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Defect detection in glass fabric reinforced thermoplastics by laboratory-based X-ray scattering.

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Title: Defect detection in glass fabric reinforced thermoplastics by laboratory-based X-ray scattering.
Authors: Öztürk, Özgul1 (AUTHOR) Oezguel.Oeztuerk@uni-siegen.de, Brönnimann, Rolf2 (AUTHOR) rolf.broennimann@empa.ch, Modregger, Peter1,3 (AUTHOR) peter.modregger@uni-siegen.de
Source: Composites: Part B, Engineering. Mar2023, Vol. 252, pN.PAG-N.PAG. 1p.
Subjects: Thermoplastics, Manufacturing processes, Glass fibers, Composite materials, Mass production, X-ray scattering
Abstract: Glass fabric reinforced thermoplastic (GFRT) constitutes a class of composite materials that are especially suited for automobile construction due to their combination of low weight, ease of production and mechanical properties. However, in the manufacturing process, during forming of prefabricated laminates, defects in the glass fabric as well as in the polymer matrix can occur, which may compromise the safety or the lifetime of components. Thus, the detection of defects in GFRTs for production monitoring and a deep understanding of defect formation/evolution is essential for mass production. Here, we experimentally demonstrate that local fiber shifts in the fabric, a type of defect difficult to image with other techniques, can be detected reliably by X-ray scattering based on the edge-illumination principle. This implies applications for research on mechanism of defect formation as well as for industrial application in production monitoring. • X-ray transmission and scattering signals are anti-correlated for GFRT samples. • Local fiber shifts defects in GFRT can be detected by X-ray transmission and scattering. • Defects are detectable in the hidden glass fiber layer. [ABSTRACT FROM AUTHOR]
Copyright of Composites: Part B, Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 161553560
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Defect detection in glass fabric reinforced thermoplastics by laboratory-based X-ray scattering.
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  Data: <searchLink fieldCode="JN" term="%22Composites%3A+Part+B%2C+Engineering%22">Composites: Part B, Engineering</searchLink>. Mar2023, Vol. 252, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Thermoplastics%22">Thermoplastics</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+processes%22">Manufacturing processes</searchLink><br /><searchLink fieldCode="DE" term="%22Glass+fibers%22">Glass fibers</searchLink><br /><searchLink fieldCode="DE" term="%22Composite+materials%22">Composite materials</searchLink><br /><searchLink fieldCode="DE" term="%22Mass+production%22">Mass production</searchLink><br /><searchLink fieldCode="DE" term="%22X-ray+scattering%22">X-ray scattering</searchLink>
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  Data: Glass fabric reinforced thermoplastic (GFRT) constitutes a class of composite materials that are especially suited for automobile construction due to their combination of low weight, ease of production and mechanical properties. However, in the manufacturing process, during forming of prefabricated laminates, defects in the glass fabric as well as in the polymer matrix can occur, which may compromise the safety or the lifetime of components. Thus, the detection of defects in GFRTs for production monitoring and a deep understanding of defect formation/evolution is essential for mass production. Here, we experimentally demonstrate that local fiber shifts in the fabric, a type of defect difficult to image with other techniques, can be detected reliably by X-ray scattering based on the edge-illumination principle. This implies applications for research on mechanism of defect formation as well as for industrial application in production monitoring. • X-ray transmission and scattering signals are anti-correlated for GFRT samples. • Local fiber shifts defects in GFRT can be detected by X-ray transmission and scattering. • Defects are detectable in the hidden glass fiber layer. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Composites: Part B, Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.compositesb.2023.110502
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      – Code: eng
        Text: English
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        PageCount: 1
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      – SubjectFull: Thermoplastics
        Type: general
      – SubjectFull: Manufacturing processes
        Type: general
      – SubjectFull: Glass fibers
        Type: general
      – SubjectFull: Composite materials
        Type: general
      – SubjectFull: Mass production
        Type: general
      – SubjectFull: X-ray scattering
        Type: general
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      – TitleFull: Defect detection in glass fabric reinforced thermoplastics by laboratory-based X-ray scattering.
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            NameFull: Öztürk, Özgul
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            NameFull: Brönnimann, Rolf
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            NameFull: Modregger, Peter
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            – D: 01
              M: 03
              Text: Mar2023
              Type: published
              Y: 2023
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              Value: 252
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            – TitleFull: Composites: Part B, Engineering
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