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Numerical Analysis of Damage in Composites: From Intra-Layer to Delamination and Data-Assisted Methods

Author

Listed:
  • Alireza Taherzadeh-Fard

    (Centre International de Mètodes Numèrics a l’Enginyeria (CIMNE), Campus Nord UPC, 08034 Barcelona, Spain
    Civil and Environmental Engineering Department (DECA), ETSECCPB, Universitat Politècnica de Catalunya (UPC BarcelonaTech), Campus Nord, 08034 Barcelona, Spain)

  • Alejandro Cornejo

    (Centre International de Mètodes Numèrics a l’Enginyeria (CIMNE), Campus Nord UPC, 08034 Barcelona, Spain
    Civil and Environmental Engineering Department (DECA), ETSECCPB, Universitat Politècnica de Catalunya (UPC BarcelonaTech), Campus Nord, 08034 Barcelona, Spain)

  • Sergio Jiménez

    (Centre International de Mètodes Numèrics a l’Enginyeria (CIMNE), Campus Nord UPC, 08034 Barcelona, Spain
    Civil and Environmental Engineering Department (DECA), ETSECCPB, Universitat Politècnica de Catalunya (UPC BarcelonaTech), Campus Nord, 08034 Barcelona, Spain)

  • Lucia G. Barbu

    (Centre International de Mètodes Numèrics a l’Enginyeria (CIMNE), Campus Nord UPC, 08034 Barcelona, Spain
    Civil and Environmental Engineering Department (DECA), ETSECCPB, Universitat Politècnica de Catalunya (UPC BarcelonaTech), Campus Nord, 08034 Barcelona, Spain)

Abstract

The simulation of damage in composite materials is an important research area that impacts different engineering applications from aerospace structures to renewable energy systems. This review provides a comprehensive analysis of current damage modeling approaches, including intra-layer and inter-layer failures. Various numerical strategies, such as continuum damage mechanics (CDM), cohesive zone models (CZM), extended finite element methods (XFEM), phase-field models (PFM), and peridynamics (PD), are examined to assess their efficiency in predicting crack initiation, propagation, and interaction. Additionally, the role of data-assisted (driven) techniques, such as machine learning, in enhancing predictive capabilities is explored. This review highlights the strengths and limitations of each approach, underscoring the need for further advancements in computational efficiency, multiscale modeling, and integration with experimental data. The findings serve as a foundation for future research into optimizing damage prediction techniques to improve the reliability and durability of composite structures.

Suggested Citation

  • Alireza Taherzadeh-Fard & Alejandro Cornejo & Sergio Jiménez & Lucia G. Barbu, 2025. "Numerical Analysis of Damage in Composites: From Intra-Layer to Delamination and Data-Assisted Methods," Mathematics, MDPI, vol. 13(10), pages 1-42, May.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:10:p:1578-:d:1653190
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    References listed on IDEAS

    as
    1. Salman Khalid & Muhammad Haris Yazdani & Muhammad Muzammil Azad & Muhammad Umar Elahi & Izaz Raouf & Heung Soo Kim, 2024. "Advancements in Physics-Informed Neural Networks for Laminated Composites: A Comprehensive Review," Mathematics, MDPI, vol. 13(1), pages 1-35, December.
    2. Eduardo Martin-Santos & Lucia G. Barbu & Pablo Cruz, 2024. "Damage and Failure Modeling of Composite Material Structures Using the Pam-Crash Code," Mathematics, MDPI, vol. 12(23), pages 1-27, December.
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