Experimental investigation on the mechanical behavior and damage of 3D printed composites under three-point bending

材料科学 复合材料 弯曲 抗弯强度 复合数 三点弯曲试验 主成分分析 纤维 声发射 玻璃纤维 变形(气象学) 无损检测 计算机科学 人工智能 医学 放射科
作者
Lianhua Ma,Kun Zhang,Zhi‐bo Pan,Wei Zhou,Jia Liu
出处
期刊:Journal of Composite Materials [SAGE Publishing]
卷期号:56 (7): 1019-1037 被引量:6
标识
DOI:10.1177/00219983211066389
摘要

Three-dimensional (3D) printing has been triumphantly applied for the manufacture of various composite components. In this work, acoustic emission (AE), X-ray micro-computed tomography (Micro-CT) are used in conjunction with digital image correlation (DIC) measurement to investigate the mechanical behaviors of 3D printed continuous fiber reinforced composites under three-point bending test. Meanwhile, several mechanical experiments are carried out to study the flexural properties of three kinds of composite specimens, among which the specimens with larger glass fiber content exhibit more superior mechanical properties. Furthermore, AE response characterizations and microscopic damage morphology are also examined. In consequence, the complementary nondestructive testing (NDT) technology combining AE, DIC, and Micro CT is successfully applied to evaluate the mechanical behaviors of 3D printed composites, and the flexural deformation and damage are comparatively investigated for different composite specimens. The cross-validation results of cluster analysis (k-means), K-Nearest Neighbor (KNN) and principal component analysis (PCA) show that AE parameters including frequency, amplitude, and RA value (rise time divided by peak amplitude) are closely associated with the damage process of different specimens. The results show that the PCA can confirm the selected K-means cluster analysis parameters (peak frequency and peak amplitude) and the dimensionality reduction effects of 20% glass fiber specimens have the best results, indicating that the proportion of the principal components extracted can represent the original parameters is 81%. It was also confirmed that the supervised learning KNN algorithm corresponding to different damage patterns can verify the unsupervised learning k-means cluster. Correspondingly, the strain fields characterized by DIC are reasonably matched with the AE signal responses. In addition, the critical damage and delamination mechanisms of the 3D printed continuous fiber reinforced composites are clearly revealed by Micro-CT characterization.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
tyughi完成签到,获得积分10
1秒前
zzz完成签到 ,获得积分20
1秒前
苏苏完成签到,获得积分10
1秒前
June完成签到,获得积分10
1秒前
sansan完成签到 ,获得积分10
1秒前
ning发布了新的文献求助10
1秒前
豌豆尖完成签到,获得积分10
2秒前
zyj完成签到,获得积分10
2秒前
leslierui发布了新的文献求助10
2秒前
炙热的孤菱完成签到,获得积分10
4秒前
行走的小鱼完成签到,获得积分10
4秒前
熊宝完成签到,获得积分10
4秒前
Akim应助GUAN采纳,获得10
5秒前
高屋建瓴发布了新的文献求助10
5秒前
Upupuu完成签到,获得积分10
5秒前
超级天川完成签到,获得积分10
5秒前
英俊尔风完成签到,获得积分10
6秒前
火星上如松完成签到 ,获得积分10
6秒前
寒冷又晴发布了新的文献求助30
7秒前
林妹妹完成签到,获得积分10
7秒前
7秒前
fishh完成签到,获得积分10
8秒前
8秒前
卷毛的好青年完成签到,获得积分10
8秒前
木头人完成签到,获得积分10
8秒前
8秒前
9秒前
执着从筠完成签到 ,获得积分10
9秒前
摩诃完成签到,获得积分10
10秒前
大将军完成签到,获得积分10
10秒前
写个锤子完成签到,获得积分10
10秒前
谨慎的含巧完成签到 ,获得积分10
11秒前
Jelly完成签到,获得积分10
12秒前
12秒前
江霭完成签到,获得积分10
12秒前
爱学习完成签到,获得积分10
12秒前
顾矜应助15945采纳,获得10
13秒前
13秒前
apeach发布了新的文献求助10
13秒前
自觉发布了新的文献求助10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
日本現代怪異事典 副読本 700
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
Models for the coupled atmosphere and ocean 600
Évora na Idade Média 555
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7385227
求助须知:如何正确求助?哪些是违规求助? 8991936
关于积分的说明 19128233
捐赠科研通 7022683
什么是DOI,文献DOI怎么找? 3227454
关于科研通互助平台的介绍 2390468
邀请新用户注册赠送积分活动 2208624