Fast Buckling Analysis of Stiffened Composite Structures for Preliminary Aerospace Design
Predicting buckling in large-scale composite structures is hindered by the need for highly detailed Finite Element (FE) models, which are computationally expensive and impractical for early-stage design iterations. This study introduces a macromodelling buckling framework that reduces those models to plate-level size without sacrificing accuracy. An equivalent bending stiffness matrix is derived from strain–energy equivalence, rigorously retaining orthotropic in-plane terms, bending–extensional coupling, and—crucially—the eccentricity of compressive loads about an unsymmetrically stiffened mid-plane, effects overlooked by conventional Parallel-Axis smearing. These stiffness terms contribute to closed-form analytical solutions for homogeneous orthotropic plates, providing millisecond-level evaluations ideal for gradient-based design optimisation. The method is benchmarked against detailed FE simulations of panels with three to ten stringers under longitudinal and transverse compression, showing less than 5% deviation in critical load prediction. Its utility is demonstrated in the sizing optimisation of the upper cover of a scaled Airbus A330 composite wing-box, where the proposed model explores the design space in minutes on a standard workstation, orders of magnitude faster than full FE analyses. By combining analytical plate theory, enhanced smearing, and rapid optimisation capability, the framework provides an accurate, ultra-fast tool for buckling analysis and the preliminary design of large-scale stiffened composite structures.
Authors
- Dimitrios G. Stamatelos (ORCID: https://orcid.org/0000-0002-7294-5201)
- G. Labeas
Institutions
- University of Patras (GR)
- Hellenic Air Force (GR)
Publication Details
- Journal
- Aerospace
- Published
- 2025-08-14
- DOI
- https://doi.org/10.3390/aerospace12080726
- Citations
- 1
- Primary Topic
- Composite Structure Analysis and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.86