@Article{icces.2023.09298,
AUTHOR = {Zhiyang Yao, Shuling Wang, Yin Yu, Yile Hu},
TITLE = {Micro-CT	Based	Meso-Scale	Modeling	and	Peridynamics	Analysis	for	 Short-Fiber	Composites},
JOURNAL = {The International Conference on Computational \& Experimental Engineering and Sciences},
VOLUME = {26},
YEAR = {2023},
NUMBER = {2},
PAGES = {1--1},
URL = {http://www.techscience.com/icces/v26n2/54041},
ISSN = {1933-2815},
ABSTRACT = {This	study	presents	a	method	for	modeling	and	analyzing	the	microstructure	of	short-fiber	composites	by	
using	state-based	PeriDynamic	(PD).	The	micro-structure	of	short-fiber	composites	is	obtained	from	MicroCT	scanning	which	provides	non-uniformly	discretized	meshes	of	short-fiber’s	surface	profile.	In	order	to	
obtain	the	uniformly	discretized	PD	model,	a	new	layering	algorithm	is	proposed	to	reconstruct	the	shortfiber	microstructure.	Furthermore,	considering	the	anisotropy	of	short-fiber,	a	clustering	algorithm	based	
on	machine	learning	is	introduced	 to	identify	 fibers	and	 calculate	 their	 orientations.	 The	 PD	interaction	
domain	of	a	material	point	on	the	boundary	is	incomplete,	it	can	be	complemented	by	searching	material	
points	on	the	opposite	side	of	the	microstructure.	Hence,	the	periodic	boundary	conditions	can	be	naturally	
satisfied.	The bond	constants	of	a	bond	crossing	the	fiber-matrix	interface	is	determined	by	the	fiber	volume	
fraction	of	that	particular	bond.	We	prepared	short-fiber	composites	(T300/Epoxy)	with	0.5%,	1%,	2%	and	
5%	volume	fractions.	And	the	length	of	fiber	composites	are	0.5,	1,	2,	3,	4	and	5	mm.	Statics	tests	are	carried	
out	on	short-fiber	composites.	The	comparisons	between	peridynamic	predictions	and	experimental	results	
show	good	agreement,	therefore,	the	accuracy	and	effectiveness	of	the	proposed	method	are	verified.	This	
method	can	be	used	to	study	the	effective	elastic	properties	and	damage	mechanisms	in	randomly	oriented	
short-fiber	composites	under	various	loading	conditions.},
DOI = {10.32604/icces.2023.09298}
}