Multi-Objective Aerodynamic Optimization of Elements' Setting for High-lift Airfoil Using Kriging Model

Multi-Objective Aerodynamic Exploration of Elements’ Setting for High-Lift Airfoil Using Kriging Model

JOURNAL OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES ◽

10.2322/jjsass.54.419 ◽

2006 ◽

Vol 54 (632) ◽

pp. 419-426 ◽

Cited By ~ 1

Author(s):

Masahiro Kanazaki ◽

Shinkyu Jeong ◽

Kentaro Tanaka ◽

Kazuomi Yamamoto

Keyword(s):

Kriging Model ◽

High Lift ◽

Multi Objective

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Multi-Objective Aerodynamic Optimization of the Streamlined Shape of High-Speed Trains Based on the Kriging Model

PLoS ONE ◽

10.1371/journal.pone.0170803 ◽

2017 ◽

Vol 12 (1) ◽

pp. e0170803 ◽

Cited By ~ 7

Author(s):

Gang Xu ◽

Xifeng Liang ◽

Shuanbao Yao ◽

Dawei Chen ◽

Zhiwei Li

Keyword(s):

High Speed ◽

Kriging Model ◽

Aerodynamic Optimization ◽

Multi Objective ◽

High Speed Trains

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A Study of Multi-Objective Aerodynamic Optimization Design for Variable Camber Airfoils and High Lift Devices

Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University ◽

10.1051/jnwpu/20183610083 ◽

2018 ◽

Vol 36 (1) ◽

pp. 83-90

Author(s):

Wangyi Zhou ◽

Junqiang Bai ◽

Lei Qiao ◽

Yasong Qiu ◽

Rui Liu ◽

...

Keyword(s):

High Speed ◽

Optimization Design ◽

Deflection Angle ◽

Aerodynamic Optimization ◽

Aerodynamic Forces ◽

High Lift ◽

Low Speed ◽

Multi Objective ◽

Multi Objective Genetic Algorithm ◽

Design Variables

Aiming at the synthetical optimization of the aerodynamic performance between the low-speed condition of two-dimensional high lift devices during take-off and landing phase and the high-speed condition of variable camber airfoil during cruise phase, an aerodynamic optimization design method for high lift device based on Kriging based surrogate model and multi-objective genetic algorithm has been developed. With the application of Adaptive Dropped Hinge Flap mechanism, the low-speed take-off and landing performance and high-speed cruise performance of the aircraft is improved by coupling deflection of the flap and spoiler. The position of flap hinge, deflection angle of spoiler and deflection angle of flap are taken as design variables; The Navier-Stokes equations are used to predict the aerodynamic forces of initial samples; The Kriging based surrogate model is employed to establish the algebraic relation between design variables and aerodynamic forces at take off, landing and cruise, obtaining four efficient prediction models for aerodynamic forces; Multi-objective optimization design with multi-objective genetic algorithm is conducted on the basis of surrogate models. The automatic generation of computational grid is achieved by the mesh deformation method based on RBF (Radial Basis Function) when the design variables change. On the basis of efficient global multi-objective optimization design platform, the synthetical optimization of high-speed and low-speed aerodynamic performance is conducted; The multi-objective solution set of the Pareto frontier is verified and analyzed, and the optimal solution with well matched high and low speed performance is selected.

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Multi-Objective Aerodynamic Exploration of Elements' Setting for High-Lift Airfoil Using Kriging Model

Journal of Aircraft ◽

10.2514/1.25422 ◽

2007 ◽

Vol 44 (3) ◽

pp. 858-864 ◽

Cited By ~ 19

Author(s):

Masahiro Kanazaki ◽

Kentaro Tanaka ◽

Shinkyu Jeong ◽

Kazuomi Yamamoto

Keyword(s):

Kriging Model ◽

High Lift ◽

Multi Objective

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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 ◽

10.1177/0954406221995863 ◽

2021 ◽

pp. 095440622199586

Author(s):

Qianhao Xiao ◽

Jun Wang ◽

Boyan Jiang ◽

Weigang Yang ◽

Xiaopei Yang

Keyword(s):

Flow Rate ◽

Optimization Design ◽

Volume Flow Rate ◽

Kriging Model ◽

Volume Flow ◽

Design Parameters ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

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A Kriging-Assisted Multi-Objective Constrained Global Optimization Method for Expensive Black-Box Functions

Mathematics ◽

10.3390/math9020149 ◽

2021 ◽

Vol 9 (2) ◽

pp. 149

Author(s):

Yaohui Li ◽

Jingfang Shen ◽

Ziliang Cai ◽

Yizhong Wu ◽

Shuting Wang

Keyword(s):

Global Optimization ◽

Pareto Frontier ◽

Kriging Model ◽

Optimization Method ◽

Function Evaluation ◽

Sampling Point ◽

Constrained Global Optimization ◽

Multi Objective ◽

Sample Data ◽

Sampling Points

The kriging optimization method that can only obtain one sampling point per cycle has encountered a bottleneck in practical engineering applications. How to find a suitable optimization method to generate multiple sampling points at a time while improving the accuracy of convergence and reducing the number of expensive evaluations has been a wide concern. For this reason, a kriging-assisted multi-objective constrained global optimization (KMCGO) method has been proposed. The sample data obtained from the expensive function evaluation is first used to construct or update the kriging model in each cycle. Then, kriging-based estimated target, RMSE (root mean square error), and feasibility probability are used to form three objectives, which are optimized to generate the Pareto frontier set through multi-objective optimization. Finally, the sample data from the Pareto frontier set is further screened to obtain more promising and valuable sampling points. The test results of five benchmark functions, four design problems, and a fuel economy simulation optimization prove the effectiveness of the proposed algorithm.

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Multi-objective optimization of weld geometry in hybrid fiber laser-arc butt welding using Kriging model and NSGA-II

Applied Physics A ◽

10.1007/s00339-016-0144-2 ◽

2016 ◽

Vol 122 (6) ◽

Cited By ~ 9

Author(s):

Zhongmei Gao ◽

Xinyu Shao ◽

Ping Jiang ◽

Chunming Wang ◽

Qi Zhou ◽

...

Keyword(s):

Fiber Laser ◽

Kriging Model ◽

Multi Objective Optimization ◽

Hybrid Fiber ◽

Nsga Ii ◽

Butt Welding ◽

Multi Objective ◽

Weld Geometry

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Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

Aircraft Engineering and Aerospace Technology ◽

10.1108/aeat-02-2021-0055 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Ramazan Özkan ◽

Mustafa Serdar Genç

Keyword(s):

Structural Optimization ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Design Parameters ◽

Aerodynamic Optimization ◽

Nsga Ii ◽

Content Type ◽

Multi Objective ◽

Optimization Study

Purpose Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine. Design/methodology/approach To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade. Findings As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production. Originality/value ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together.

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