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This research investigates the buckling strength of thin-walled composite structures with various hole shapes and laminates under mechanical and thermal loads using finite element analysis and machine learning. A parametric study optimizes material and structural parameters to enhance resilience, while machine learning techniques predict optimal critical buckling loads. The study highlights the effectiveness of combining finite element methods with machine learning for advanced analysis in composite enginee

Author

sarv

Language

EN