Skip to main content

Advertisement

Log in

A multi-dwell temperature profile design for the cure of thick CFRP composite laminates

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper develops a multi-objective optimization method for the cure of thick composite laminates. The purpose is to minimize the cure time and maximum temperature overshoot in the cure process by designing the cure temperature profile. This method combines the finite element–based thermo-chemical coupled cure simulation with the non-dominated sorting genetic algorithm-II (NSGA-II). In order to investigate the influence of the number of dwells on the optimization result, four-dwell and two-dwell temperature profiles are selected for the design variables. The optimization method obtains successfully the Pareto optimal front of the multi-objective problem in thick and ultra-thick laminates. The result shows that the cure time and maximum temperature overshoot are both reduced significantly. The optimization result further illustrates that the four-dwell cure profile is more effective than the two-dwell, especially for the ultra-thick laminates. Through the optimization of the four-dwell profile, the cure time is reduced by 51.0% (thick case) and 30.3% (ultra-thick case) and the maximum temperature overshoot is reduced by 66.9% (thick case) and 73.1% (ultra-thick case) compared with the recommended cure profile. In addition, self-organizing map (SOM) is employed to visualize the relationships between the design variables with respect to the optimization result.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Availability of data and materials

The raw/processed data required to reproduce these findings cannot be shared publicly but is available upon request.

References

  1. Wang Q, Wang L, Zhu W, Xu Q, Ke Y (2017) Design optimization of molds for autoclave process of composite manufacturing. J Reinf Plast Compos 36(21):1564–1576. https://doi.org/10.1177/0731684417718265

    Article  Google Scholar 

  2. Shevtsov S, Zhilyaev I, Soloviev A, Parinov I, Dubrov V (2012) Optimization of the composite cure process based on the thermo-kinetic model. In: Advanced Materials Design and Mechanics, Vol. 569 of Advanced Materials Research, Trans Tech Publications Ltd, pp 185–192. https://doi.org/10.4028/www.scientific.net/AMR.569.185

  3. Struzziero G, Teuwen J, Skordos A (2019) Numerical optimisation of thermoset composites manufacturing processes: a review. Composites Part A: Applied Science and Manufacturing 124:105499. https://doi.org/10.1016/j.compositesa.2019.105499

    Article  Google Scholar 

  4. Hui X, Xu Y, Zhang W (2021) An integrated modeling of the curing process and transverse tensile damage of unidirectional cfrp composites. Composite Structures 263:113681. https://doi.org/10.1016/j.compstruct.2021.113681

    Article  Google Scholar 

  5. Sorrentino L, Polini W, Bellini C (2014) To design the cure process of thick composite parts: experimental and numerical results. Adv Compos Mater 23(3):225–238. https://doi.org/10.1080/09243046.2013.847780

    Article  Google Scholar 

  6. Moghaddam MK, Breede A, Brauner C, Lang W (2015) Embedding piezoresistive pressure sensors to obtain online pressure profiles inside fiber composite laminates. Sensors 15(4):7499–7511. https://doi.org/10.3390/s150407499

    Article  Google Scholar 

  7. Hui X, Xu Y, Zhang W (2020) Multiscale model of micro curing residual stress evolution in carbon fiber-reinforced thermoset polymer composites. Front Mech Eng 15(3):475–483. https://doi.org/10.1007/s11465-020-0590-6

    Article  Google Scholar 

  8. Griffis C, Masumura R, Chang C (1981) Thermal response of graphite epoxy composite subjected to rapid heating. J Compos Mater 15(5):427–442. https://doi.org/10.1177/002199838101500503

    Article  Google Scholar 

  9. Anandan S, Dhaliwal G, Huo Z, Chandrashekhara K, Apetre N, Iyyer N (2018) Curing of thick thermoset composite laminates: multiphysics modeling and experiments. Appl Compos Mater 25 (5):1155–1168. https://doi.org/10.1007/s10443-017-9658-9

    Article  Google Scholar 

  10. Liu X, He Y, Qiu D, Yu Z (2019) Numerical optimizing and experimental evaluation of stepwise rapid high-pressure microwave curing carbon fiber/epoxy composite repair patch. Composite Structures 230:111529. https://doi.org/10.1016/j.compstruct.2019.111529

    Article  Google Scholar 

  11. Li D, Li X, Dai J (2018) Process modelling of curing process-induced internal stress and deformation of composite laminate structure with elastic and viscoelastic models. Appl Compos Mater 25(3):527–544. https://doi.org/10.1007/s10443-017-9633-5

    Article  MathSciNet  Google Scholar 

  12. Qiao Y, Zhang J, Zhang M, Hu H, Liu L, Zhai P, Li S (2018) Numerical analysis on the flow–compaction behavior and the effect of interface permeability in thick composite plates during autoclave processing. J Mater Sci 53(20):14412–14422. https://doi.org/10.1007/s10853-018-2660-2

    Article  Google Scholar 

  13. Oh JH, Lee DG (2002) Cure cycle for thick glass/epoxy composite laminates. J Compos Mater 36(1):19–45. https://doi.org/10.1177/0021998302036001300

    Article  Google Scholar 

  14. Kennedy GJ, Hansen JS (2010) The hybrid-adjoint method: a semi-analytic gradient evaluation technique applied to composite cure cycle optimization. Optim Eng 11(1):23–43. https://doi.org/10.1007/s11081-008-9068-9

    Article  MathSciNet  Google Scholar 

  15. Vafayan M, Ghoreishy MHR, Abedini H, Beheshty MH (2015) Development of an optimized thermal cure cycle for a complex-shape composite part using a coupled finite element/genetic algorithm technique. Iran Polym J 24(6):459–469. https://doi.org/10.1007/s13726-015-0337-0

    Article  Google Scholar 

  16. Wang H, Chen L, Ye F, Wang J (2018) A multi-hierarchical successive optimization method for reduction of spring-back in autoclave forming. Compos Struct 188:143–158. https://doi.org/10.1016/j.compstruct.2018.01.010

    Article  Google Scholar 

  17. Aleksendrić D, Bellini C, Carlone P, Ćirović V, Rubino F, Sorrentino L (2019) Neural-fuzzy optimization of thick composites curing process. Mater Manuf Process 34(3):262–273. https://doi.org/10.1080/10426914.2018.1512116

    Article  Google Scholar 

  18. Struzziero G, Skordos A (2017) Multi-objective optimisation of the cure of thick components. Compos A: Appl Sci Manuf 93:126–136. https://doi.org/10.1016/j.compositesa.2016.11.014

    Article  Google Scholar 

  19. Shah P, Halls V, Zheng J, Batra R (2018) Optimal cure cycle parameters for minimizing residual stresses in fiber-reinforced polymer composite laminates. J Compos Mater 52(6):773–792. https://doi.org/10.1177/0021998317714317

    Article  Google Scholar 

  20. Dolkun D, Zhu W, Xu Q, Ke Y (2018) Optimization of cure profile for thick composite parts based on finite element analysis and genetic algorithm. J Compos Mater 52(28):3885–3894. https://doi.org/10.1177/0021998318771458

    Article  Google Scholar 

  21. Wang Q, Yang X, Zhao H, Zhang X, Cao G, Ren M (2021) Microscopic residual stresses analysis and multi-objective optimization for 3d woven composites. Compos Part A: Appl Sci Manuf 144:106310. https://doi.org/10.1016/j.compositesa.2021.106310

    Article  Google Scholar 

  22. Sorrentino L, Tersigni L (2012) A method for cure process design of thick composite components manufactured by closed die technology. Appl Compos Mater 19(1):31–45. https://doi.org/10.1007/s10443-010-9179-2

    Article  Google Scholar 

  23. Sorrentino L, Bellini C (2015) Validation of a methodology for cure process optimization of thick composite laminates. Polymer-Plastics Technology and Engineering 54 (17):1803–1811. https://doi.org/10.1080/03602559.2015.1050513

    Article  Google Scholar 

  24. Jahromi PE, Shojaei A, Reza Pishvaie SM (2012) Prediction and optimization of cure cycle of thick fiber-reinforced composite parts using dynamic artificial neural networks. J Reinf Plast Compos 31 (18):1201–1215. https://doi.org/10.1177/0731684412451937

    Article  Google Scholar 

  25. Hojjati M, Hoa S (1994) Curing simulation of thick thermosetting composites. Compos Manuf 5(3):159–169. https://doi.org/10.1016/0956-7143(94)90025-6

    Article  Google Scholar 

  26. Li X, Wang J, Li S, Ding A (2020) Cure-induced temperature gradient in laminated composite plate: numerical simulation and experimental measurement. Compos Struct 253:112822. https://doi.org/10.1016/j.compstruct.2020.112822

    Article  Google Scholar 

  27. Johnston AA (1997) An integrated model of the development of process-induced deformation in autoclave processing of composite structures. Ph.D. thesis, University of British Columbia

  28. Abdelal GF, Robotham A, Cantwell W (2013) Autoclave cure simulation of composite structures applying implicit and explicit fe techniques. Int J Mech Mater Des 9(1):55–63. https://doi.org/10.1007/s10999-012-9205-7

    Article  Google Scholar 

  29. Ding A, Li S, Wang J, Zu L (2015) A three-dimensional thermo-viscoelastic analysis of process-induced residual stress in composite laminates. Compos Struct 129:60–69. https://doi.org/10.1016/j.compstruct.2015.03.034

    Article  Google Scholar 

  30. Antonucci V, Giordano M, Inserraimparato S, Nicolais L (2001) Analysis of heat transfer in autoclave technology. Polymer Compos 22(5):613–620. https://doi.org/10.1002/pc.10564

    Article  Google Scholar 

  31. Esposito L, Sorrentino L, Penta F, Bellini C (2016) Effect of curing overheating on interlaminar shear strength and its modelling in thick frp laminates. Int J Adv Manuf Technol 87(5):2213–2220. https://doi.org/10.1007/s00170-016-8613-5

    Article  Google Scholar 

  32. Fallah-Mehdipour E, Bozorg Haddad O, Rezapour Tabari MM, Mariño MA (2012) Extraction of decision alternatives in construction management projects: application and adaptation of nsga-ii and mopso. Expert Syst Appl 39(3):2794–2803. https://doi.org/10.1016/j.eswa.2011.08.139

    Article  Google Scholar 

  33. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. EEE Trans Evol Comput 6(2):182–197. https://doi.org/10.1109/4235.996017

    Article  Google Scholar 

  34. Yuan Z, Tong X, Yang G, Yang Z, Song D, Li S, Li Y (2020) Curing cycle optimization for thick composite laminates using the multi-physics coupling model. Appl Compos Mater 27(6):839–860. https://doi.org/10.1007/s10443-020-09836-0

    Article  Google Scholar 

  35. Matsuzaki R, Yokoyama R, Kobara T, Tachikawa T (2019) Multi-objective curing optimization of carbon fiber composite materials using data assimilation and localized heating. Compos A: Appl Sci Manuf 119:61–72. https://doi.org/10.1016/j.compositesa.2019.01.021

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by National Natural Science Foundation of China (11872310).

Author information

Authors and Affiliations

Authors

Contributions

Wenchang Zhang: conceptualization, methodology, writing—original draft, conceptualization, software, data curation, and validation. Yingjie Xu: investigation, writing—review and editing, funding acquisition, and supervision. Xinyu Hui: methodology, data curation, and validation. Weihong Zhang: supervision and visualization.

Corresponding author

Correspondence to Yingjie Xu.

Ethics declarations

Ethics approval

Work was conducted ethically with no human test subjects.

Consent to participate

Work was conducted with no human test subjects.

Consent for Publication

Work has consent to publish.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, W., Xu, Y., Hui, X. et al. A multi-dwell temperature profile design for the cure of thick CFRP composite laminates. Int J Adv Manuf Technol 117, 1133–1146 (2021). https://doi.org/10.1007/s00170-021-07765-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-07765-1

Keywords

Navigation