RESEARCH PAPER
Inverse Method for Material Characterization of a UAV Composite Wing Based on FEM and Dynamic Response
1
Wrocław University of Science and Technology Faculty of Mechanical Engineering, Poland
Submission date: 2025-05-06
Final revision date: 2025-05-21
Acceptance date: 2025-06-18
Online publication date: 2025-06-19
Publication date: 2025-06-19
Corresponding author
Artur Kierzkowski
Wrocław University of Science and Technology Faculty of Mechanical Engineering, Poland, 27 Wybrzeże Wyspiańskiego st., 50370, Wroclaw, Poland
Wrocław University of Science and Technology Faculty of Mechanical Engineering, Poland, 27 Wybrzeże Wyspiańskiego st., 50370, Wroclaw, Poland
Eksploatacja i Niezawodność – Maintenance and Reliability 2026;28(1):207312
HIGHLIGHTS
- Inverse identification method for composite materials based on dynamic response analysis.
- Integration of experimental and numerical modal analysis for material property estimation.
- Validated method applicable to UAV composite structures.
- Non-destructive approach enabling accurate FEM-based material calibration.
KEYWORDS
Modal AnalysisUnmanned Aerial VehiclesComposite StructuresMaterial CharacterizationGround Vibration Test
TOPICS
ABSTRACT
This work introduces a method for the inverse identification of composite material properties using dynamic response data and finite element modelling. The methodology combines numerical modal analysis, Design of Experiments (DoE), Response Surface Methodology, and a Multi-Objective Genetic Algorithm (MOGA) to determine material parameters without destructive testing. The approach was applied to a UAV composite wing, achieving high correlation between simulated and experimental modal characteristics, with natural frequencies deviations below 2%. Variations between the identified parameters and reference data are linked to inherent inconsistencies in composite manufacturing and the operational condition of the tested structure. Nevertheless, the proposed method proves to be a reliable and non-invasive tool for estimating mechanical properties, enhancing the predictive capabilities of numerical models. Its adaptability makes it a promising solution for future applications in structural health monitoring, damage assessment, and optimization of aerospace composite structures.
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