The Myth of the High-Order-Lifting-Surface Method

2005 ◽  
Vol 42 (2) ◽  
pp. 575-575 ◽  
Author(s):  
William P. Rodden
Keyword(s):  
High Order ◽  
Surface Method ◽  
Lifting Surface

Optimization of Wind Turbine Blades Using Lifting Surface Method and Genetic Algorithm

2011 ◽  
Author(s):  
Xin Shen ◽  
Xiao-cheng Zhu ◽  
Zhao-hui Du
Keyword(s):  
Genetic Algorithm ◽  
Design Method ◽  
Turbine Blades ◽  
Optimization Method ◽  
Efficient Design ◽  
Wind Turbine Blades ◽  
Surface Method ◽  
Lifting Surface ◽  
Horizontal Axis Wind Turbines ◽  
Wake Model

This paper describes an optimization method for the design of horizontal axis wind turbines using the lifting surface method as the performance prediction model and a genetic algorithm for optimization. The aerodynamic code for the design method is based on the lifting surface method with a prescribed wake model for the description of the wake. A micro genetic algorithm handles the decision variables of the optimization problem such as the chord and twist distribution of the blade. The scope of the optimization method is to achieve the best trade off of the following objectives: maximum of annual energy production and minimum of blade loads including thrust and blade rood flap-wise moment. To illustrate how the optimization of the blade is carried out the procedure is applied to NREL Phase VI rotor. The result shows the optimization model can provide a more efficient design.

Iterative Lifting Surface Method for Thick Bladed Hovering Helicopter Rotors

1981 ◽  
Vol 18 (6) ◽  
pp. 417-424 ◽  
Author(s):  
K. Rajarama Shenoy ◽  
Robin B. Gray
Keyword(s):  
Helicopter Rotors ◽  
Surface Method ◽  
Lifting Surface

Adaptive anisotropic response surface method based on univariate dimension-reduction model and its high-order revision

2020 ◽  
Vol 37 (9) ◽  
pp. 3097-3125
Author(s):  
Wenliang Fan ◽  
Wentong Zhang ◽  
Min Li ◽  
Alfredo H.-S. Ang ◽  
Zhengliang Li
Keyword(s):  
Dimension Reduction ◽  
Response Surface ◽  
Response Surface Method ◽  
High Order ◽  
Practical Implementation ◽  
Content Type ◽  
Reduction Model ◽  
Surface Method ◽  
Univariate Function ◽  
Improving Accuracy

Purpose Based on univariate dimension-reduction model, this study aims to propose an adaptive anisotropic response surface method (ARSM) and its high-order revision (HARSM) to balance the accuracy and efficiency for response surface method (RSM). Design/methodology/approach First, judgment criteria for the constitution of a univariate function are derived mathematically, together with the practical implementation. Second, by combining separate polynomial approximation of each component function of univariate dimension-reduction model with its constitution analysis, the anisotropic ARSM is proposed. Third, the high-order revision for component functions is introduced to improve the accuracy of ARSM, namely, HARSM, in which the revision is also anisotropic. Finally, several examples are investigated to verify the accuracy, efficiency and convergence of the proposed methods, and the influence of parameters on the proposed methods is also performed. Findings The criteria for constitution analysis are appropriate and practical. Obtaining the undetermined coefficients for every component functions is easier than the existing RSMs. The existence of special component functions is useful to improve the efficiency of the ARSM. HARSM is helpful for improving accuracy significantly and it is more robust than ARSM and the existing quadratic polynomial RSMs and linear RSM. ARSM and HARSM can achieve appropriate balance between precision and efficiency. Originality/value The constitution of univariate function can be determined adaptively and the nonlinearity of different variables in the response surface can be treated in an anisotropic way.

Induced Drag Calculation by Numerical Lifting Surface Method

1997 ◽  
Vol 34 (2) ◽  
pp. 257-259
Author(s):  
Masami Ichikawa ◽  
Akira Matsuda
Keyword(s):  
Induced Drag ◽  
Surface Method ◽  
Lifting Surface
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