Multidisciplinary Wing Layout Optimisation

Studies to enhance the static and dynamic characteristics of aircraft often lead to increased weight, resulting in higher power demand and fuel consumption, which can reduce flight time. This study formulates two optimisation problems aimed at improving the wing’s static and dynamic properties without adding weight. The optimisation focused on the positioning of the wing’s spar and rib structures, with static and dynamic properties defined as objective functions. The first objective was to reduce wing displacement and increase its first natural frequency, while the second aimed to raise the ratio of the wing’s first torsional frequency to its first bending frequency to enhance flutter speed. A parametric wing model was created, and analyses were performed in ANSYS, automated with a Python script. A surrogate model was built using Modified Latin Hypercube Sampling (MLHS), and optimization was conducted using multi-objective genetic algorithms and genetic algorithms. After optimization, the wing’s natural frequency increased by 4 %, displacement decreased by 5.7 %, and the torsional-to-bending frequency ratio improved by 6.61 %.

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Publication Details

Journal
Defence Science Journal
Published
2025-03-24
DOI
https://doi.org/10.14429/20144
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Multidisciplinary Wing Layout Optimisation

Necmettin Kaya, Hakan Demir
Defence Science Journal
Advanced Manufacturing and Logistics Optimization
article

Multidisciplinary Wing Layout Optimisation

Necmettin Kaya, Hakan Demir
article en

Abstract

Studies to enhance the static and dynamic characteristics of aircraft often lead to increased weight, resulting in higher power demand and fuel consumption, which can reduce flight time. This study formulates two optimisation problems aimed at improving the wing’s static and dynamic properties without adding weight. The optimisation focused on the positioning of the wing’s spar and rib structures, with static and dynamic properties defined as objective functions. The first objective was to reduce wing displacement and increase its first natural frequency, while the second aimed to raise the ratio of the wing’s first torsional frequency to its first bending frequency to enhance flutter speed. A parametric wing model was created, and analyses were performed in ANSYS, automated with a Python script. A surrogate model was built using Modified Latin Hypercube Sampling (MLHS), and optimization was conducted using multi-objective genetic algorithms and genetic algorithms. After optimization, the wing’s natural frequency increased by 4 %, displacement decreased by 5.7 %, and the torsional-to-bending frequency ratio improved by 6.61 %.

Defence Science JournalVol. 75(2)
Bursa Uludağ Üni̇versi̇tesi̇ (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 93%
Advanced Manufacturing and Logistics Optimization
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