A Study Based on the AIAA Aerodynamic Design Optimization Discussion Group Test Cases

LeDoux, Stephen T.; Young, David P.; Fugal, Spencer R.; Elliott, J.; Kamenetskiy, Dmitry S.; Melvin, Robin G.; Huffman, William P.

doi:10.2514/6.2015-1717

Cited by 6 publications

(5 citation statements)

References 11 publications

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“…Meheut [20] compared a number of optimised aerofoil shapes from six different institutes [4,5,7,13,14,16] with the same flow solver. This produced a range of final drag results (all similar to values declared in the original publications) ranging from 32 to 86 drag counts on a mesh with 1024 points around the aerofoil.…”

Section: B Previous Workmentioning

confidence: 99%

“…Due to the large range of factors influencing the results it is difficult to isolate contribution of the parameterisation method from these previous studies. For example, the choice of flow solver [16] or optimisation algorithm [14] has been shown to have a significant impact on the optimisation results for this case. For this reason this work tests this case with a large range of parameterisation methods under the same optimisation framework across a range of design variables.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Masters

Poole

Taylor

et al. 2016

54th AIAA Aerospace Sciences Meeting

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Department of Aerospace Engineering, University of BristolThis paper presents an investigation into the influence of shape parameterisation and dimensionality on the optimisation of a benchmark case described by the AIAA Aerodynamic Design Optimisation Discussion Group. This problem specifies the drag minimisation of a NACA0012 under inviscid flow conditions at M = 0.85 and α = 0 subject to the constraint that local thickness must only increase. The work presented here applies six different shape parameterisation schemes to this optimisation problem with between 4 and 40 design variables. The parameterisation methods used are: Bèzier Surface FFD; B-Splines; CSTs; Hicks-Henne bump functions; a Radial Basis Function domain element method (RBF-DE) and a Singular Value Decomposition (SVD) method. The optimisation framework used consists of a gradient based SQP optimiser coupled with the SU 2 adjoint Euler solver which enables the efficient calculation of the design variable gradients. Results for the all the parameterisation methods are presented with the best results for each method ranging between 25 and 56 drag counts from an initial value of 469. The optimal result was achieved with the B-Spline method with 16 design variables. A further validation of the results is then presented and the presence of hysteresis is explored.

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Section: B Previous Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Masters

Poole

Taylor

et al. 2016

54th AIAA Aerospace Sciences Meeting

View full text Add to dashboard Cite

show abstract

“…Many of these works found that single design point aerodynamic optimization lead to results with poor off-design performance and that multiple flight conditions must be considered to lead to a practical and robust design [24,28]. More recently, several optimization cases featuring multiple design conditions were also defined and solved [18,25]. These benchmark cases have been successful in getting practitioners from academia and industry to solve the same problem.…”

Section: Introductionmentioning

confidence: 99%

Undeflected Common Research Model (uCRM): An Aerostructural Model for the Study of High Aspect Ratio Transport Aircraft Wings

Brooks

Kenway

Martins

2017

35th AIAA Applied Aerodynamics Conference

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Since its introduction, the NASA Common Research Model (CRM) has served as a useful aerodynamic benchmark for CFD-based drag prediction and aerodynamic design optimization. The model was originally conceived as a purely aerodynamic benchmark and as such, the wing geometry corresponds to the deflected shape at the nominal 1 g flight condition. There has been growing interest in extending this model for aeroelastic studies. Due to its predefined deflection, the model is not suitable for aeroelastic analysis and design. To address this issue, we define an undeflected Common Research Model (uCRM), which includes the outer mold line geometry of the undeflected wing and the corresponding internal wingbox structure. The developed aeroelastic model achieves the flying shape of the CRM under the nominal flight condition. The topology of the wingbox is designed to be similar to that of a Boeing 777. The jig shape was obtained through an inverse design procedure where the objective was to minimize the difference between the 1 g aerostructurally deflected shape and the CRM. The original CRM has an aspect ratio of 9, so we refer to this model as the uCRM-9. Additionally, since modern transport aircraft are trending toward higher aspect ratio wing designs to reduce induced drag, and therefore fuel burn, there is a need for a higher aspect ratio variant of this model to assess next-generation wings. This variant, the uCRM-13.5, has a larger aspect ratio of 13.5 and is defined through a multipoint aerostructural optimization subject to buffet onset constraints. These models provide a publicly available benchmark for aeroelastic wing analysis and design optimization studies.

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“…As such, the AIAA Aerodynamic Design Optimization Discussion Group (ADODG) a was formed. As part of this, a number of inviscid and viscous aerofoil and wing optimization cases were suggested, with a number of research groups presenting results; see [13][14][15][16][17][18][19][20] for example.…”

Section: Introductionmentioning

confidence: 99%

Global Optimization of Multimodal Aerodynamic Optimization Benchmark Case

Poole

Allen

Rendall

2017

35th AIAA Applied Aerodynamics Conference

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. An investigation into a multimodal aerodynamic optimization benchmark case using an approximate global optimization approach is presented. A new benchmark case of the AIAA Aerodynamic Design Optimization Discussion Group that involves the drag minimization of a rectangular NACA0012 wing subject to lift and root bending moment, as well as other geometric constraints, that is currently believed to be multimodal has been suggested. In this paper, optimization of that case using a constrained populationbased global optimization framework is presented, with three independent runs of the optimizer (each with different starting locations) having been performed. The runs are all coarsely-converged to give approximately converged solutions such that rapid run-times can be achieved and used to demonstrate any pitfalls that may be encountered when using a gradient-based optimizer. All three of the runs converged onto drag values close to the theoretical optimum, however with substantially different final shapes. This likely indicates the presence of a flat optimum region within the design space, where a substantial number of wing shapes are able to obtain the theoretical optimum span loading.

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A Study Based on the AIAA Aerodynamic Design Optimization Discussion Group Test Cases

Cited by 6 publications

References 11 publications

Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Impact of Shape Parameterisation on Aerodynamic Optimisation of Benchmark Problem

Undeflected Common Research Model (uCRM): An Aerostructural Model for the Study of High Aspect Ratio Transport Aircraft Wings

Global Optimization of Multimodal Aerodynamic Optimization Benchmark Case

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