Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison
This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/23/11464 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846124402552340480 |
|---|---|
| author | Evgenii Kurkin Vladislava Chertykovtseva Andry Sedelnikov Evgenii Minaev Ekaterina Kurkina Andrey Gavrilov |
| author_facet | Evgenii Kurkin Vladislava Chertykovtseva Andry Sedelnikov Evgenii Minaev Ekaterina Kurkina Andrey Gavrilov |
| author_sort | Evgenii Kurkin |
| collection | DOAJ |
| description | This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. This makes it possible to use an electron microscope to image fiber samples corresponding to the sample size using microtomography. Molded samples and pellets of four polyamide-6 short-glass fiber-reinforced composites with mass fractions of 15%, 30%, and 50% were considered. The aspect ratio distribution measured by SEM for the investigated materials was 20.25 with a coefficient of variation of 5.1%. The fiber aspect ratio obtained based on mean field homogenization theory and the tensile curve approximation was underestimated at 13.698 with a coefficient of variation of 5.2%. The deviation between the micro- and macro-estimates can be represented as a mean effective aspect ratio of 68% with a coefficient of variation of 8.5%. The developed technology for preparing samples for SEM and automated image processing can be used to study other short-reinforced polymer composite materials. The obtained estimates can serve as a useful reference when calibrating other models of short-fiber-reinforced polymer materials. |
| format | Article |
| id | doaj-art-eaf026984d3d4c83bca5cb301f48deb7 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-eaf026984d3d4c83bca5cb301f48deb72024-12-13T16:24:00ZengMDPI AGApplied Sciences2076-34172024-12-0114231146410.3390/app142311464Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation ComparisonEvgenii Kurkin0Vladislava Chertykovtseva1Andry Sedelnikov2Evgenii Minaev3Ekaterina Kurkina4Andrey Gavrilov5Institute of Aerospace Engineering, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaInstitute of Aerospace Engineering, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaInstitute of Aerospace Engineering, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaDepartment of Supercomputers and General Informatics, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaInstitute of Aerospace Engineering, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaInstitute of Aerospace Engineering, Samara National Research University, 34 Moskovskoe Shosse, Samara 443086, RussiaThis paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. This makes it possible to use an electron microscope to image fiber samples corresponding to the sample size using microtomography. Molded samples and pellets of four polyamide-6 short-glass fiber-reinforced composites with mass fractions of 15%, 30%, and 50% were considered. The aspect ratio distribution measured by SEM for the investigated materials was 20.25 with a coefficient of variation of 5.1%. The fiber aspect ratio obtained based on mean field homogenization theory and the tensile curve approximation was underestimated at 13.698 with a coefficient of variation of 5.2%. The deviation between the micro- and macro-estimates can be represented as a mean effective aspect ratio of 68% with a coefficient of variation of 8.5%. The developed technology for preparing samples for SEM and automated image processing can be used to study other short-reinforced polymer composite materials. The obtained estimates can serve as a useful reference when calibrating other models of short-fiber-reinforced polymer materials.https://www.mdpi.com/2076-3417/14/23/11464glass short fibersaspect ratioeffective fiber lengthimage segmentationtensile testelectron microscope |
| spellingShingle | Evgenii Kurkin Vladislava Chertykovtseva Andry Sedelnikov Evgenii Minaev Ekaterina Kurkina Andrey Gavrilov Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison Applied Sciences glass short fibers aspect ratio effective fiber length image segmentation tensile test electron microscope |
| title | Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison |
| title_full | Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison |
| title_fullStr | Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison |
| title_full_unstemmed | Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison |
| title_short | Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison |
| title_sort | short glass fiber aspect ratios in polyamide 6 composites homogenization and deep learning based scanning image microscope segmentation comparison |
| topic | glass short fibers aspect ratio effective fiber length image segmentation tensile test electron microscope |
| url | https://www.mdpi.com/2076-3417/14/23/11464 |
| work_keys_str_mv | AT evgeniikurkin shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison AT vladislavachertykovtseva shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison AT andrysedelnikov shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison AT evgeniiminaev shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison AT ekaterinakurkina shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison AT andreygavrilov shortglassfiberaspectratiosinpolyamide6compositeshomogenizationanddeeplearningbasedscanningimagemicroscopesegmentationcomparison |