کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7824841 | 1502921 | 2018 | 26 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The remarkably enhanced particle erosion resistance and toughness properties of glass fiber/epoxy composites via thermoplastic polyurethane nonwoven fabric
ترجمه فارسی عنوان
مقاومت قابل توجهی در برابر فرسایش ذرات و خواص چسبندگی کامپوزیت های فیبر شیشه ای / اپوکسی از طریق پارچه غیر پارچه ای پلی اورتان ترموپلاستیک
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آلی
چکیده انگلیسی
In this work, a new method of preparing glass fiber/epoxy (GF/EP) composites with excellent solid particle erosion resistance and fracture toughness properties via thermoplastic polyurethane nonwoven fabric (TNF) was reported. TNF was prepared by virtue of the melt-blown (MB) process, and the composites were fabricated by vacuum-assisted resin transfer molding (VARTM) technique. Solid particle erosion characteristics of the composites were investigated in a confined space by impinging angular silica particles with a size about 300â¯Î¼m. Compared with conventional GF/EP composites, the erosive wear resistance of TNF/glass fiber/epoxy (TNF/GF/EP) composites were improved by 99%, 108%, 205% and 493% at the impingement angles of 20°, 30°, 45° and 90°, respectively. Meanwhile, increase of 78% in GIC and 115% in Gâ
¡C were achieved. Microstructure characterizations, including scanning electron microscopy (SEM) and optical microscopy were performed to investigate the variations of microstructure and further to establish the relationship between epoxy matrix and glass fibers. This work suggests a promising routine to improve particle erosion resistance and fracture toughness by interleaving the laminates with lightweight thermoplastic polyurethane nonwoven fabrics.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Polymer Testing - Volume 69, August 2018, Pages 470-477
Journal: Polymer Testing - Volume 69, August 2018, Pages 470-477
نویسندگان
Guangchao Lv, Na Zhang, Ming Huang, Changyu Shen, Jose Castro, Kunlun Tan, Xianhu Liu, Chuntai Liu,