

confidence: 99%

“…The accuracy of surrogate models for a particular problem should be checked because different models may have different performances. Global optimization algorithms such as the multi-island genetic algorithm (MIGA) (Zhao et al, 2015) and optimal gradient methods such as nonlinear programming by quadratic Lagrangian (NLPQL) have been presented recently, and their capacities for airfoil optimization have been compared in this paper. Ma et al (2015) optimized the aerodynamic shape of a hypersonic lifting body using a multi-objective evolutionary algorithm based on a decomposition (MOEA/D) method, which was in turn based on the kriging model, but the shape function of the CST method they used was omitted in optimization, so not all configurations may have been presented.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method

Zhang

Huang

Wang

et al. 2016

J. Zhejiang Univ. Sci. A

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An excellent airfoil with a high lift-to-drag ratio may decrease oil consumption and enhance the voyage. Based on NACA 0012, an improved airfoil is explored in this paper. The class/shape function transformation has been proved to be a good method for airfoil parameterization, and in this paper it is modified to improve imitation accuracy. The computational fluid dynamics method is applied to obtain numerically the aerodynamic parameters of the parameterized airfoil, and the result is proved credible by comparison with available experimental data in the open literature. A polynomial-based response surface model and the uniform Latin hypercube sampling method are employed to decrease computational cost. Finally, the nonlinear programming by quadratic Lagrangian method is utilized to modify the multi-island genetic algorithm, which has an improved optimization effect than the method used on its own. The obtained result shows that the modified class/shape function transformation method produces a better imitation of an airfoil in the nose and tail regions than the original method, and that it will satisfy the tolerance zone of the model in a wind tunnel. The response surface model based on the uniform Latin hypercube sampling method gives an accurate prediction of the lift-to-drag ratio with changes in the design variables. The numerical result of the flow around the airfoil shows reasonable agreement with the experimental data graphically and quantitatively. Ultimately, an airfoil with better capacity than the original one is acquired using the multi-island genetic algorithm based nonlinear programming by quadratic Lagrangian optimization method. The pressure contours and lift-to-drag ratio along with the attack angle have been compared with those of the original airfoil, and the results demonstrate the strength of the optimized airfoil. The process for exploring an improved airfoil through parameterization to optimization is worth referencing in future work.

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Section: Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method

Zhang

Huang

Wang

et al. 2016

J. Zhejiang Univ. Sci. A

View full text Add to dashboard Cite

show abstract

“…Then the selection, crossover, and mutation operations are executed for the every sub-population like the traditional GA. And the individuals of the sub-populations are exchanged by the migration operation. The calculation speed of MIGA can be faster than those of traditional genetic algorithms [29]. The MIGA parameters of S1223 airfoil optimization are presented in Table 1.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Airfoil Optimization Design Based on the Pivot Element Weighting Iterative Method

Liu

2018

Algorithms

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Class function/shape function transformation (CST) is an advanced geometry representation method employed to generate airfoil coordinates. Aiming at the morbidity of the CST coefficient matrix, the pivot element weighting iterative (PEWI) method is proposed to improve the condition number of the ill-conditioned matrix in the CST. The feasibility of the PEWI method is evaluated by using the RAE2822 and S1223 airfoil. The aerodynamic optimization of the S1223 airfoil is conducted based on the Isight software platform. First, the S1223 airfoil is parameterized by the CST with the PEWI method. It is very significant to confirm the range of variables for the airfoil optimization design. So the normalization method of design variables is put forward in the paper. Optimal Latin Hypercube sampling is applied to generate the samples, whose aerodynamic performances are calculated by the numerical simulation. Then the Radial Basis Functions (RBF) neural network model is trained by these aerodynamic performance data. Finally, the multi-island genetic algorithm is performed to achieve the maximum lift-drag ratio of S1223. The results show that the robustness of the CST can be improved. Moreover, the lift-drag ratio of S1223 increases by 2.27% and the drag coefficient decreases by 1.4%.

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“…The traditional GA is compared with the MIGA and the latter is proved to be more effective and less likely to fall into local optimal results. 14 MIGA has been applied widely in different disciplines such as optimization on satellite separation systems, 15 turbulence model optimization 16 and optimization of suction control in airfoil, 17 etc. However, the MIGA is merely used in the optimization of composite cylindrical hulls, let alone used in the CRSCH composed with uniform or hybrid materials.…”

Section: Introductionmentioning

confidence: 99%

Optimization of composite ring stiffened cylindrical hulls for unmanned underwater vehicles using multi-island genetic algorithm

Song

Lyu

Jiang

2018

Journal of Reinforced Plastics and Composites

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The usage of composite material helps reducing structure’s weight in many conditions. In this paper, The Composite Ring Stiffened Cylindrical Hulls used by Unmanned Underwater Vehicles is optimized in various depths. The optimization aims to reducing the weight of the composite ring stiffened cylindrical hulls. Two candidate composite materials, T700/Epoxy and B(4)5505/Epoxy, are chosen to form the outer shell and stiffeners. Number and shape of the stiffeners, ply angles, and the number of the plies are considered. The Multi-Island Genetic Algorithm (MIGA) is performed in MATLAB and a new two-step method is proposed in crossover operations. ANSYS parametric design language is integrated in optimization procedure to ensure the acceptance of the optimal result. The results reveal that the proposed two-step method for multi-island genetic algorithm is efficiency and robust in reducing the weight of the composite ring stiffened cylindrical hulls. The weight for optimized composite ring stiffened cylindrical hulls with T700/Epoxy shells and B(4)5505/Epoxy stiffeners is 10.5% lighter than that with single composite material when the operating depth is 200 m.

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Optimization of Suction Control on an Airfoil Using Multi-island Genetic Algorithm

Cited by 31 publications

References 14 publications

A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method

A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method

Airfoil Optimization Design Based on the Pivot Element Weighting Iterative Method

Optimization of composite ring stiffened cylindrical hulls for unmanned underwater vehicles using multi-island genetic algorithm

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