L.M. Martulli, M. Sordi, A. Dinosio, A. Bernasconi
{"title":"Fully automated measurement of the spatial distribution of both fibre length and orientation from micro-CT images of short fibre reinforced polymers","authors":"L.M. Martulli, M. Sordi, A. Dinosio, A. Bernasconi","doi":"10.1016/j.compscitech.2024.110943","DOIUrl":null,"url":null,"abstract":"<div><div>The morphology of Short Fibre Reinforced Polymers (SFRPs) plays a fundamental role in determining their stiffness, strength and fracture behaviour. Measurements tools for the analysis of their microstructure are therefore of paramount importance. To this end, a fully automated algorithm able to segment single fibres from X-ray micro-computed tomography images was developed. This method was tailored to reconstruct the microstructure of large volumes of material; in particular, to acquire fibre length, position and orientation, even dealing with low-resolution images. The algorithm was tested on different specimens of short glass fibre-reinforced polyamide and it was validated comparing the fibre orientation with the one obtained with commercial software analysis and the fibre length with the experimentally determined one. Therefore, the proposed algorithm allows to easily identify microstructural trends without requiring the usual complex evaluating procedures.</div></div>","PeriodicalId":283,"journal":{"name":"Composites Science and Technology","volume":"259 ","pages":"Article 110943"},"PeriodicalIF":8.3000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Composites Science and Technology","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S026635382400513X","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, COMPOSITES","Score":null,"Total":0}
引用次数: 0
Abstract
The morphology of Short Fibre Reinforced Polymers (SFRPs) plays a fundamental role in determining their stiffness, strength and fracture behaviour. Measurements tools for the analysis of their microstructure are therefore of paramount importance. To this end, a fully automated algorithm able to segment single fibres from X-ray micro-computed tomography images was developed. This method was tailored to reconstruct the microstructure of large volumes of material; in particular, to acquire fibre length, position and orientation, even dealing with low-resolution images. The algorithm was tested on different specimens of short glass fibre-reinforced polyamide and it was validated comparing the fibre orientation with the one obtained with commercial software analysis and the fibre length with the experimentally determined one. Therefore, the proposed algorithm allows to easily identify microstructural trends without requiring the usual complex evaluating procedures.
短纤维增强聚合物(SFRP)的形态在决定其刚度、强度和断裂行为方面起着至关重要的作用。因此,分析其微观结构的测量工具至关重要。为此,我们开发了一种能够从 X 射线微型计算机断层扫描图像中分割单根纤维的全自动算法。该方法专门用于重建大量材料的微观结构,特别是获取纤维长度、位置和方向,甚至可以处理低分辨率图像。该算法在不同的短玻璃纤维增强聚酰胺试样上进行了测试,并将纤维取向与商业软件分析获得的取向进行了比较,将纤维长度与实验确定的纤维长度进行了比较。因此,所提出的算法可以轻松识别微观结构趋势,而无需通常复杂的评估程序。
期刊介绍:
Composites Science and Technology publishes refereed original articles on the fundamental and applied science of engineering composites. The focus of this journal is on polymeric matrix composites with reinforcements/fillers ranging from nano- to macro-scale. CSTE encourages manuscripts reporting unique, innovative contributions to the physics, chemistry, materials science and applied mechanics aspects of advanced composites.
Besides traditional fiber reinforced composites, novel composites with significant potential for engineering applications are encouraged.