A Parametric Study of Multimodality in Aerodynamic Shape Optimization of Wings

Streuber, Gregg M.; Zingg, David W.

doi:10.2514/6.2018-3637

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…The mesh generated for optimization contained 15.5 million cells. It was a complicated 3D aerodynamic optimization problem with relatively high dimensionality and multimodality [64]. 200 sample points were generated in the initial design space by the LHS method, and 500 sample points were to be updated as optimization progresses.…”

Section: Test On Benchmark Problemsmentioning

confidence: 99%

Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design

Zhang

Gao

Wang³

et al. 2023

International Journal of Aerospace Engineering

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For complicated aerodynamic design problems, the efficient global optimization method suffered from the defect of the incorrect portrayal of the design space, resulting in bad global convergence and efficiency performance. To this end, a Kriging-based global optimization method, named the Kriging-based space exploration method (KSE), was proposed in this paper. It selected multiple promising local minima and classified them into partially and fully explored minima in terms of the fitting quality of the surrogate model. Then, the partially explored minima would be furtherly exploited. During the local search, an enhanced trust-region method was adopted to make deep exploitation. By combining local and global searches, the proposed method could improve the fitting quality of the surrogate model and the optimization efficiency. The KSE was compared to other global surrogate-based optimization methods on 12 bound-constrained testing functions with 2 to 16 design variables and 2 aerodynamic optimization problems with 24 to 77 design variables. The results indicated that the KSE generally took fewer function evaluations to find the global optima or reach the target value in most test problems, holding better efficiency and robustness.

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Section: Test On Benchmark Problemsmentioning

confidence: 99%

Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design

Zhang

Gao

Wang³

et al. 2023

International Journal of Aerospace Engineering

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“…In ASO gradient based optimisation is most common, it offers fast and reliable convergence. SNOPT [46] is a widely used Sequential Quadratic Programming (SQP) code used in the ASO community [4,15,44,[47][48][49]. The adjoint method, developed by Pironneau [50] and popularised in ASO by Jameson [51], was a major breakthrough in the field of optimisation.…”

Section: Aerodynamic Shape Optimisationmentioning

confidence: 99%

“…Their use is restricted in ASO by computational expense. This consideration has limited their use to explorations of the modality of the aerodynamic design space [15,48,[53][54][55][56]. These studies provide mounting evidence that ASO design spaces are at least somewhat multi-modal.…”

Section: Aerodynamic Shape Optimisationmentioning

confidence: 99%

Structural Topology Optimisation with R-Snakes Volume of Solid

Taylor

Payot

Allen

et al. 2019

AIAA Scitech 2019 Forum

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A topologically flexible parameterisation method developed for aerodynamic optimisation is tested on a variety of 2 dimensional structural topology problems. The background to the restricted snakes volume of solid (RSVS) is explained. A topology optimisation framework is develloped using FreeFem++ as a linear elastic solver and differential evolution as the agent based optimiser. Validation of the analysis is presented as well as mesh convergence and impact studies. The work here is significant such that if a parameterisation method is capable of both aerodynamic and structural optimisation, the potential for multidisciplinary analysis arises. Structural topology optimisation of volume constrained agent-based optimisation, minimising deflection, has been run on four common benchmark cases; two short cantilever beams and two longer centrally loaded (MBB) beams. Results were compared to SIMP calculations made following using Sigmund's 99 line topology optimisation code [1]. RSVS solutions scored objective functions comparable to those found via SIMP in all cases with differences ranging from +40% to-5%. In the long run the combined capability of the RSVS in aerodynamics and structures offers the potential of the development of a general aero-structural topology optimisation framework using a single set of design variables.

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“…When planform variables are added to the design problem, multiple local minima do appear in the design space [23,[26][27][28]. However, it is crucial to distinguish mathematically rigorous local minima and physically significant local minima.…”

Section: Introductionmentioning

confidence: 99%

Aerostructural Design Exploration of a Wing in Transonic Flow

Bons

Martins

2020

Aerospace

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Multidisciplinary design optimization (MDO) has been previously applied to aerostructural wing design problems with great success. Most previous applications involve fine-tuning a well-designed aircraft wing. In this work, we broaden the scope of the optimization problem by exploring the design space of aerostructural wing design optimization. We start with a rectangular wing and optimize the aerodynamic shape and the sizing of the internal structure to achieve minimum fuel burn on a transonic cruise mission. We use a multi-level optimization procedure to decrease computational cost by 40%. We demonstrate that the optimization can transform the rectangular wing into a swept, tapered wing typical of a transonic aircraft. The optimizer converges to the same wing shape when starting from a different initial design. Additionally, we use a separation constraint at a low-speed, high-lift condition to improve the off-design performance of the optimized wing. The separation constraint results in a substantially different wing design with better low-speed performance and only a slight decrease in cruise performance.

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A Parametric Study of Multimodality in Aerodynamic Shape Optimization of Wings

Cited by 5 publications

References 36 publications

Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design

Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design

Structural Topology Optimisation with R-Snakes Volume of Solid

Aerostructural Design Exploration of a Wing in Transonic Flow

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