Three-Dimensional Aerodynamic Shape Optimization Using Genetic and Gradient Search Algorithms

Foster, Norman F.; Dulikravich, George S.

doi:10.2514/2.3189

Cited by 78 publications

(28 citation statements)

References 9 publications

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“…They have successfully been applied in engineering electromagnetics [35][36][37][38], in mechanical engineering [39,40], and been coupled with turbulent flows in earlier papers, notably in metallurgy and manufacturing processes [41][42][43]. A GA works with a population of candidate solutions which are called individuals.…”

Section: Determination Of the Laser Beam Dire-ctions By Applying A Gementioning

confidence: 99%

Genetic Algorithm Approach and Experimental Confirmation of a Laser-Based Diagnostic Technique for the Local Thermal Turbulence in a Hot Wind Tunnel Jet

Pemha¹,

Nyobe²

2011

PIER B

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Abstract-This paper is devoted to a laser-based diagnostic technique described as a method for solving an applied inverse problem in turbulent media using laser beam propagation. This problem consists of extracting local information about temperature fluctuations inside a hot turbulent jet of air, from the luminous photodiode trace produced by a laser beam, after having traversed the jet. A genetic algorithm is implemented in order to calculate the optimized laser beam directions corresponding to the whole luminous trace. An approximated ray equation which is proved from the geometrical optics is solved numerically by using those directions and enables to determine the variance of temperature fluctuations along the whole path of the laser beam. A good agreement coming from the comparison between the results obtained and the published experimental data proves the validity of the method.

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Section: Determination Of the Laser Beam Dire-ctions By Applying A Gementioning

confidence: 99%

Genetic Algorithm Approach and Experimental Confirmation of a Laser-Based Diagnostic Technique for the Local Thermal Turbulence in a Hot Wind Tunnel Jet

Pemha¹,

Nyobe²

2011

PIER B

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“…With respect to the method proposed in Reference [30] as well as other published works in aerodynamics [31,32], it should become clear that the hybridization with hill-climbing, i.e. any optimization method, which could further improve the current best individual at each generation, is beyond the scope of this paper.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical distributed metamodel‐assisted evolutionary algorithms in shape optimization

Karakasis

Koubogiannis

Giannakoglou

2006

Numerical Methods in Fluids

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SUMMARYIn aerodynamic shape optimization, the availability of multiple evaluation models of different precision and hence computational cost can be efficiently exploited in a hierarchical evolutionary algorithm. Thus, in this work the demes of a distributed evolutionary algorithm are ordered in levels, with each level employing a different flow analysis method, giving rise to a hierarchical distributed scheme. The arduous task of exploring the design space is undertaken by demes consisting the lower hierarchy level, which use a lowcost flow analysis tool, namely a viscous-inviscid flow interaction method. Promising solutions are directed towards the higher level, where these are further evolved based on a high precision/cost evaluation tool, viz. a Navier-Stokes equations solver. The final, optimal solution is obtained from the highest hierarchy level. At each level, metamodels, trained on-line on the outcome of evaluations with the level's analysis tool, are used. The role of metamodels is to allow a parsimonious use of computational resources by filtering the poorly performing individuals in each deme. The entire algorithm has been implemented so as to take advantage of a parallel computing system. The efficiency and effectiveness of the proposed hierarchical distributed evolutionary algorithm have been assessed in the design of a transonic isolated airfoil and a compressor cascade. Remarkable superiority over the conventional evolutionary algorithms has been monitored.

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“…Also, there has been growing interest in the use of global optimization methods in a wide range of design problems, as well as aerodynamic shape optimization. Hybrid optimization methods based on genetic and gradient search algorithms have been applied to wing planform [3]. Anderson et al [1] applied Pareto genetic algorithms (GAs) to the multiobjective optimization of missile aerodynamic shape design.…”

mentioning

confidence: 99%

“…Here, a normal distribution is used to represent the design space efficiently, which was originally proposed by Arakawa et al in binary-coded Adaptive Range Genetic Algorithms for single objective problem. [3] Oyama et al extended the binary-coded to real-coded ARGAs [5] for design optimization. The ARMOGA is extended to MO optimization problems to treat multiple solutions and to maintain the diversity of solutions to collect multiple non-dominated solutions, unlike single objective problems.…”

mentioning

confidence: 99%

An Airfoil Shape Design using the Real-Coded Adaptive Range Multi-Objective Genetic Algorithm and PARSEC Method

Jung¹,

Filho²,

Madeira³

2016

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Three-Dimensional Aerodynamic Shape Optimization Using Genetic and Gradient Search Algorithms

Cited by 78 publications

References 9 publications

Genetic Algorithm Approach and Experimental Confirmation of a Laser-Based Diagnostic Technique for the Local Thermal Turbulence in a Hot Wind Tunnel Jet

Genetic Algorithm Approach and Experimental Confirmation of a Laser-Based Diagnostic Technique for the Local Thermal Turbulence in a Hot Wind Tunnel Jet

Hierarchical distributed metamodel‐assisted evolutionary algorithms in shape optimization

An Airfoil Shape Design using the Real-Coded Adaptive Range Multi-Objective Genetic Algorithm and PARSEC Method

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