362 research outputs found
Sharp error estimates for spline approximation: explicit constants, -widths, and eigenfunction convergence
In this paper we provide a priori error estimates in standard Sobolev
(semi-)norms for approximation in spline spaces of maximal smoothness on
arbitrary grids. The error estimates are expressed in terms of a power of the
maximal grid spacing, an appropriate derivative of the function to be
approximated, and an explicit constant which is, in many cases, sharp. Some of
these error estimates also hold in proper spline subspaces, which additionally
enjoy inverse inequalities. Furthermore, we address spline approximation of
eigenfunctions of a large class of differential operators, with a particular
focus on the special case of periodic splines. The results of this paper can be
used to theoretically explain the benefits of spline approximation under
-refinement by isogeometric discretization methods. They also form a
theoretical foundation for the outperformance of smooth spline discretizations
of eigenvalue problems that has been numerically observed in the literature,
and for optimality of geometric multigrid solvers in the isogeometric analysis
context.Comment: 31 pages, 2 figures. Fixed a typo. Article published in M3A
Computation of multi-degree B-splines
Multi-degree splines are smooth piecewise-polynomial functions where the
pieces can have different degrees. We describe a simple algorithmic
construction of a set of basis functions for the space of multi-degree splines,
with similar properties to standard B-splines. These basis functions are called
multi-degree B-splines (or MDB-splines). The construction relies on an
extraction operator that represents all MDB-splines as linear combinations of
local B-splines of different degrees. This enables the use of existing
efficient algorithms for B-spline evaluations and refinements in the context of
multi-degree splines. A Matlab implementation is provided to illustrate the
computation and use of MDB-splines
Whole breast radiotherapy in prone and supine position: is there a place for multi-beam IMRT?
Background: Early stage breast cancer patients are long-term survivors and finding techniques that may lower acute and late radiotherapy-induced toxicity is crucial. We compared dosimetry of wedged tangential fields (W-TF), tangential field intensity-modulated radiotherapy (TF-IMRT) and multi-beam IMRT (MB-IMRT) in prone and supine positions for whole-breast irradiation (WBI).
Methods: MB-IMRT, TF-IMRT and W-TF treatment plans in prone and supine positions were generated for 18 unselected breast cancer patients. The median prescription dose to the optimized planning target volume (PTVoptim) was 50 Gy in 25 fractions. Dose-volume parameters and indices of conformity were calculated for the PTVoptim and organs-at-risk.
Results: Prone MB-IMRT achieved (p= 600 cc heart dose was consistently lower in prone position; while for patients with smaller breasts heart dose metrics were comparable or worse compared to supine MB-IMRT. Doses to the contralateral breast were similar regardless of position or technique. Dosimetry of prone MB-IMRT and prone TF-IMRT differed slightly.
Conclusions: MB-IMRT is the treatment of choice in supine position. Prone IMRT is superior to any supine treatment for right-sided breast cancer patients and left-sided breast cancer patients with larger breasts by obtaining better conformity indices, target dose distribution and sparing of the organs-at-risk. The influence of treatment techniques in prone position is less pronounced; moreover dosimetric differences between TF-IMRT and MB-IMRT are rather small
Tchebycheffian B-splines in isogeometric Galerkin methods
Tchebycheffian splines are smooth piecewise functions whose pieces are drawn
from (possibly different) Tchebycheff spaces, a natural generalization of
algebraic polynomial spaces. They enjoy most of the properties known in the
polynomial spline case. In particular, under suitable assumptions,
Tchebycheffian splines admit a representation in terms of basis functions,
called Tchebycheffian B-splines (TB-splines), completely analogous to
polynomial B-splines. A particularly interesting subclass consists of
Tchebycheffian splines with pieces belonging to null-spaces of
constant-coefficient linear differential operators. They grant the freedom of
combining polynomials with exponential and trigonometric functions with any
number of individual shape parameters. Moreover, they have been recently
equipped with efficient evaluation and manipulation procedures. In this paper,
we consider the use of TB-splines with pieces belonging to null-spaces of
constant-coefficient linear differential operators as an attractive substitute
for standard polynomial B-splines and rational NURBS in isogeometric Galerkin
methods. We discuss how to exploit the large flexibility of the geometrical and
analytical features of the underlying Tchebycheff spaces according to
problem-driven selection strategies. TB-splines offer a wide and robust
environment for the isogeometric paradigm beyond the limits of the rational
NURBS model.Comment: 35 pages, 18 figure
Explicit error estimates for spline approximation of arbitrary smoothness in isogeometric analysis
In this paper we provide a priori error estimates with explicit constants for
both the -projection and the Ritz projection onto spline spaces of
arbitrary smoothness defined on arbitrary grids. This extends the results
recently obtained for spline spaces of maximal smoothness. The presented error
estimates are in agreement with the numerical evidence found in the literature
that smoother spline spaces exhibit a better approximation behavior per degree
of freedom, even for low smoothness of the functions to be approximated. First
we introduce results for univariate spline spaces, and then we address
multivariate tensor-product spline spaces and isogeometric spline spaces
generated by means of a mapped geometry, both in the single-patch and in the
multi-patch case.Comment: 39 pages, 4 figures. Improved the presentation. Article published in
Numerische Mathemati
On multivariate polynomials in Bernstein–Bézier form and tensor algebra
AbstractThe Bernstein–Bézier representation of polynomials is a very useful tool in computer aided geometric design. In this paper we make use of (multilinear) tensors to describe and manipulate multivariate polynomials in their Bernstein–Bézier form. As an application we consider Hermite interpolation with polynomials and splines
Adaptive isogeometric analysis with hierarchical box splines
Isogeometric analysis is a recently developed framework based on finite
element analysis, where the simple building blocks in geometry and solution
space are replaced by more complex and geometrically-oriented compounds. Box
splines are an established tool to model complex geometry, and form an
intermediate approach between classical tensor-product B-splines and splines
over triangulations. Local refinement can be achieved by considering
hierarchically nested sequences of box spline spaces. Since box splines do not
offer special elements to impose boundary conditions for the numerical solution
of partial differential equations (PDEs), we discuss a weak treatment of such
boundary conditions. Along the domain boundary, an appropriate domain strip is
introduced to enforce the boundary conditions in a weak sense. The thickness of
the strip is adaptively defined in order to avoid unnecessary computations.
Numerical examples show the optimal convergence rate of box splines and their
hierarchical variants for the solution of PDEs
Adaptive refinement with locally linearly independent LR B-splines: Theory and applications
In this paper we describe an adaptive refinement strategy for LR B-splines.
The presented strategy ensures, at each iteration, local linear independence of
the obtained set of LR B-splines. This property is then exploited in two
applications: the construction of efficient quasi-interpolation schemes and the
numerical solution of elliptic problems using the isogeometric Galerkin method.Comment: 23 pages, 14 figure
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