2008
DOI: 10.1002/fld.1734
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An improved meshing method for shape optimization of aerodynamic profiles using genetic algorithms

Abstract: SUMMARYOne of the basic problems in fluid dynamics shape optimization is mesh generation. When analysis is performed using the finite element method, meshes of sufficient quality need to be constructed automatically. This work presents a structured meshing procedure that creates subdomains for generating good quality structured meshes in critical flow regions around aerodynamic profiles. Techniques of this nature enable other kinds of problems and geometries to be tackled. To demonstrate its capacity, it was a… Show more

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Cited by 10 publications
(6 citation statements)
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“…Thus, the meshing method used in this study was designed to accomplish three objectives: the robustness of the mesh generation process, the accuracy of the meshes, and an affordable mesh cost. Using this framework, a reliable meshing procedure for GA optimization problems was developed [19]. Instead of deforming the previous grid, a new mesh is reconstructed by dividing the domain into mesh blocks, which vary according to the geometry of the profile.…”
Section: Meshing Methodmentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, the meshing method used in this study was designed to accomplish three objectives: the robustness of the mesh generation process, the accuracy of the meshes, and an affordable mesh cost. Using this framework, a reliable meshing procedure for GA optimization problems was developed [19]. Instead of deforming the previous grid, a new mesh is reconstructed by dividing the domain into mesh blocks, which vary according to the geometry of the profile.…”
Section: Meshing Methodmentioning
confidence: 99%
“…The block boundaries starting from the wall were designed according to the slope of the wall in the same way as a previous study [19], but the boundaries opposite to the wall are now straight and independent of the airfoil. As the family of the mesh lines "parallel" to the flow direction is calculated by linear interpolation between the wall and its opposite straight frontier, these mesh lines become more similar to the wall as one moves towards it.…”
Section: Meshing Methodmentioning
confidence: 99%
“…However, these methods are not robust and often converge to local optima. Therefore, it is necessary to use slower but more reliable and robust algorithms, such as the genetic algorithms, simulated annealing algorithm, and neural network algorithm. Hybrid methods combining these 2 categories of algorithms have also been used .…”
Section: Overall Optimization Approachmentioning
confidence: 99%
“…In practice, a combination of both approaches may be used to better understand and design airfoils for specific working conditions [2]. Once the aforementioned approach is established, a numerical method is commonly employed, taking into account aspects such as: (a) The accurate determination of the physical aspects of the problem, that include whether the flow is compressible or incompressible, viscous or inviscid, subsonic or transonic, among others [1]; (b) The generation of the airfoil geometry, which is often achieved using curve parameterization methods [14] and (c) The discretization and mesh generation methods for numerical resolution, which are essential for obtaining accurate results [6,13].…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, when a specific optimal airfoil is required for a particular operating condition, the airfoil design can be formulated as an optimization problem. In this context, optimization algorithms have found extensive use in pure aerodynamic design [6]. Various techniques have been developed using this approach, ranging from single objective function optimization [12] to optimization with multiple (and sometimes conflicting) objective functions, incorporating multiple constraints that need to be simultaneously optimized [10].…”
Section: Introductionmentioning
confidence: 99%