The initial flaws in laminated composite structures are susceptible to inter-/intraply damage. Progressive damage analysis tools help the understanding of the mechanisms for damage initiation and growth while assisting in the design, analysis, and sustainment methods. The global–local modeling approach for the single-stringer postbuckled panel evaluated in this effort used Teflon inserts to provide initial “cracks” for model validation. The effort aimed to develop, evaluate, and enhance methods to predict damage initiation, progression, and failure of postbuckled composite hat-stiffened panels using the commercially available software Abaqus. Three methods were considered: the virtual crack closure technique (VCCT), the cohesive zone model (CZM), and enhanced Schapery theory (EST). The VCCT and CZM successfully predicted multiple delaminations. EST works with the CZM to capture delamination and facilitate interactions between interlaminar and intralaminar failures. When comparing the damage morphology against the experimental data produced through the NASA Advanced Composites Project, the present models captured the delamination, matrix, and fiber damage patterns. The VCCT and EST predictions were within 2% of the experimental peak load.


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    Titel :

    Damage Prediction of Buckled Composite Single Stiffened Panel Subject to Static Compression


    Beteiligte:
    Goyal, Vijay K. (Autor:in) / Pennington, Austin (Autor:in) / Gagliano, Jacob (Autor:in) / Lin, Shiyao (Autor:in) / Waas, Anthony (Autor:in)

    Erschienen in:

    AIAA Journal ; 61 , 9 ; 4164-4181


    Erscheinungsdatum :

    2023-07-19


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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    Weight-Effect of Buckled Composite Stiffened Panels Under Static Compression

    Goyal, Vijay / Gagliano, Jacob N. / Pennington, Austin et al. | TIBKAT | 2023


    Weight-Effect of Buckled Composite Stiffened Panels Under Static Compression

    Goyal, Vijay / Gagliano, Jacob N. / Pennington, Austin et al. | AIAA | 2023