@Article{icces.2023.09068,
AUTHOR = {Yuhao Yang, Yingjun Wang},
TITLE = {An	Automatic	Post-Processing	Procedure	for	Isogeometric	Topology	 Optimization	Results},
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/v26n2/54035},
ISSN = {1933-2815},
ABSTRACT = {In	 the	 intelligent	 structural	 optimization,	 designers	 can	 obtain	 a	 high-performance	 design	 scheme	
automatically	with	the	help	of	topology	optimization	(TO).	Since	computer	aided	design	(CAD)	and	computer	
aided	engineering	(CAE)	models	have	different	geometric	representations	in	TO,	the	optimized	results	must	
be	reconstructed	to	generate	CAD	models,	which	is	complicated	and	time-consuming.	To	address	this	issue,	
the	isogeometric	analysis	(IGA)	is	employed	in	TO	to	replace	the	finite	element	method	(FEM),	and	such	TO	
is	termed	as	isogeometric	TO	(ITO).	ITO	is	an	advanced	TO	method	with	high	efficiency	and	accuracy.	It	uses	
the	 same	 non-uniform	 rational	 B-spline	 (NURBS) basis	 function	 in	 both	 geometric	 representation	 and	
physical	interpolation.	However,	due	to	the	complex	optimized	structures,	the	automatic	post-processing	
procedure	 for	 ITO	 is	 still	 challenging.	 To	 solve	 this	 problem,we	 present	 an	 automatic	 post-processing	
procedure	to	generate	editable	CAD	models	in	terms	of	the	control	points	of	ITO.	The	procedure	takes	the	
design	 variables	as	high-dimensional	 coordinates	 of	 the	 control	points,	and	 reconstructs	 the	CAD	model	
automatically	 by	 a	 series	 of	 geometric	 algorithms	 such	 as	 surface/plane	 intersection	 algorithm,	 surface	
skinning,	and	plane	trimming	algorithm.	Therefore,	the	result	CAD	models	of	the	procedure	are	boundary	
representation	consisting	of	skinned	B-spline	surfaces	and	trimmed	planes.	The	proposed	automatic	postprocessing	procedure	takes	full	advantage	of	ITO,	and	breaks	the	bottleneck	of	integrating	structure	design,	
analysis,	and	optimization.},
DOI = {10.32604/icces.2023.09068}
}