Efficient matrix computation for tensor-product isogeometric analysis: The use of sum factorization

2015 ◽  
Vol 285 ◽  
pp. 817-828 ◽  
Author(s):  
P. Antolin ◽  
A. Buffa ◽  
F. Calabrò ◽  
M. Martinelli ◽  
G. Sangalli
Keyword(s):  
Tensor Product ◽  
Isogeometric Analysis ◽  
Matrix Computation

scholarly journals Optimal and reduced quadrature rules for tensor product and hierarchically refined splines in isogeometric analysis

2017 ◽  
Vol 316 ◽  
pp. 966-1004 ◽  
Author(s):  
René R. Hiemstra ◽  
Francesco Calabrò ◽  
Dominik Schillinger ◽  
Thomas J.R. Hughes
Keyword(s):  
Tensor Product ◽  
Isogeometric Analysis ◽  
Quadrature Rules

A HIERARCHICALLY SUPERIMPOSING LOCAL REFINEMENT METHOD FOR ISOGEOMETRIC ANALYSIS

2014 ◽  
Vol 11 (05) ◽  
pp. 1350074 ◽  
Author(s):  
ZOO-HWAN HAH ◽  
HYUN-JUNG KIM ◽  
SUNG-KIE YOUN
Keyword(s):  
Tensor Product ◽  
Isogeometric Analysis ◽  
Spline Space ◽  
Local Refinement ◽  
Compatibility Conditions ◽  
Spline Surfaces ◽  
Refinement Method ◽  
Refinement Strategy ◽  
Different Levels ◽  
Made In

In isogeometric analysis, the tensor-product form of Nonuniform Rational B-spline (NURBS) represents spline surfaces. Due to the nature of the tensor-product, the local refinement in isogeometric analysis has many issues to be resolved. Attempts have been made in this regard, such as T-splines and hierarchical approaches. In this work, a local refinement method for isogeometric analysis based on a superimposing concept is proposed. Local refinements are performed by superimposing hierarchically-created finer overlay meshes onto the regions of high error rather than a change of analysis basis (from NURBS to some other spline space). To employ the superimposing concept as a local refinement strategy in isogeometric analysis, a hierarchical framework to construct overlay meshes is developed, and compatibility conditions across the interfacial boundaries of different levels of meshes is discussed. Through numerical examples, the effectiveness and validity of the proposed method are demonstrated.

Reference Signal Based Tensor Product Expansion for EOG-Related Artifact Separation in EEG

2017 ◽  
Vol E100.A (11) ◽  
pp. 2230-2237
Author(s):  
Akitoshi ITAI ◽  
Arao FUNASE ◽  
Andrzej CICHOCKI ◽  
Hiroshi YASUKAWA
Keyword(s):  
Tensor Product ◽  
Reference Signal

On degeneracy problem of NFSRs via semi-tensor product

2020 ◽  
Author(s):  
Xinyu Zhao ◽  
Biao Wang ◽  
Shuqian Zhu ◽  
Jun-e Feng
Keyword(s):  
Tensor Product ◽  
Degeneracy Problem
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