scholarly journals Adaptive isogeometric methods with hierarchical splines: Error estimator and convergence

2015 ◽  
Vol 26 (01) ◽  
pp. 1-25 ◽  
Author(s):  
Annalisa Buffa ◽  
Carlotta Giannelli

The problem of developing an adaptive isogeometric method (AIGM) for solving elliptic second-order partial differential equations with truncated hierarchical B-splines of arbitrary degree and different order of continuity is addressed. The adaptivity analysis holds in any space dimensions. We consider a simple residual-type error estimator for which we provide a posteriori upper and lower bound in terms of local error indicators, taking also into account the critical role of oscillations as in a standard adaptive finite element setting. The error estimates are properly combined with a simple marking strategy to define a sequence of admissible locally refined meshes and corresponding approximate solutions. The design of a refine module that preserves the admissibility of the hierarchical mesh configuration between two consecutive steps of the adaptive loop is presented. The contraction property of the quasi-error, given by the sum of the energy error and the scaled error estimator, leads to the convergence proof of the AIGM.

2017 ◽  
Vol 27 (14) ◽  
pp. 2631-2674 ◽  
Author(s):  
Gregor Gantner ◽  
Daniel Haberlik ◽  
Dirk Praetorius

We consider an adaptive algorithm for finite element methods for the isogeometric analysis (IGAFEM) of elliptic (possibly non-symmetric) second-order partial differential equations in arbitrary space dimension [Formula: see text]. We employ hierarchical B-splines of arbitrary degree and different order of smoothness. We propose a refinement strategy to generate a sequence of locally refined meshes and corresponding discrete solutions. Adaptivity is driven by some weighted residual a posteriori error estimator. We prove linear convergence of the error estimator (respectively, the sum of energy error plus data oscillations) with optimal algebraic rates. Numerical experiments underpin the theoretical findings.


2019 ◽  
Vol 53 (5) ◽  
pp. 1645-1665
Author(s):  
Guanglian Li ◽  
Yifeng Xu

In this work, we derive a reliable and efficient residual-typed error estimator for the finite element approximation of a 2D cathodic protection problem governed by a steady-state diffusion equation with a nonlinear boundary condition. We propose a standard adaptive finite element method involving the Dörfler marking and a minimal refinement without the interior node property. Furthermore, we establish the contraction property of this adaptive algorithm in terms of the sum of the energy error and the scaled estimator. This essentially allows for a quasi-optimal convergence rate in terms of the number of elements over the underlying triangulation. Numerical experiments are provided to confirm this quasi-optimality.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Michael Innerberger ◽  
Dirk Praetorius

AbstractWe consider an adaptive finite element method with arbitrary but fixed polynomial degree {p\geq 1}, where adaptivity is driven by an edge-based residual error estimator. Based on the modified maximum criterion from [L. Diening, C. Kreuzer and R. Stevenson, Instance optimality of the adaptive maximum strategy, Found. Comput. Math. 16 2016, 1, 33–68], we propose a goal-oriented adaptive algorithm and prove that it is instance optimal. More precisely, the goal error is bounded by the product of the total errors (being the sum of energy error plus data oscillations) of the primal and the dual problem, and the proposed algorithm is instance optimal with respect to this upper bound. Numerical experiments underline our theoretical findings.


2020 ◽  
Vol 54 (5) ◽  
pp. 1635-1660 ◽  
Author(s):  
Sören Bartels ◽  
Marijo Milicevic

The primal-dual gap is a natural upper bound for the energy error and, for uniformly convex minimization problems, also for the error in the energy norm. This feature can be used to construct reliable primal-dual gap error estimators for which the constant in the reliability estimate equals one for the energy error and equals the uniform convexity constant for the error in the energy norm. In particular, it defines a reliable upper bound for any functions that are feasible for the primal and the associated dual problem. The abstract a posteriori error estimate based on the primal-dual gap is provided in this article, and the abstract theory is applied to the nonlinear Laplace problem and the Rudin–Osher–Fatemi image denoising problem. The discretization of the primal and dual problems with conforming, low-order finite element spaces is addressed. The primal-dual gap error estimator is used to define an adaptive finite element scheme and numerical experiments are presented, which illustrate the accurate, local mesh refinement in a neighborhood of the singularities, the reliability of the primal-dual gap error estimator and the moderate overestimation of the error.


2008 ◽  
Vol 15 (2) ◽  
pp. 50-59 ◽  
Author(s):  
Amy Philofsky

AbstractRecent prevalence estimates for autism have been alarming as a function of the notable increase. Speech-language pathologists play a critical role in screening, assessment and intervention for children with autism. This article reviews signs that may be indicative of autism at different stages of language development, and discusses the importance of several psychometric properties—sensitivity and specificity—in utilizing screening measures for children with autism. Critical components of assessment for children with autism are reviewed. This article concludes with examples of intervention targets for children with ASD at various levels of language development.


1998 ◽  
Vol 5 (1) ◽  
pp. 115A-115A
Author(s):  
K CHWALISZ ◽  
E WINTERHAGER ◽  
T THIENEL ◽  
R GARFIELD
Keyword(s):  

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