Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures

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Year : 2026 | Volume : 14 | 02 | Page :
    By

    D Sai Ganesh,

  • S. N. Padhi,

  1. M.Tech Student, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India
  2. Professor, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India

Abstract

Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. This study explores the application of multi-objective optimization (MOO) methods to polymer-based FGCs. Techniques such as genetic algorithms (GA), particle swarm optimization (PSO), and multi-objective evolutionary algorithms (MOEAs) are employed to balance trade-offs between weight reduction, stiffness, and durability. The optimization framework combines analytical models, micromechanical analysis, and finite element simulations to predict stress, deflection, and failure under mechanical and thermal loads. Experimental data on graded polymer composites are used to validate computational results. Case studies demonstrate that optimized P-FGCs achieve up to 25% weight reduction and 30% increase in stiffness compared to conventional composites. Pareto-front analyses reveal optimal trade-offs between mechanical strength, thermal efficiency, and manufacturability. Despite progress, challenges remain in incorporating uncertainties from manufacturing defects, material variability, and cost constraints into optimization frameworks. The paper concludes with future perspectives on combining machine learning, additive manufacturing, and real-time digital twin systems to accelerate optimization and deployment of P-FGCs in next-generation lightweight structural applications.

Keywords: functionally graded composites, polymer composites, lightweight structures, multi-objective optimization, Pareto front.

How to cite this article:
D Sai Ganesh, S. N. Padhi. Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures. Journal of Polymer & Composites. 2026; 14(02):-.
How to cite this URL:
D Sai Ganesh, S. N. Padhi. Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures. Journal of Polymer & Composites. 2026; 14(02):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=243647


References

  1. Aghdam MM, Faghidian SA. Thermal stress analysis of FG polymer composites. Composite Structures. 2018;192:246-54. doi:10.1016/j.compstruct.2018.03.026
  2. Akhtar MJ, Sheikh AH. Finite element modeling of FG polymer composites. Materials Today: Proceedings. 2020;27(4):3189-96. doi:10.1016/j.matpr.2019.12.321
  3. Arif MF, Kumar R, Cantwell WJ. Additive manufacturing of FG polymer composites. Additive Manufacturing. 2021;37:101622. doi:10.1016/j.addma.2020.101622
  4. Saibabaa OS, Raja GS, Bhagat V, Arun Kumar MP, Dessai AN, Reddy RKK, Padhi SN. Free vibration of graphene reinforced polymer composite sandwich panel. Materials Today: Proceedings. 2022;57:834-9. doi:10.1016/j.matpr.2021.02.434
  5. Padhi SN, Rout T, Raghuram KS. Parametric instability of a rotating cantilever FGO beam. International Journal of Recent Technology and Engineering. 2019;8(1):2921-5. doi:10.35940/ijrte.A1234.058119
  6. Uma Mageswari SD, Suresh M, Rajesh Kumar U, Krishnamoorthy N, Padhi SN, Bamane KD, Munjal N, Rajaram A. Study on phytoextraction with biochar. Oxidation Communications. 2023;46(4):986-93.
  7. Vinayaka N, Christiyan KG, Shreepad S, Padhi SN, Dambhare SG, Gayathri K, Kolekar AB, Nagarajan S, et al. Tribological behavior on stir-casted MMCs of Al8011 & nano B4C. Journal of Nanomaterials. 2023;2023:1-10. doi:10.1155/2023/9945482
  8. Chawla KK. Composite Materials: Science and Engineering. 4th ed. New York: Springer; 2019. doi:10.1007/978-3-030-28983-6
  9. Das S, Ray BC. Advances in processing of FG polymer composites. Progress in Materials Science. 2022;124:100872. doi:10.1016/j.pmatsci.2021.100872
  10. Bhargava A, Mahapatra SS. Multi-scale modeling of FG composites. Composites Part B: Engineering. 2020;182:107631. doi:10.1016/j.compositesb.2019.107631
  11. Zhang X, Zhou D. Stress transfer and damage evolution in FG polymer composites. Composite Structures. 2021;268:113942. doi:10.1016/j.compstruct.2021.113942
  12. Liu H, Zhang Y. FEM simulation of delamination in FG polymer composites. Composites Part A: Applied Science and Manufacturing. 2022;156:106861. doi:10.1016/j.compositesa.2022.106861
  13. Huang Z, Wu C. FEM modeling of FG laminates. Journal of Composite Materials. 2020;54(18):2419-31. doi:10.1177/0021998319900876
  14. Mishra S, Patnaik A. Mechanical behavior of FG polymer nanocomposites. Journal of Materials Science. 2020;55(15):6625-41. doi:10.1007/s10853-020-04475-9
  15. Roy A, Banerjee S. Stress concentration and failure in graded composites. Composite Structures. 2018;201:464-72. doi:10.1016/j.compstruct.2018.06.067
  16. Arif MF, Kumar R, Cantwell WJ. Topology optimization of AM composites. Additive Manufacturing. 2021;37:101622. doi:10.1016/j.addma.2020.101622
  17. Mohammed T, Ali S. AM & modeling of polymer FGMs: A review. Polymers. 2023;15(6):1253. doi:10.3390/polym15061253
  18. Kumar A, Singh R. Functionally graded nanocomposites. Journal of Materials Research and Technology. 2021;14:2830-41. doi:10.1016/j.jmrt.2021.08.034
  19. Feng W, Li Y. Interfacial stress transfer in CNT-reinforced polymer composites. Computational Materials Science. 2019;160:80-90. doi:10.1016/j.commatsci.2018.12.054
  20. Wang L, Zhao C. Computational modeling of nano-reinforced composites. Composites Part C: Open Access. 2020;2:100024. doi:10.1016/j.jcomc.2020.100024
  21. Annamalai M, Ganesan S. Stress transfer in polymer composites. Journal of Reinforced Plastics and Composites. 2019;38(11):495-508. doi:10.1177/0731684419835053
  22. Jain S, Singh R. Review of shear-lag models for stress transfer. Mechanics of Composite Materials. 2017;53(5):625-38. doi:10.1007/s11029-017-9698-5
  23. Bansal Y, Sharma RK. Micromechanical modeling of polymer nanocomposites. Mechanics of Advanced Materials and Structures. 2017;24(3):189-97. doi:10.1080/15376494.2015.1124950
  24. Bose S, Roy M. Thermo-mechanical characterization of graded composites. Polymer Composites. 2018;39(10):3731-42. doi:10.1002/pc.24402
  25. Sahu P, Behera B. Experimental validation of FEM. Polymer Testing. 2019;74:89-96. doi:10.1016/j.polymertesting.2018.12.015
  26. Roland G, Padhi SN, Kayalvili S, Cloudin S, Kumar A, et al. Automated system for arrhythmia detection. Proceedings of the International Conference on Advances in Computing and Research Systems. 2022. doi:10.1109/ICACRS51859.2022.9893421
  27. Gupta V, Sharma N. Thermal residual stresses in graded composites. Mechanics Research Communications. 2018;92:39-45. doi:10.1016/j.mechrescom.2018.07.002
  28. Singh S, Ray S. Advances in polymer-based FGMs. Journal of Applied Polymer Science. 2022;139(35):e52987. doi:10.1002/app.52987
  29. Li J, Chen X. Analytical modeling of graded composites. International Journal of Mechanical Sciences. 2019;160:214-25. doi:10.1016/j.ijmecsci.2019.06.033
  30. Hu Y, Liu L. Stress transfer in short fiber composites. Composite Structures. 2021;264:113694. doi:10.1016/j.compstruct.2021.113694.
Ahead of Print Subscription Original Research
Volume 14
02
Received 28/10/2025
Accepted 25/11/2025
Published 13/05/2026
Publication Time 197 Days
2

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