scholarly journals Airfoil Optimization Design Based on the Pivot Element Weighting Iterative Method

Algorithms ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 163 ◽  
Author(s):  
Xinqiang Liu ◽  
Weiliang He
Keyword(s):  
Optimization Design ◽  
Rbf Neural Network ◽  
Latin Hypercube Sampling ◽  
Coefficient Matrix ◽  
Aerodynamic Optimization ◽  
Airfoil Optimization ◽  
Design Variables ◽  
Aerodynamic Performances ◽  
Optimal Latin Hypercube Sampling ◽  
Drag Ratio

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%.

A multiobjective aerodynamic optimization design of a high-speed train head under crosswinds

2017 ◽  
Vol 232 (3) ◽  
pp. 895-912 ◽  
Author(s):  
Liang Zhang ◽  
Jiye Zhang ◽  
Tian Li ◽  
Yadong Zhang
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Free Form ◽  
Pareto Optimal ◽  
Head Coach ◽  
High Speed Train ◽  
Aerodynamic Optimization ◽  
Design Variables ◽  
Aerodynamic Performances ◽  
Sample Points

In this work, a multiobjective aerodynamic optimization of a high-speed train head was performed to improve the aerodynamic performance of the high-speed train running on an embankment under crosswinds. Seven optimization design variables were selected to control five regions on the train head. The total aerodynamic drag force, aerodynamic lift force, and aerodynamic side force of the head coach were set as the optimization objectives. The optimal Latin hypercube sampling method was used to obtain the values of the design variables of the sample points. The high-speed train head was deformed using the free-form deformation approach through which the mesh morphing was performed without remodeling and re-meshing. Then, the aerodynamic performances of the high-speed trains at the sample points were calculated using the computational fluid dynamics method. A Kriging surrogate model between the design variables and their optimization objectives was constructed. Then, the multiobjective aerodynamic optimization of the high-speed train head was performed using multiobjective genetic algorithms based on the Kriging model. Based on the results of the sample points, the relationships between the optimization design variables and the optimization objectives were analyzed, and the contributions of the primary factors to the optimization objectives were obtained. After optimization, a series of Pareto-optimal head shapes were obtained. The steady and unsteady aerodynamic performances of the train with an optimal head, which was selected from the Pareto-optimal head shapes, were compared with those of the original train.

Aerodynamic Efficiency Optimization of the 1st Stage of Transonic High Pressure Turbine through Lean and Sweep Angles

2019 ◽  
Vol 36 (3) ◽  
pp. 245-256
Author(s):  
Yoonki Kim ◽  
Sanga Lee ◽  
Kwanjung Yee ◽  
Young-Seok Kang
Keyword(s):  
High Pressure ◽  
Surrogate Model ◽  
Design Space ◽  
Latin Hypercube Sampling ◽  
Expected Improvement ◽  
Total Efficiency ◽  
High Pressure Turbine ◽  
Sweep Angle ◽  
Design Variables ◽  
Optimal Latin Hypercube Sampling

Abstract The purpose of this study is to optimize the 1st stage of the transonic high pressure turbine (HPT) for enhancement of aerodynamic performance. Isentropic total-to-total efficiency is designated as the objective function. Since the isentropic efficiency can be improved through modifying the geometry of vane and rotor blade, lean angle and sweep angle are chosen as design variables, which can effectively alter the blade geometry. The sensitivities of each design variable are investigated by applying lean and sweep angles to the base nozzle and rotor, respectively. The design space is also determined based on the results of the parametric study. For the design of experiment (DoE), Optimal Latin Hypercube sampling is adopted, so that 25 evenly distributed samples are selected on the design space. Sequentially, based on the values from the CFD calculation, Kriging surrogate model is constructed and refined using Expected Improvement (EI). With the converged surrogate model, optimum solution is sought by using the Genetic Algorithm. As a result, the efficiency of optimum turbine 1st stage is increased by 1.07 % point compared to that of the base turbine 1st stage. Also, the blade loading, pressure distribution, static entropy, shock structure, and secondary flow are thoroughly discussed.

Optimization of a vacuum cleaner fan suction and shaft power using Kriging surrogate model and MIGA

2021 ◽  
pp. 095765092110496
Author(s):  
Soheil Almasi ◽  
Mohammad Mahdi Ghorani ◽  
Mohammad Hadi Sotoude Haghighi ◽  
Seyed Mohammad Mirghavami ◽  
Alireza Riasi
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Internal Flow ◽  
Latin Hypercube Sampling ◽  
Sample Space ◽  
Geometrical Parameters ◽  
Vacuum Cleaner ◽  
Time Saving ◽  
Design Variables ◽  
Shaft Power

Optimization of vacuum cleaner fan components is a low-cost and time-saving solution to satisfy the increasing requirement for compact energy-efficient cleaners. In this study, surrogate-based optimization technique is used and for the first time it is focused on maximization of Airwatt parameter, which describes the fan suction power, as an objective function (Case II). Besides, the shaft power is minimized (Case I) as another optimization target in order to reduce the power consumption of the vacuum cleaner. 11 geometrical variables of 3 fan components including impeller, diffuser and return channel are selected as the optimization design variables. 80 training points are distributed in the sample space using Advanced Latin Hypercube Sampling (ALHS) technique and the outputs of sample points are calculated by means of CFD simulations. Kriging and RSA surrogate models have been fitted to the outputs of the sample space. Through coupling of constructed Kriging models and Multi-Island Genetic Algorithm (MIGA), the optimal design for each of the optimization cases is presented and evaluated using numerical simulations. A 20.22% reduction in shaft power in Case I and an improvement of 27.73% in Airwatt in Case II have been achieved as the overall results of this study. Despite achieving goals in both optimization cases, a slight decrease in Airwatt in Case I (−6.20%) and a slight increase in shaft power in Case II (+4.82%) are observed relative to primary fan. Furthermore, the Analysis of Variance (ANOVA) determines the importance level of design variables and their 2-way interactions on the objective functions. It was concluded that geometrical parameters related to all of the fan components must be considered simultaneously to conduct a comprehensive optimization. The reasons of enhancement in optimal cases compared with the reference design have been further investigated by analysis of the fan internal flow field. Post-processing of the CFD results demonstrates that the applied geometrical modifications cause a more uniform flow through the flow passages of the optimal fan components.

Aerodynamic Optimization Design of Airfoil Shape Using Entropy Generation as an Objective

2018 ◽  
Vol 11 (2) ◽  
Author(s):  
Wei Wang ◽  
Jun Wang ◽  
Xiao-Pei Yang ◽  
Yan-Yan Ding
Keyword(s):  
Entropy Generation ◽  
Energy Cost ◽  
Optimization Design ◽  
Generation Rate ◽  
Entropy Generation Rate ◽  
Aerodynamic Optimization ◽  
Analysis And Design ◽  
Constraint Model ◽  
The Impact ◽  
Drag Ratio

Abstract An entropy analysis and design optimization methodology is combined with airfoil shape optimization to demonstrate the impact of entropy generation on aerodynamics designs. In the work herein, the entropy generation rate is presented as an extra design objective along with lift-drag ratio, while the lift coefficient is the constraint. Model equation, which calculates the local entropy generation rate in turbulent flows, is derived by extending the Reynolds-averaging of entropy balance equation. The class-shape function transform (CST) parametric method is used to model the airfoil configuration and combine the radial basis functions (RBFs) based mesh deformation technique with flow solver to compute the quantities such as lift-drag ratio and entropy generation at the design condition. From the multi-objective solutions which represent the best trade-offs between the design objectives, one can select a set of airfoil shapes with a low relative energy cost and with improved aerodynamic performance. It can be concluded that the methodology of entropy generation analysis is an effective tool in the aerodynamic optimization design of airfoil shape with the capability of determining the amount of energy cost.

Aerodynamic Optimization Design of Airfoil Based on Directly Manipulated FFD Technique

2013 ◽  
Vol 390 ◽  
pp. 121-128 ◽  
Author(s):  
Jun Qiang Bai ◽  
Song Chen
Keyword(s):  
Shape Optimization ◽  
Drag Reduction ◽  
Optimization Design ◽  
High Order ◽  
Control Points ◽  
Aerodynamic Shape Optimization ◽  
Aerodynamic Optimization ◽  
Aerodynamic Shape ◽  
Design Variables ◽  
Geometrical Constraints

The method of applying direct manipulated FFD (DFFD) technique into aerodynamic shape optimization has been proposed and researched. Due to the disadvantage of the original FFD method within which the geometrical manipulation is not direct and intuitive, the DFFD approach has been developed by solving each displacement of the FFD control points with some specified geometry points movements, so that the deformation of the target geometry could be directly manipulated. Besides, it has been illustrated that by DFFD method a relatively small number of design variables together with high order FFD control frame could be accomplished. The study cases has shown that applying this method in aerodynamic shape optimization of airfoil for drag reduction is of good feasibility and result, and could be coupled with effective geometrical constraints like airfoil thickness.

Three-Dimensional Aerodynamic Optimization for Axial-Flow Compressors Based Upon the Inverse Design and the Aerodynamic Variables

2010 ◽  
Author(s):  
Liu He ◽  
Peng Shan
Keyword(s):  
Computer Aided Design ◽  
Optimization Design ◽  
Three Dimensional ◽  
Visual Sensitivity ◽  
Inverse Design ◽  
Geometrical Parameters ◽  
Optimization Strategy ◽  
Design Code ◽  
Aerodynamic Optimization ◽  
Design Variables

Integrating a genetic algorithm code with a response surface methodology code based upon the artificial neural network model, this paper develops an optimization system. By introducing a quasi-three dimensional through-flow design code and a design code of axial compressor airfoils with camber lines of arbitrary shape, and involving a three-dimensional computational fluid dynamics solver, this paper establishes a numerical aerodynamic optimization platform for the three-dimensional blades of axial compressors. The optimization in this paper mainly has four features. First, it applies the conventional inverse design method instead of the common computer aided design parameterization method to generate a three-dimensional blade. Second, it chooses aerodynamic parameters with physical meaning as optimization design variables instead of purely geometrical parameters. Third, it presents a stage-by-stage optimization strategy about the multistage turbomachinery optimization. Fourth, it introduces the visual sensitivity analysis method into optimization, which can adjust variation ranges of variables by analysing how great the variables influence the objective function. The above techniques were applied to the redesign of a single rotor row and two double-stage axial fans separately. The departure angles and work distributions in the inverse design were taken as design variables separately in optimizations of the single rotor and double-stage fans, and they were parametrically represented by means of Be´zier curves, whose parameters were used as the optimization variables in the practical operation. The three investigated examples elucidate that not only the techniques mentioned above are appropriate and effective in engineering, but also the design guidance for similar inverse design problems can be obtained from the optimization results.

scholarly journals A New Aerodynamic Optimization Method with the Consideration of Dynamic Stability

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Mi Baigang ◽  
Wang Xiangyu
Keyword(s):  
Dynamic Stability ◽  
Optimization Design ◽  
Optimization Method ◽  
Aerodynamic Optimization ◽  
Conventional Optimization ◽  
And Control ◽  
Drag Ratio ◽  
Lift To Drag Ratio ◽  
Oscillation Method ◽  
Small Amplitude Oscillation

Dynamic stability is significantly important for flying quality evaluation and control system design of the advanced aircraft, and it should be considered in the initial aerodynamic design process. However, most of the conventional aerodynamic optimizations only focus on static performances and the dynamic motion has never been included. In this study, a new optimization method considering both dynamic stability and general lift-to-drag ratio performance has been developed. First, the longitudinal combined dynamic derivative based on the small amplitude oscillation method is calculated. Then, combined with the PSO (particle swarm optimization) algorithm, a dynamic stability derivative that must not be decreased is added to the constraints of optimization and the lift-drag ratio is chosen as the optimization objective. Finally, a new aerodynamic optimization method can be built. We take NACA0012 as an example to validate this method. The results show that the dynamic derivative calculation method is effective and conventional optimization design can significantly improve the lift-drag ratio. However, the dynamic stability is enormously changed at the same time. By contrast, the new optimization method can improve the lift-drag performance while maintaining the dynamic stability.

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

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.

scholarly journals Aerodynamic Optimization Design on Supersonic Transports Considering Sonic Boom Intensity

2020 ◽  
Vol 38 (2) ◽  
pp. 271-278
Author(s):  
Shaowei Liu ◽  
Junqiang Bai ◽  
Peixun Yu ◽  
Bao Chen ◽  
Boxiao Zhou
Keyword(s):  
Optimization Design ◽  
Stokes Equations ◽  
Aircraft Design ◽  
Sonic Boom ◽  
Free Form ◽  
Parameter Method ◽  
Far Field ◽  
Aerodynamic Optimization ◽  
Optimization System ◽  
Design Variables

It is key points to improve the aerodynamic efficiency and decrease the sonic-boom intensity for the supersonic aircraft design. Sonic-boom prediction method with high precision combining the near-field sonic-boom prediction based on Reynolds-Averaged Navier-Stokes equations and the far-field sonic-boom prediction based on waveform parameter method is firstly established. Then the gradient of sonic boom with respect to the design variables is calculated by the finite difference method and is combined with the gradient of the aerodynamic object by the discrete adjoint technique, acting as the gradient of the weighed object function. Assembling two gradients, the optimization system couples Free Form Deform method、the dynamic mesh technique based on Inverse Distance Weighting interpolation method、the gradient-based optimization algorithm based on the sequential quadratic programming. Using the aerodynamic optimization system considering the sonic boom intensity, the paper conducts a nose angle deflection optimization design and an elaborate aerodynamic optimization including huge design variables and constraints on a supersonic business jet, while the optimization objects are the weighed object and the supersonic cruise drag coefficient. The results show that the nose is deflected downward and the shock wave pattern is changed, leading to a lower far-field maximum overpressure; the drag is decreased by 15.8 counts, and the wing load is moved inboard, also, the pressure drag of the outer wing reduces. Meanwhile, the pressure distribution in the outer wing has a weaker adverse pressure gradient and a more gentle pressure recovery. After optimization, the low-drag and low-sonic boom configuration is obtained, which verified the effectiveness of the optimization system.

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