Multi-Objective Evolutionary Structural Optimization Using Combined Static/Dynamic Control Parameters. Delivery Order 0007

2007 ◽  
Author(s):  
Ramana V. Grandhi ◽  
Woo-Young Kim ◽  
Mark A. Haney
Keyword(s):  
Structural Optimization ◽  
Dynamic Control ◽  
Control Parameters ◽  
Multi Objective ◽  
Evolutionary Structural Optimization

Multiobjective Evolutionary Structural Optimization Using Combined Static/Dynamic Control Parameters

AIAA Journal ◽  
2006 ◽  
Vol 44 (4) ◽  
pp. 794-802 ◽  
Author(s):  
Woo-Young Kim ◽  
Ramana V. Grandhi ◽  
Mark Haney
Keyword(s):  
Structural Optimization ◽  
Dynamic Control ◽  
Control Parameters ◽  
Evolutionary Structural Optimization

Bidirectional Evolutionary Structural Optimization with Regional Penalty Factor

2018 ◽  
Vol 30 (12) ◽  
pp. 2224
Author(s):  
Cong Wang ◽  
Changdong Zhang ◽  
Tingting Liu ◽  
Wenhe Liao
Keyword(s):  
Structural Optimization ◽  
Evolutionary Structural Optimization ◽  
Penalty Factor

scholarly journals Improved Bi-Direction Evolutionary Structural Optimization Method and Its Application

2021 ◽  
Vol 632 ◽  
pp. 042032
Author(s):  
Jialei Zhu ◽  
Xiaodong Liang ◽  
Shuai Shao ◽  
Yongdong Bi ◽  
Runze Miao
Keyword(s):  
Structural Optimization ◽  
Optimization Method ◽  
Evolutionary Structural Optimization

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

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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