Analysis and Optimization of the Mechanical Properties of Composite Materials for Advanced Engineering Applications
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Due to the unique properties of composite materials, they have become increasingly popular for various engineering applications. Their demand has increased in modern engineering. Due to their high strength-to-weight ratio, stiffness, corrosion resistance, fatigue performance and design flexibility, they have been quickly adopted for advanced engineering applications in aerospace, automotive, marine, energy, civil, biomedical, etc. The mechanical behavior of composites is a function of several interacting parameters, such as type of reinforcement, fiber volume fraction, fiber orientation, matrix properties, interfacial adhesion, manufacturing conditions, and defects. The analysis and optimization of the mechanical properties of composite materials, particularly fiber-reinforced polymer composite materials, is investigated in this study. The tensile strength, tensile modulus, flexural strength, flexural modulus, impact resistance and failure behaviour is studied. The research involves a methodology using experimental characterization, design of experiments, response surface methodology, statistics, and FE simulation. Advanced methods like machine-learning techniques are also being discussed as tools to predict mechanical performance and optimize the material. The proposed framework regards fiber volume fraction, fiber orientation, curing conditions and manufacturing parameters as important design variables. Statistical techniques like ANOVA (Analysis of Variance) and regression modeling can be used to find out the significance of individual factors and their interactions. A multi-response approach in which strength, stiffness, impact resistance, weight and manufacturability are being optimized simultaneously. The analysis reveals that the fiber orientation and fiber volume fraction are among the most influential parameters affecting the mechanical performance of fiber-reinforced composites. Nonetheless, greater reinforcement loading may lead to processing problems, voids, poor resin penetration, and increased loss of interfacial properties. The ideal composite design should strike a balance between mechanical performance and manufacturing quality and not simply emphasizing the reinforcement content. The suggested framework allows one to systematically develop lightweight and high-performance composite materials for advanced engineering applications.
[1] M. F. Ashby, Materials Selection in Mechanical Design, 4th ed. Oxford, U.K.: Butterworth-Heinemann, 2011.
[2] I. M. Daniel and O. Ishai, Engineering Mechanics of Composite Materials, 2nd ed. New York, NY, USA: Oxford University Press, 2006.
[3] R. F. Gibson, Principles of Composite Material Mechanics, 4th ed. Boca Raton, FL, USA: CRC Press, 2016.
[4] R. M. Jones, Mechanics of Composite Materials, 2nd ed. Philadelphia, PA, USA: Taylor & Francis, 1999.
[5] P. K. Mallick, Fiber-Reinforced Composites: Materials, Manufacturing, and Design, 3rd ed. Boca Raton, FL, USA: CRC Press, 2007.
[6] National Aeronautics and Space Administration, “NASA hosts 2026 review on advanced composite manufacturing,” NASA, Washington, DC, USA, 2026. [Online]. Available: https://www.nasa.gov/directorates/armd/aavp/hicam/nasa-hosts-2026-review-on-advanced-composite-manufacturing/
[7] G. Struzziero, J. J. E. Teuwen, and A. A. Skordos, “Numerical optimisation of thermoset composites manufacturing processes: A review,” Compos. Part A Appl. Sci. Manuf., vol. 124, Art. no. 105499, 2019, doi: 10.1016/j.compositesa.2019.105499.
[8] Y. Hermawan, I. G. K. Puja, and H. Y. Nanlohy, “Optimization of glass fiber reinforced polymer composite using response surface methodology for application on train panels,” Mech. Eng. Soc. Ind., vol. 5, no. 2, pp. 319-330, 2025, doi: 10.31603/mesi.13090.
[9] ASTM International, ASTM D3039/D3039M-17(2025), Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials. West Conshohocken, PA, USA: ASTM International, 2025.
[10] ASTM International, ASTM D7264/D7264M-26, Standard Test Method for Flexural Properties of Polymer Matrix Composite Materials. West Conshohocken, PA, USA: ASTM International, 2026.
[11] ASTM International, ASTM D3479/D3479M-19(2023), Standard Test Method for Tension-Tension Fatigue of Polymer Matrix Composite Materials. West Conshohocken, PA, USA: ASTM International, 2023.
[12] ASTM International, ASTM D3171-22, Standard Test Methods for Constituent Content of Composite Materials. West Conshohocken, PA, USA: ASTM International, 2022.
[13] S. S. Sorour, C. A. Saleh, and M. Shazly, “A review on machine learning implementation for predicting and optimizing the mechanical behaviour of laminated fiber-reinforced polymer composites,” Heliyon, vol. 10, no. 13, Art. no. e33681, 2024, doi: 10.1016/j.heliyon.2024.e33681.
[14] V. Daghigh, H. Daghigh, T. E. Lacy, and M. Naraghi, “Review of machine learning applications for defect detection in composite materials,” Mach. Learn. Appl., vol. 18, Art. no. 100600, 2024, doi: 10.1016/j.mlwa.2024.100600.
[15] S. S. Kumar et al., “Investigation and machine learning-based prediction of mechanical properties in hybrid natural fiber composites,” Sci. Rep., vol. 15, Art. no. 33700, 2025, doi: 10.1038/s41598-025-18944-5.
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