journal article·2024-06Open access

Multi-objective optimization of sandwich structures for reinforcing composite fuselages

Alejandro Eduardo Albanesi, Nahuel José Volpe, Federico Langhi, Víctor Daniel Fachinotti

Abstract

This study introduces a simulation-based optimization approach that combines a multi-objective genetic algorithm and the finite element method to design sandwich structures to reinforce composite fuselages. The sandwich structure has been parametrized with a set of mixed integer-continuous variables representing the polymer core thickness, the number and weight of laminated fiberglass layers, and size and position of the structure. Automatic scripting builds the geometry of the structure, then mounts it in the fuselage, and finally creates a conformal mesh. During the optimization, each reinforced fuselage is subjected to several load cases specified by the CS-22 EASA design standard, determining the worst load condition. Two objectives were considered: increasing the reinforced fuselage’s minimum fiber stress safety factor for improved safety and reducing the number of layers of the sandwich structure to minimize manufacturing costs. Structural constraints were the mass of the sandwich structure and buckling and flexo-torsional deformation of the reinforced fuselage. Results show an efficient material arrangement due to the reduced number of layers in the sandwich structure and a stress safety factor surpassing that set by the standard. Finally, the reinforcement of a glider fuselage to incorporate a retractable electric propulsion system is presented as a real-world industrial application.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Topology Optimization in Engineering · Advanced Multi-Objective Optimization Algorithms · Composite Structure Analysis and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

CIMEC Centro de Investigación de Métodos Computacionales, CONICET Santa Fe, Santa Fe, Argentina

Funding

Consejo Nacional de Investigaciones Científicas y Técnicas · Agencia Santafesina de Ciencia, Tecnología e Innovación · National Technological University of Argentina

References (27)

Show source-provided references
1. 10.1007/s10443-010-9180-910.1007/s10443-010-9180-9 ↗
2. 10.1177/109963621348700410.1177/1099636213487004 ↗
3. 10.1177/1099636222111541810.1177/10996362221115418 ↗
4. 10.1007/s00158-009-0413-110.1007/s00158-009-0413-1 ↗
5. 10.1007/s11081-008-9077-810.1007/s11081-008-9077-8 ↗
6. 10.1177/109963621036920510.1177/1099636210369205 ↗
7. 10.1007/s42405-019-00172-710.1007/s42405-019-00172-7 ↗
8. 10.1177/109963622096227810.1177/1099636220962278 ↗
9. 10.1007/s13272-022-00628-910.1007/s13272-022-00628-9 ↗
10. 10.1109/4235.99601710.1109/4235.996017 ↗
11. Deb K · 2001
12. 10.1177/109963621453151610.1177/1099636214531516 ↗
13. 10.1007/s00158-016-1559-210.1007/s00158-016-1559-2 ↗
14. 10.1177/109963622199389110.1177/1099636221993891 ↗
15. 10.1177/109963622092765010.1177/1099636220927650 ↗
16. EASA · 2018
17. CENTRAIR · 2014
18. Megson T · 2010
19. PARG · 2013
20. 10.1007/s00158-011-0666-310.1007/s00158-011-0666-3 ↗
21. Bergeaud V · 2010
22. EDF Electricité de France · 2019
23. EDF Electricité de France · 2022
24. 10.1016/j.compstruct.2017.10.05110.1016/j.compstruct.2017.10.051 ↗
25. 10.1007/s00158-020-02518-210.1007/s00158-020-02518-2 ↗
26. Barbero EJ · 2011
27. Kudawoo AD · DST, DKTG and Q4G · 2018 · 61