Fiber length distribution effects on the fracture of short-fiber composites

1990 ◽  
Vol 11 (6) ◽  
pp. 307-313 ◽  
Author(s):  
M. J. Carling ◽  
J. G. Williams
Keyword(s):  
Fiber Length ◽  
Length Distribution ◽  
Fiber Composites ◽  
Short Fiber ◽  
Fiber Length Distribution

Strength of short fiber reinforced polymers: Effect of fiber length distribution

2008 ◽  
Vol 29 (6) ◽  
pp. 644-648 ◽  
Author(s):  
Muratahan Aykol ◽  
Nihat Ali Isitman ◽  
Emre Firlar ◽  
Cevdet Kaynak
Keyword(s):  
Fiber Length ◽  
Length Distribution ◽  
Short Fiber ◽  
Fiber Reinforced Polymers ◽  
Fiber Reinforced ◽  
Reinforced Polymers ◽  
Fiber Length Distribution

Bias Reduction in Kernel Estimation of the Density Function of Cotton Fiber Length

2012 ◽  
Vol 627 ◽  
pp. 23-28
Author(s):  
Yu Heng Su ◽  
Guang Song Yan
Keyword(s):  
Density Function ◽  
Cotton Fiber ◽  
Fiber Length ◽  
Length Distribution ◽  
Estimation Method ◽  
Kernel Estimation ◽  
Short Fiber ◽  
Bias Reduction ◽  
Theoretical Research ◽  
Fiber Length Distribution

Abstract. The non-parameter kernel estimation has become a dramatic method on fitting the distribution density function of cotton fiber length in theoretical research on fiber length. It can get a differentiable and integrable density function of cotton length distribution, and make the probability approach more effective on analysis and prediction of yarn performance. But, due to the requirements of the fitting smoothness, there is a bias between calculational index and measured value, especially to the short fiber content. This research uses the power function to fit the distribution of short fibers, then according to the principle of mixed distribution, revises the density function gotten by kernel estimation method, and gives a precise estimation of density function. The revised algorithm is more exact to fit the density function of fiber length. This approach is a new way to study the fiber length distribution and its effect on yarn properties both theoretically and practically.

Effect of Doffer Speed on Fiber Length Distribution in Flat Strips

2014 ◽  
Vol 1048 ◽  
pp. 89-93
Author(s):  
Xin Guo ◽  
Lan Jie Xu ◽  
Peng Zi Sun
Keyword(s):  
Fiber Length ◽  
Length Distribution ◽  
Short Fiber ◽  
Fiber Content ◽  
Test Results ◽  
Fiber Length Distribution ◽  
Better Than

The effect of doffer speed on fiber length distribution in flat strips was studied. The fiber length of flat strips produced at three doffer speeds was tested by Premier aQura neps and short fiber tester. The test results show that 1fiber length in flat strips is between 6-38 mm; 2doffer speed has some effect on flat strips quality, which is best at the doffer speed of 20r/min; 3 3% ,5% fiber length and effective fiber length at the doffer speed of 25r/min are better than those at the doffer speed of 30r/min, but short fiber content (<12.7mm and <16 mm ) at the doffer speed of 25r/min are less than those at the doffer speed of 30r/min 4 from the viewpoint of fiber length distribution, the doffer speed of 30r/min is better than that of 25r/min; 5it may not be complete only using fiber length parameters to judge the carding effect, and the fiber length distribution may be more accurate to evaluate the carding process.

Calculation method of a random beard fibrogram based on the derived Kubelka–Munk theory

2018 ◽  
Vol 89 (12) ◽  
pp. 2281-2293 ◽  
Author(s):  
Meiqin Wu ◽  
Jingye Jin ◽  
Jin Zhang ◽  
Fumei Wang
Keyword(s):  
Fiber Length ◽  
Low Cost ◽  
Length Distribution ◽  
Short Fiber ◽  
Image Method ◽  
Symmetry Principle ◽  
Significance Level ◽  
Fiber Length Distribution ◽  
Wool Fibers ◽  
Accuracy And Repeatability

The random beard image method is a newly developed fiber length measurement method with the advantages of speed, reliability and low cost. This paper proposed the methods of acquiring an accurate and stable fibrogram from the transmission image with the random beard image method based on the derived Kubelka–Munk theory. In the dual-beard preparation process, the optical properties of the short fiber region in the beard were changed by the napping effect. To solve this problem, an imitating experiment with five types of wool fibers was designed to obtain the optical coefficient of the maximum value of the fibrograms of 1.03. To eliminate the random error of the sample, the symmetry principle was adopted to determine the start line of the dual-fibrogram, and the weighted smoothing average fibrogram from two dual-beards is used as the final fibrogram. In addition, upon testing 20 types of wool fiber samples by the random beard image method and the international standard instrument Almeter100, the waviness coefficient of 1.10 was determined. A Z-test and Bland–Altman plot were also applied to verify the accuracy and repeatability of the random beard image method. The results show that under the significance level α = 0.05, the accuracy and the repeatability of the two methods are at the same level. This method sets the foundation for measuring the fiber length distribution parameters, especially the short fiber content.

Fiber length distribution and thermal, mechanical and morphological properties of thermally conductive polycarbonate/chopped carbon fiber composites

2018 ◽  
Vol 67 (8) ◽  
pp. 1137-1144 ◽  
Author(s):  
Zhixing Yu ◽  
Yu Bai ◽  
Yingcheng Li ◽  
Xiaoyu Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Carbon Fiber ◽  
Fiber Length ◽  
Length Distribution ◽  
Fiber Composites ◽  
Morphological Properties ◽  
Carbon Fiber Composites ◽  
Fiber Length Distribution ◽  
Thermally Conductive

Estimation of yarn strength based on critical slipping length and fiber length distribution

2017 ◽  
Vol 89 (2) ◽  
pp. 182-194 ◽  
Author(s):  
Zhan Jiang ◽  
Chongwen Yu ◽  
Jianping Yang ◽  
Guangting Han ◽  
Mingjie Xing
Keyword(s):  
Fiber Length ◽  
Length Distribution ◽  
Probability Method ◽  
Yarn Strength ◽  
Fiber Length Distribution ◽  
Yarn Twist ◽  
Twist Multiplier ◽  
Strength Based ◽  
Breaking Mechanism ◽  
Yarn Structure

Yarn strength is composed of the total contributions made by all breaking and slipping fibers which are determined by critical slipping length lc. Though the definition of lc has been the focus of many research projects, it still remains unsolved. In this study, idealized assumptions were made on yarn structure, and lc was then estimated. At the same time, the actual contributions that breaking fibers and slipping fibers make to yarn strength were recalculated based on an idealized yarn structure, which was analyzed with the conditional probability method according to fiber length distribution. Then, yarn strength was computed by simulating random fiber arrangement in the yarn. It could be seen from calculated results that the critical slipping length declines as yarn twist multiplier increases. Meanwhile, as the twist multiplier increases, the calculated yarn strength rises to the highest point and then declines, which is in agreement with traditional spinning theory. Thus, the calculation of yarn strength based on critical slipping length could reflect the yarn breaking mechanism with a change in the yarn twist multiplier, and could be applied for further prediction of yarn strength.

Cotton Fiber Length Distribution— An Important Quality Factor

1955 ◽  
Vol 25 (5) ◽  
pp. 422-429 ◽  
Author(s):  
Helmut Wakeham
Keyword(s):  
Quality Factor ◽  
Cotton Fiber ◽  
Fiber Length ◽  
Length Distribution ◽  
Fiber Length Distribution ◽  
Important Quality
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