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@article{205596,
        author = {M.Deepthi},
        title = {FATIGUE ANALYSIS OF COMPOSITE MATERIAL COMPONENT USING FEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {9166-9169},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205596},
        abstract = {Composite materials are widely used in aerospace, automotive, and structural engineering applications because of their high strength-to-weight ratio and durability. However, understanding their fatigue behavior under repeated cyclic loading is essential for ensuring structural reliability and safety. This study investigates the fatigue performance of composite material components using Computer-Aided Design (CAD), Finite Element Method (FEM), and Artificial Intelligence (AI)-based predictive techniques. Finite element analysis is performed in ANSYS to evaluate stress distribution, deformation characteristics, and fatigue life under varying loading conditions. Fatigue assessment is carried out using S-N curve analysis, while AI models are employed to enhance prediction accuracy and reduce computational effort. The results indicate that composite materials exhibit superior fatigue resistance compared to conventional materials, although failure mechanisms vary with stress levels and loading conditions. The integration of FEM and AI improves the efficiency of fatigue life prediction and supports the optimization of composite component design. The study contributes to the development of reliable, lightweight, and high-performance composite structures for advanced engineering applications.},
        keywords = {Composite Materials, Fatigue Analysis, Finite Element Method (FEM), ANSYS, Artificial Intelligence (AI), S-N Curve, CAD/CAM.},
        month = {June},
        }