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    Investigation on Tomographic-Based Nondestructive Characterization of Short Glass Fiber-Reinforced Composites as Obtained From Micro Injection Molding

    Source: Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2020:;volume( 003 ):;issue: 002
    Author:
    Rathore, Jitendra Singh
    ,
    Konopczyński, Tomasz
    ,
    Hesser, Jürgen
    ,
    Lucchetta, Giovanni
    ,
    Carmignato, Simone
    DOI: 10.1115/1.4046000
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Quantitative assessment of fiber characteristics in composite parts is of great significance in order to correlate them with the fiber-induced mechanical properties. X-ray computed tomography (CT) is being successfully used as a three-dimensional nondestructive measuring technique for the analysis of fiber characteristics (mainly the fiber orientation and fiber volume content) in fiber-reinforced composite materials. However, the accuracy of such analyses depends on various factors (e.g., scanning parameters, resolution), which is the motivation for this study. The current work investigates the effect of CT scanning parameters and spatial resolution on the obtained fiber orientation and fiber volume content. First a simulation study is carried out using a computationally generated fiber composite model followed by a validation using a thin-wall injection-molded part. The findings showed that the effect of CT settings is not significant on the measurements, but the resolution affects the estimated fiber volume content adversely. A preliminary error calculation method is proposed for correcting the overestimation in the fiber volume content.
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      Investigation on Tomographic-Based Nondestructive Characterization of Short Glass Fiber-Reinforced Composites as Obtained From Micro Injection Molding

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    contributor authorRathore, Jitendra Singh
    contributor authorKonopczyński, Tomasz
    contributor authorHesser, Jürgen
    contributor authorLucchetta, Giovanni
    contributor authorCarmignato, Simone
    date accessioned2022-02-04T14:22:28Z
    date available2022-02-04T14:22:28Z
    date copyright2020/02/05/
    date issued2020
    identifier issn2572-3901
    identifier othernde_3_2_021004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4273530
    description abstractQuantitative assessment of fiber characteristics in composite parts is of great significance in order to correlate them with the fiber-induced mechanical properties. X-ray computed tomography (CT) is being successfully used as a three-dimensional nondestructive measuring technique for the analysis of fiber characteristics (mainly the fiber orientation and fiber volume content) in fiber-reinforced composite materials. However, the accuracy of such analyses depends on various factors (e.g., scanning parameters, resolution), which is the motivation for this study. The current work investigates the effect of CT scanning parameters and spatial resolution on the obtained fiber orientation and fiber volume content. First a simulation study is carried out using a computationally generated fiber composite model followed by a validation using a thin-wall injection-molded part. The findings showed that the effect of CT settings is not significant on the measurements, but the resolution affects the estimated fiber volume content adversely. A preliminary error calculation method is proposed for correcting the overestimation in the fiber volume content.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleInvestigation on Tomographic-Based Nondestructive Characterization of Short Glass Fiber-Reinforced Composites as Obtained From Micro Injection Molding
    typeJournal Paper
    journal volume3
    journal issue2
    journal titleJournal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
    identifier doi10.1115/1.4046000
    page21004
    treeJournal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2020:;volume( 003 ):;issue: 002
    contenttypeFulltext
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