@Article{icces.2023.09307,
AUTHOR = {Jiaming Liang, Qizheng Wang, Yile Hu, Yin Yu},
TITLE = {Detection of Fatigue Cracks in Metal Material Based on Peridynamic Differential Operator},
JOURNAL = {The International Conference on Computational \& Experimental Engineering and Sciences},
VOLUME = {25},
YEAR = {2023},
NUMBER = {4},
PAGES = {1--1},
URL = {http://www.techscience.com/icces/v25n4/53875},
ISSN = {1933-2815},
ABSTRACT = {The	most	common	 form	of	damage	in	aircraft	structures	is	 fatigue	damage.	Accurate	detection	of	fatigue	
crack	tip	is	the	cornerstone	for	prediction	of	crack	propagation	path	and	the	basis	for	calculation	of	residual	
strength	 and	 stiffness.	 It	 is	 of	 great	 significance	 to	 improve	 structural	 fatigue	 resistance	 design.	 When	
simulating	the	crack	growth	problem	based	on	the	traditional	method,	the	crack	tip	needs	to	be	re-meshed	
so	 that	 resulting	in	low	 calculation	 efficiency.	 The	 expansion	 of	 fatigue	 cracks	 has	 a	 complex	 shape,	 for	
example,	the	fatigue	crack	damage	on	the	aircraft	skin	often	shows	a	curved shape.	The	current	traditional	
mechanical	model	cannot	simulate	 this	com-plex	crack	shape.	 In	 this	paper,	 the	images of	 the	 test	piece	
obtained	by	DIC	are used	as	input,	and	the	corresponding	displacement	field	is	calculated	by	the	optical	flow	
method.	 Since	 the	 points	 in	 the	 displacement	 field	 calculated	 by	 the	 optical	 flow	 method	 are	 unevenly	
distributed	 points,	 the	 displacement	 field	with	 uniformly	 distributed	 points	is	 obtained	 by	interpolation	
using	the	Peridynamic	Differential	Operator.	Based	on	the	calculated	displacement	field,	the	Peridynamic	
Differential	 Operator	 is	 used	 to	 calculate	 the	 strain,	 and	 the	 strain	 compatibility	 functional	 is	 used	 to	
distinguish	the	cracked	area	from	the	non-cracked	area.	In	order	to	reduce	the	influence	of	test	noise	on	the	
results,	the	strain	compatibility	functional	is	converted	into	a	probability,	and	the	crack	area	is	extracted.
Good	 agreement	 has	 been	 observed	 between	 the	 PD	 predictions	 and	 DIC	 results,	 thus,	 verifying	 the	
correctness	and	effectiveness	of	the	proposed	method.},
DOI = {10.32604/icces.2023.09307}
}