Multi-Fidelity Aerodynamic Optimization Using Treed Meta-Models

Author(s):  
Andrea Nelson ◽  
Juan Alonso ◽  
Thomas Pulliam
Author(s):  
Gilberto Bueno Luque Filho ◽  
Marco Aurélio Leonel Matunaga ◽  
João Luiz F. Azevedo

2020 ◽  
Vol 33 (3) ◽  
pp. 826-839 ◽  
Author(s):  
Peixun YU ◽  
Jiahui PENG ◽  
Junqiang BAI ◽  
Xiao HAN ◽  
Xiang SONG

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramazan Özkan ◽  
Mustafa Serdar Genç

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.


Author(s):  
Wei Wang ◽  
Jun Wang ◽  
Xiao-Pei Yang ◽  
Yan-Yan Ding

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.


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