Response surface approach to aerodynamic optimization design of helicopter rotor blade

Sun, Hyosung; Lee, Soogab

doi:10.1002/nme.1391

Cited by 29 publications

(13 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This capability is being exploited in the rapidly-growing research field of Computational Fluid Dynamics (CFD) optimization which is being utilised across a range of areas including aerospace engineering [2,3], tribology [4], polymer moulding [5], ship design [6], vehicle aerodynamics [7][8][9][10], hospital ward ventilation [11] and jet pump design [12]. Although these examples demonstrate the versatility of CFD-based optimization, there is one aspect which can prove problematic: the presence of numerical noise in the CFD responses [10,[13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Dealing with numerical noise in CFD-based design optimization

Gilkeson¹,

Торопов²,

Thompson³

et al. 2014

Computers & Fluids

View full text Add to dashboard Cite

SUMMARYNumerical noise is an inevitable by-product of Computational Fluid Dynamics (CFD) simulations which can lead to challenges in finding optimum designs. This article draws attention to the issue, illustrating the difficulties it can cause for road vehicle aerodynamics simulations. Firstly a benchmark problem is used to assess a range of turbulence models and grid types. Large noise amplitudes up to 22% are evident for solutions computed on unstructured tetrahedral grids whereas computations on hexahedral and polyhedral grid structures exhibit substantially less noise. The Spalart Allmaras turbulence model is shown to be far less susceptible to noise levels than two other commonly-used models for this application.Secondly, multi-objective aerodynamic shape optimization is applied to a fairing for a practical road vehicle which is parameterised in terms of three design variables. Moving Least Squares (MLS) metamodels are constructed from 50 highfidelity CFD solutions for two objective functions. Subsequent optimization is successful for the first objective, however numerical noise levels in excess of 7% give rise to difficulties for the second one. A revision to the problem leads to success and the construction of a small Pareto Front. Further analysis underlines the inherent capability of MLS metamodels in dealing with noisy CFD responses.

show abstract

Section: Introductionmentioning

confidence: 99%

Dealing with numerical noise in CFD-based design optimization

Gilkeson¹,

Торопов²,

Thompson³

et al. 2014

Computers & Fluids

View full text Add to dashboard Cite

show abstract

“…This was coupled with the outcome of analysis of variance, which declared the adequacy of the built-up models at 95% confidence level, in the range of the factors under consideration. Furthermore, Sun et al (2005) studied the impact of design variables as well as the various design situations, for instance, objective function as well as restrictions on rotor enactment. The primary tools used were the response surface methodology rootedin the D-optimal 3-level factorials as well as the genetic algorithm with the intent of achieving the most favourable outcome for a specified objective function, embracing the penalty items of limitations.…”

Section: Introductionmentioning

confidence: 99%

Optimization of machining parameters of hard porcelain on a CNC machine by Taguchi-and RSM method

Agrawal¹,

Gaur²,

Kasdekar³

et al. 2018

Int. J. Eng. Sci. Tech

View full text Add to dashboard Cite

In order to build up a relationship between quality and productivity, the present work focuses an optimized approach to establishing the multi-objective machining parameters and mathematical models for Pressure and Voltage on CNC turning machine (SINUMERIK802D). The Pressure and Voltage seem to be known as quality issues; they are as well presumed to have direct association with productivity. In this study, minimization of response parameters has been identified by using design of experimental methods, Taguchi Analysis and Response surface methodology (RSM). The conduct of experiments was made by employing the Taguchi's L 27 Orthogonal array to design the experiment by considering spindle speed (SS), feed rate (FR), angle of cut (AOC) and depth of cut (DOC) as Machining parameters. The model for the Pressure and Voltage, as the function of response parameters, is obtained using the RSM. Finally, the result of developed mathematical model is examined by ANOVA. Experimental results indicate that the feed rate, angle of cut and depth of cut are the leading parameters that affect the Pressure (P). similarly for Voltage (V), all the cutting parameters (Spindle speed, feed rate, angle of cut and depth of cut) are found to be significant, which can be diminished when the significant factors were kept at the lower level, while other factors were kept at the highest level. On the Basis of analysis, it is found that both the optimization techniques predict the results in fair agreement.

show abstract

“…Existing literature shows that desirability or metaheuristic functions are normally used, the most common being the genetic algorithm (GA). Sun & Lee (Sun & Lee, 2005), present an approach which associates the RSM and GA with the optimal aerodynamic design of a helicopter rotor blade. The ACO is a metaheuristic, which has been successfully used to solve several combinatorial optimization problems.…”

Section: Introductionmentioning

confidence: 99%

“…Some options are offered for this kind of problem, such as the desirability function and the genetic GA used by some authors, such as Sun & Lee (Sun & Lee, 2005) or Abdul-Wahad & Abdo (AbdulWahad & Abdo, 2007). The literature shows that for many problems, the ant colony approach produces better results in terms of quality solutions and resolution speed, as compared to the GA.…”

Section: Introductionmentioning

confidence: 99%