2008
DOI: 10.1016/j.gmod.2008.03.001
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Polynomial splines over hierarchical T-meshes

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Cited by 281 publications
(182 citation statements)
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“…cubic splines over hierarchical T-meshes with reduced C 1 regularity, no refinement propagation is observed -see for example the original papers [2,12] or their recent application for the numerical solution of partial differential equations [9,14]. Despite a proper local refinement behavior in this case, the reduced regularity leads to a higher number of degrees of freedom to achieve a certain given accuracy.…”
Section: Neverthelessmentioning
confidence: 99%
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“…cubic splines over hierarchical T-meshes with reduced C 1 regularity, no refinement propagation is observed -see for example the original papers [2,12] or their recent application for the numerical solution of partial differential equations [9,14]. Despite a proper local refinement behavior in this case, the reduced regularity leads to a higher number of degrees of freedom to achieve a certain given accuracy.…”
Section: Neverthelessmentioning
confidence: 99%
“…T-splines [17,18] and PHT-splines [2] are defined over T-meshes, where T-junctions between axis aligned segments are allowed. The T-spline framework has already shown its potential as a powerful modeling tool for advanced computer aided geometric design problems.…”
Section: Introductionmentioning
confidence: 99%
“…The polynomial splines introduced in [7] are related to B-splines of reduced continuity over hierarchical T-meshes. Local refinement is an appealing property of the PHT-splines, which makes their use suitable for fitting arbitrary domains.…”
Section: Polynomial Splines Over Hierarchical T-meshes (Pht Splines)mentioning
confidence: 99%
“…For a linear mapping between the parameter space and the physical space, the control points of the initial mesh (ℓ = 1) are set as the locations of the Greville Abscissae, while the control points at level ℓ > 1 can be computed using the geometric information of the basis functions [7]. The geometric information is determined by the location of the basis vertex in the physical space and the values of the derivatives of the mapping evaluated at the basis vertex.…”
Section: Computing the Control Pointsmentioning
confidence: 99%
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