Acquiring efficient, economic and accurate methods for identifying the material properties of heterogeneous materials have been one of themajor objectives in the mechanical engineering community, thus, inverse methods may be considered as contributing to a very promising way of achieving the objective. This paper is concerned with an inverse method for identifying the material properties of a kenaf reinforced compositetest model. Aninitial finite element model of the composite test model is developed and normal modes analysis is carried out to calculate the modal parameters of the initial finite element model. The inverse method which is developed fromMSC Nastran SOL200 is used to update iteratively the material properties of the initial finite element model based on the comparison between the calculated modal parameters and those observed experimentally from experimental modal analysis (EMA). The objective is to acquire the most appropriate set of material properties that provide well match between the finite element model and the test model. It was found that the identified material properties are well matched with that of previous published papers in terms of the reduction in total errors, which are discussed in this paper.


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    Titel :

    Inverse method for material properties identification of a kenaf reinforced composite


    Beteiligte:
    Peter, C. (Autor:in) / Rani, M. N. Abdul (Autor:in) / Yunus, M. A. (Autor:in) / Zin, M. S. Mohd (Autor:in) / Kalam, A. (Autor:in) / Shah, M. A. S. Aziz (Autor:in) / Ghani, Saiful Anwar Che (Herausgeber:in) / Abdullah, Abdul Adam (Herausgeber:in) / Sani, Mohd. Shahrir Mohd (Herausgeber:in) / Hamzah, Wan Azmi Wan (Herausgeber:in)

    Kongress:

    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AUTOMOTIVE INNOVATION GREEN ENERGY VEHICLE: AIGEV 2018 ; 2018 ; Kuantan, Malaysia


    Erschienen in:

    Erscheinungsdatum :

    11.01.2019


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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