Airfoil Aerodynamic Optimization Design Using Ensemble Learning Surrogate Model-Reference-Cited by-同舟云学术

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Airfoil Aerodynamic Optimization Design Using Ensemble Learning Surrogate Model

Published:2024-11 Issue:6 Volume:37 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Wang Shu¹,Xu Qinzheng²^ORCID,Wei Nan³

Affiliation:

1. Associate Professor, College of Information Science and Engineering, Northeastern Univ., Shenyang, Liaoning 110819, China.

2. Master’s Student, College of Information Science and Engineering, Northeastern Univ., Shenyang, Liaoning 110819, China (corresponding author). ORCID: .

3. Master’s Student, College of Information Science and Engineering, Northeastern Univ., Shenyang, Liaoning 110819, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JAEEEZ.ASENG-5410

Reference37 articles.

1. Voronoi diagrams—a survey of a fundamental geometric data structure

2. Cook, P. H., M. A. McDonald, and M. C. P. Firmin. 1979. Aerofoil RAE 2822: Pressure distributions, and boundary layer and wake measurements. AGARD report ar 138, 47. Neuilly sur Seine, France: AGARD.

3. A fast and elitist multiobjective genetic algorithm: NSGA-II

4. An airfoil shape optimization technique coupling PARSEC parameterization and evolutionary algorithm

5. Bezier-PARSEC: An optimized aerofoil parameterization for design

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