000227212 001__ 227212
000227212 005__ 20181203024626.0
000227212 0247_ $$2doi$$a10.1016/j.cma.2014.12.013
000227212 022__ $$a0045-7825
000227212 037__ $$aARTICLE
000227212 245__ $$aEfficient matrix computation for tensor-product isogeometric analysis: the use of sum factorization
000227212 260__ $$c2015
000227212 269__ $$a2015
000227212 336__ $$aJournal Articles
000227212 520__ $$aIn this paper we discuss the use of the sum-factorization for the calculation of the integrals arising in Galerkin isogeometric analysis. While introducing very little change in an isogeometric code based on element-by-element quadrature and assembling, the sum-factorization approach, taking advantage of the tensor-product structure of splines or NURBS shape functions, significantly reduces the quadrature computational cost. © 2014 Elsevier B.V.
000227212 700__ $$0250510$$g276526$$aAntolin Sanchez, Pablo
000227212 700__ $$0250290$$g271675$$aBuffa, Annalisa
000227212 700__ $$aCalabrò, F.
000227212 700__ $$aMartinelli, M.
000227212 700__ $$aSangalli, G.
000227212 773__ $$j285$$tComputer Methods in Applied Mechanics and Engineering$$q817-828
000227212 909C0 $$xU13308$$0252586$$pMNS
000227212 909CO $$pSB$$particle$$ooai:infoscience.tind.io:227212
000227212 917Z8 $$x102085
000227212 917Z8 $$x271675
000227212 917Z8 $$x249835
000227212 937__ $$aEPFL-ARTICLE-227212
000227212 970__ $$aMR3312688/MNS
000227212 973__ $$rREVIEWED$$sPUBLISHED$$aOTHER
000227212 980__ $$aARTICLE