Aerofoil Design Variable Extraction for Aerodynamic Optimization

Poole, Daniel J; Allen, Christian B; Rendall, Thomas

doi:10.2514/6.2013-2705

Cited by 13 publications

(8 citation statements)

References 54 publications

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“…63,64 To satisfy further the requirement for efficiency, and make the method generally applicable to aerofoil optimization, the authors developed a method to derive a set of orthogonal fundamental shape design variables using a singular value decomposition (SVD) approach. 55,56,65 These design variables are shape perturbation modes, extracted via SVD of a perturbation matrix constructed from an aerofoil library, see; 55, 56, 65 perturbations of the first three geometric design variables are shown in figure 1. These are the design variables used here for efficient aerodynamic shape optimization.…”

Section: Va Geometry Parameterization and Mesh Controlmentioning

confidence: 99%

Comparison of Local and Global Constrained Aerodynamic Shape Optimization

Poole

Allen

Rendall

2014

32nd AIAA Applied Aerodynamics Conference

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A comparison is presented of gradient-based and agent-based optimization schemes, applied to constrained aerodynamic shape optimization in two dimensions. The optimizers developed are a feasible sequential quadratic programming (FSQP) gradient-based algorithm and a modified gravitational search algorithm (GSA), extended to include a new separation-sub-swarm (3S) constraint handling method. Lift constrained drag minimization of the NACA 0012 and RAE 2822 aerofoils at different flow conditions are presented, and results show that the constraint handling global search algorithm is able to locate better optima than the gradient-based scheme, although at the cost of more objective function evaluations. The design variables used here are derived using a mathematical decomposition, which has produced a set of orthogonal design variables that are very efficient, and as few as six are required to obtain shock-free solutions using the global search algorithm.

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Section: Va Geometry Parameterization and Mesh Controlmentioning

confidence: 99%

Comparison of Local and Global Constrained Aerodynamic Shape Optimization

Poole

Allen

Rendall

2014

32nd AIAA Applied Aerodynamics Conference

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“…Deformations may also be calculated using a modal decomposition of a geometry library [39], and applied using a control point method [40], or as shape changes directly. When considering aerofoils, public libraries of well over 1000 may be formed, representing a wealth of design experience aimed at the problem in hand.…”

Section: Descriptive Function Methodsmentioning

confidence: 99%

“…A standard test [62,40] of a parameterisation scheme focusses on the capability to successfully recover an existing aerofoil geometry using as few design here is calculated after a resplining procedure using an identical method, after which the RMS error is calculated following equation (13) where N is the number of generated surface points, y t (x i ) is the y coordinate of the point on the target surface at x i and y(x i ) is the point on the generated surface.…”

Section: Comparison With Other Parameterisationsmentioning

confidence: 99%

A volumetric geometry and topology parameterisation for fluids-based optimisation

et al. 2017

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. A volumetric geometry and topology parameterisation for fluids-based optimisation. Computers and Fluids, 148,[137][138][139][140][141][142][143][144][145][146][147][148][149][150][151][152][153][154][155][156] University of Bristol -Explore Bristol Research General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. AbstractA new geometry and topology parameterisation method is presented which is based on creating a parameterisation grid of cells and reconstructing surfaces from the fraction of the cell volume defined to be solid, with the volume fractions acting as design variables. This method is able to include topological changes alongside fine-level geometric control, and therefore offers a significant increase in flexibility. In this work, the geometric capabilities of the method are confirmed by successfully constructing a variety of surfaces, using both arbitrary object outlines and aerofoil geometries. The method is then used in a range of optimisation problems covering the design of a coastal defence, increasing fluid damping within an oscillating box by the addition of baffles, and design of a multi-body configuration for minimum drag in supersonic flow. These problems demonstrate the benefits of a parameterisation for fluids modelling that is capable of topological changes and which can be used with global search as well as gradient-based methods.

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“…Masters et al [2] compared seven different airfoil parameterization schemes by considering the geometric shape recovery of over 2000 airfoils. In their comparison, they included class-shape transformations [3], Hicks-Henne bump functions [4], singular-value decomposition (airfoil modes) [5,6,7,8], B-splines, radial basis function domain elements, Bézier surfaces, and the parameterized sections method. They concluded that the airfoil modes parameterization was the most efficient approach.…”

Section: Introductionmentioning

confidence: 99%

“…The modes for the subsonic regime are based on 1172 existing airfoils taken from the University of Illinois Urbana-Champaign (UIUC) airfoil database [22], while the modes for the transonic regime are based on the NASA SC(2) airfoils. Unlike approaches that use full-airfoil modes [2,5,6,7,8], we compute separate camber and thickness modes to parameterize the airfoils because they are more suitable for optimization problems with thickness constraints. The design space contains all the existing airfoils that are used for the decomposition, and we use a strategy to exclude abnormal airfoils that would never be desirable.…”

Section: Introductionmentioning

confidence: 99%

A data-based approach for fast airfoil analysis and optimization

Bouhlel

Martins

2018

2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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Airfoils are of great importance in aerodynamic design, and various tools have been developed to evaluate and optimize their performance. Existing tools are usually either accurate or efficient, but not both. This paper presents a tool that can analyze airfoils in both subsonic and transonic regimes in about one hundredth of a second, and optimize airfoil shapes in a few seconds. We use camber and thickness mode shapes derived from over one thousand existing airfoils to parameterize the airfoil shape, which reduces the number of design variables. More than one hundred thousand RANS evaluations associated with different airfoils and flow conditions are used to train a surrogate model that combines gradient-enhanced kriging, partial least squares, and mixture of experts. These surrogate models provide fast aerodynamic analysis and gradient computation, which are coupled with a gradient-based optimizer to perform rapid airfoil shape design optimization. When comparing the surrogate-based optimization with optimization based on direct RANS evaluations, the largest differences in minimum C d are 0.04 counts for subsonic cases and 2.5 counts for transonic cases. This approach opens the door for interactive airfoil analysis and design optimization using any modern computer or mobile device. ct = joint camber and thickness f = full airfoil t = airfoil thickness

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Aerofoil Design Variable Extraction for Aerodynamic Optimization

Cited by 13 publications

References 54 publications

Comparison of Local and Global Constrained Aerodynamic Shape Optimization

Comparison of Local and Global Constrained Aerodynamic Shape Optimization

A volumetric geometry and topology parameterisation for fluids-based optimisation

A data-based approach for fast airfoil analysis and optimization

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