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钻孔工艺参数对玻璃纤维/铝网增强环氧树脂复合材料承载强度的影响。

Effect of drilling process parameters on bearing strength of glass fiber/aluminum mesh reinforced epoxy composites.

作者信息

Seif Amr, Fathy A, Megahed A A

机构信息

Mechanical Design and Production Engineering Department, Faculty of Engineering, Zagazig University, P. O. Box 44519, Zagazig, Al-Sharqia, Egypt.

Mechanical Department, Higher Technological Institute, Tenth of Ramadan City, Egypt.

出版信息

Sci Rep. 2023 Jul 26;13(1):12143. doi: 10.1038/s41598-023-39097-3.

DOI:10.1038/s41598-023-39097-3
PMID:37495646
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10372084/
Abstract

The current study attempted to evaluate the impact of drilling parameters and delamination on the bearing strength of both neat GFRP (NG) and hybrid GFRP/aluminum (Al)-wire mesh with two various configurations, first with Al-mesh in the outer surface of specimen (AG) and the other with Al-mesh in the core of specimen (GA). Drilling procedure is carried out using [Formula: see text] 6 mm carbide twist drill with three different tip angles (90°, 120° and 135°), as well as Three different speeds and feeds (1000, 2000, and 3000 rpm) and (20, 40, and 60 mm/min), respectively. Taguchi and ANOVA analyses are used to analyze the influence of processing parameters. The findings showed that AG specimen experienced the least delamination damage. The maximum bearing strength refers to NG specimen, which is 9.6% and 8.7% more than AG and GA specimens, respectively. Drill point angle has the major effect on bearing strength for both AG and GA specimens, while for NG feed rate is of the major effect. The developed regression model displayed a high level of fitness with an average prediction error of less than 3%.

摘要

当前研究试图评估钻孔参数和分层对纯玻璃纤维增强塑料(NG)以及两种不同配置的玻璃纤维增强塑料/铝(Al)丝网混合材料承载强度的影响,第一种配置是Al丝网位于试样外表面(AG),另一种是Al丝网位于试样芯部(GA)。钻孔过程使用直径6毫米的硬质合金麻花钻,采用三种不同的顶角(90°、120°和135°),以及分别采用三种不同的转速和进给量(1000、2000和3000转/分钟)和(20、40和60毫米/分钟)。采用田口方法和方差分析来分析加工参数的影响。研究结果表明,AG试样的分层损伤最小。最大承载强度出现在NG试样上,分别比AG和GA试样高9.6%和8.7%。钻尖角对AG和GA试样的承载强度影响最大,而对于NG试样,进给速度影响最大。所建立的回归模型显示出较高的拟合度,平均预测误差小于3%。

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