Aerodynamic shape optimization of co-flow jet airfoil using a multi-island genetic algorithm

Jiang, Hao; Xu, Ming; Yao, Weigang

doi:10.1063/5.0124372

Cited by 14 publications

(4 citation statements)

References 47 publications

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“…The main feature of MIGA is that a large population is divided into several subpopulations, namely "islands", and the subpopulations on each "island" are optimized by a genetic algorithm. Therefore, the MIGA will conduct population individual exchange between "islands" and "islands" [25,26]. The main process of MIGA is shown in Figure 7.…”

Section: Optimization Of Migamentioning

confidence: 99%

Research on Noise Reduction of Water Hydraulic Throttle Valve Based on RBF Neural Network and Multi-Island Genetic Algorithm

Wang,

Nan,

Zhou

et al. 2024

Machines

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Excessive pressure drop within the internal flow channel of the water hydraulic throttle valve will generate severe noise. In order to reduce the noise of the throttle valve, in this paper, the model of the throttle valve was established, and the flow characteristics and acoustic characteristics of the valve were simulated. The simulation results showed that the parameters of the throat structure, such as the half angle, throat inlet angle and throat length, have a significant effect on the noise of the valve. Then, the three main structural parameters were used as optimization variables, and radial basis function (RBF) neural networks and multi-island genetic algorithms (MIGA) were used to reduce the noise of the valve. The approximate model of the relationship between the structural parameters of the valve and noise was established by RBF neural networks, and MIGA was used to optimize the approximate model. Finally, the optimal valve model was established based on the obtained optimal parameters, and its noise was analyzed through simulation and experiment. The research results indicated that the optimization method, which combines RBF Neural Network and MIGA, can effectively reduce the noise of hydraulic throttle valves.

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Section: Optimization Of Migamentioning

confidence: 99%

Research on Noise Reduction of Water Hydraulic Throttle Valve Based on RBF Neural Network and Multi-Island Genetic Algorithm

Wang,

Nan,

Zhou

et al. 2024

Machines

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“…As per our previous study [34], the airfoil used in the experiment was the optimized co-flow jet 6421 (OCFJ6421) airfoil. This airfoil is an improvement over the CFJ6421 airfoil achieved by coupling and optimizing the CFJ technology with the parametric shape.…”

Section: Experimental Airfoil and Scheme Designmentioning

confidence: 99%

“…Design variables c i ( ×10 −2 )[34] of the OFJ6421 airfoil in optimization. From 1 to 7 is from the leading edge to the trailing edge…”

mentioning

confidence: 99%

Experimental design for a novel co-flow jet airfoil

Jiang,

Yao,

2023

Adv. Aerodyn.

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The Co-flow Jet (CFJ) technology holds significant promise for enhancing aerodynamic efficiency and furthering decarbonization in the evolving landscape of air transportation. The aim of this study is to empirically validate an optimized CFJ airfoil through low-speed wind tunnel experiments. The CFJ airfoil is structured in a tri-sectional design, consisting of one experimental segment and two stationary segments. A support rod penetrates the airfoil, fulfilling dual roles: it not only maintains the structural integrity of the overall model but also enables the direct measurement of aerodynamic forces on the test section of the CFJ airfoil within a two-dimensional wind tunnel. In parallel, the stationary segments are designed to effectively minimize the interference from the lateral tunnel walls. The experimental results are compared with numerical simulations, specifically focusing on aerodynamic parameters and flow field distribution. The findings reveal that the experimental framework employed is highly effective in characterizing the aerodynamic behavior of the CFJ airfoil, showing strong agreement with the simulation data.

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“…13,14 Optimization is usually divided into three procedures: shape parameterization, deriving the optimization algorithm, and fitness value evaluation. 15 Honing these procedures should result in the effectiveness and efficiency of optimization. 16 During optimization, the dimensions of its design variables are completely determined using parameterization methods.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic optimization method of intake grille of active clearance control system for turbines based on modified social spider algorithm (MSSA)

Xie,

Zhang,

Shi

et al. 2024

Advances in Mechanical Engineering

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During the operation of an active clearance control (ACC) system of a turbine, the aerodynamic performance of the intake grille indirectly influences its control. To improve the performance, an aerodynamic optimization method is proposed, consisting of parameterization, an optimization algorithm, and a fitness evaluation. During parameterization, its geometry is represented by seven geometric variables. A modified social spider algorithm is used as the optimization algorithm. To evaluate the aerodynamic performance of the grille, a special fitness function is adopted, obtained using an adaptive topological multi-layer feedforward artificial neural network. To verify the feasibility of this method, experiments and numerical calculations are carried out on the original and optimized intake grilles. The results show that the average intake flow rate and average total pressure recovery coefficient of the optimized grille have increased by 17.3% and 4.9%, respectively.

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Aerodynamic shape optimization of co-flow jet airfoil using a multi-island genetic algorithm

Cited by 14 publications

References 47 publications

Research on Noise Reduction of Water Hydraulic Throttle Valve Based on RBF Neural Network and Multi-Island Genetic Algorithm

Research on Noise Reduction of Water Hydraulic Throttle Valve Based on RBF Neural Network and Multi-Island Genetic Algorithm

Experimental design for a novel co-flow jet airfoil

Aerodynamic optimization method of intake grille of active clearance control system for turbines based on modified social spider algorithm (MSSA)

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