Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts
Injection-molded fiber-reinforced thermoplastic parts are increasingly used in several industrial applications thanks to their low weight, high mechanical properties, vast design possibilities, and reduced costs. However, the geometrical characteristics of fibers (i.e. fiber orientation, length, and...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Polymer Testing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142941823003434 |
| _version_ | 1797390586959888384 |
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| author | Filippo Zanini Marco Sorgato Giovanni Lucchetta Simone Carmignato |
| author_facet | Filippo Zanini Marco Sorgato Giovanni Lucchetta Simone Carmignato |
| author_sort | Filippo Zanini |
| collection | DOAJ |
| description | Injection-molded fiber-reinforced thermoplastic parts are increasingly used in several industrial applications thanks to their low weight, high mechanical properties, vast design possibilities, and reduced costs. However, the geometrical characteristics of fibers (i.e. fiber orientation, length, and concentration) have a considerable impact on the mechanical properties of the fabricated parts. The conventional methods used to study the relationship between the fiber characteristics and the resulting mechanical properties typically rely on destructive and time-consuming techniques. Micro X-ray computed tomography, instead, allows performing non-destructive measurements of the geometrical characteristics of fibers. Nevertheless, tomographic measurements are still affected by a consistent number of influence factors, hindering the results accuracy. This work proposes a methodology to verify and enhance the accuracy of tomographic fiber geometrical measurements as well as to determine their uncertainty. The improved outcomes are then exploited to accurately predict the mechanical properties of injection-molded glass-fiber-reinforced specimens characterized by different fiber volume fractions. |
| first_indexed | 2024-03-08T23:14:01Z |
| format | Article |
| id | doaj.art-fdfd25b73b174dbd83ad8f3fa5f09a36 |
| institution | Directory Open Access Journal |
| issn | 0142-9418 |
| language | English |
| last_indexed | 2024-03-08T23:14:01Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Polymer Testing |
| spelling | doaj.art-fdfd25b73b174dbd83ad8f3fa5f09a362023-12-15T07:22:21ZengElsevierPolymer Testing0142-94182023-12-01129108263Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic partsFilippo Zanini0Marco Sorgato1Giovanni Lucchetta2Simone Carmignato3Department of Management and Engineering, University of Padua, Vicenza, Italy; Corresponding author.Department of Industrial Engineering, University of Padua, Padova, ItalyDepartment of Industrial Engineering, University of Padua, Padova, ItalyDepartment of Management and Engineering, University of Padua, Vicenza, ItalyInjection-molded fiber-reinforced thermoplastic parts are increasingly used in several industrial applications thanks to their low weight, high mechanical properties, vast design possibilities, and reduced costs. However, the geometrical characteristics of fibers (i.e. fiber orientation, length, and concentration) have a considerable impact on the mechanical properties of the fabricated parts. The conventional methods used to study the relationship between the fiber characteristics and the resulting mechanical properties typically rely on destructive and time-consuming techniques. Micro X-ray computed tomography, instead, allows performing non-destructive measurements of the geometrical characteristics of fibers. Nevertheless, tomographic measurements are still affected by a consistent number of influence factors, hindering the results accuracy. This work proposes a methodology to verify and enhance the accuracy of tomographic fiber geometrical measurements as well as to determine their uncertainty. The improved outcomes are then exploited to accurately predict the mechanical properties of injection-molded glass-fiber-reinforced specimens characterized by different fiber volume fractions.http://www.sciencedirect.com/science/article/pii/S0142941823003434X-ray computed tomographyMetrologyFiber-reinforced plasticsInjection moldingFiber measurementMechanical properties |
| spellingShingle | Filippo Zanini Marco Sorgato Giovanni Lucchetta Simone Carmignato Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts Polymer Testing X-ray computed tomography Metrology Fiber-reinforced plastics Injection molding Fiber measurement Mechanical properties |
| title | Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts |
| title_full | Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts |
| title_fullStr | Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts |
| title_full_unstemmed | Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts |
| title_short | Metrological X-ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber-reinforced plastic parts |
| title_sort | metrological x ray computed tomography for fiber geometrical characterization and mechanical properties prediction in fiber reinforced plastic parts |
| topic | X-ray computed tomography Metrology Fiber-reinforced plastics Injection molding Fiber measurement Mechanical properties |
| url | http://www.sciencedirect.com/science/article/pii/S0142941823003434 |
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