A machine learning-driven approach to predict mechanical degradation associated with matrix cracks in fiber-reinforced composite laminates

M.J. Mohammad Fikry, Jason P. Mack, Faizan Mirza, Niken Prasasti Martono, K.T. Tan, Vladimir Vinogradov, Shinji Ogihara

Open source

DOI
10.1016/j.nxmate.2025.101209
Published
2025-10
Container
Next Materials
Publisher
Elsevier BV
Open access
unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.nxmate.2025.101209,
  title = {A machine learning-driven approach to predict mechanical degradation associated with matrix cracks in fiber-reinforced composite laminates},
  author = {M.J. Mohammad Fikry and Jason P. Mack and Faizan Mirza and Niken Prasasti Martono and K.T. Tan and Vladimir Vinogradov and Shinji Ogihara},
  year = {2025},
  journal = {Next Materials},
  doi = {10.1016/j.nxmate.2025.101209},
  url = {https://doi.org/10.1016/j.nxmate.2025.101209}
}

RIS

TY  - JOUR
TI  - A machine learning-driven approach to predict mechanical degradation associated with matrix cracks in fiber-reinforced composite laminates
AU  - M.J. Mohammad Fikry
AU  - Jason P. Mack
AU  - Faizan Mirza
AU  - Niken Prasasti Martono
AU  - K.T. Tan
AU  - Vladimir Vinogradov
AU  - Shinji Ogihara
PY  - 2025
JO  - Next Materials
DO  - 10.1016/j.nxmate.2025.101209
UR  - https://doi.org/10.1016/j.nxmate.2025.101209
ER  - 

APA

Fikry, M. M., Mack, J. P., Mirza, F., Martono, N. P., Tan, K., Vinogradov, V., & Ogihara, S. (2025). A machine learning-driven approach to predict mechanical degradation associated with matrix cracks in fiber-reinforced composite laminates. Next Materials. https://doi.org/10.1016/j.nxmate.2025.101209

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