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First variation of the general curvature-dependent surface energy

Günay DoğanRicardo H. Nochetto — 2012

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

We consider general surface energies, which are weighted integrals over a closed surface with a weight function depending on the position, the unit normal and the mean curvature of the surface. Energies of this form have applications in many areas, such as materials science, biology and image processing. Often one is interested in finding a surface that minimizes such an energy, which entails finding its first variation with respect to perturbations of the surface. We present a concise derivation...

First variation of the general curvature-dependent surface energy

Günay DoğanRicardo H. Nochetto — 2011

ESAIM: Mathematical Modelling and Numerical Analysis

We consider general surface energies, which are weighted integrals over a closed surface with a weight function depending on the position, the unit normal and the mean curvature of the surface. Energies of this form have applications in many areas, such as materials science, biology and image processing. Often one is interested in finding a surface that minimizes such an energy, which entails finding its first variation with respect to perturbations of the surface. We present a concise derivation...

A posteriori error control for the Allen–Cahn problem : circumventing Gronwall’s inequality

Daniel KesslerRicardo H. NochettoAlfred Schmidt — 2004

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

Phase-field models, the simplest of which is Allen–Cahn’s problem, are characterized by a small parameter ε that dictates the interface thickness. These models naturally call for mesh adaptation techniques, which rely on a posteriori error control. However, their error analysis usually deals with the underlying non-monotone nonlinearity via a Gronwall argument which leads to an exponential dependence on ε - 2 . Using an energy argument combined with a topological continuation argument and a spectral...

Adaptive finite element method for shape optimization

Pedro MorinRicardo H. NochettoMiguel S. PaulettiMarco Verani — 2012

ESAIM: Control, Optimisation and Calculus of Variations

We examine shape optimization problems in the context of inexact sequential quadratic programming. Inexactness is a consequence of using adaptive finite element methods (AFEM) to approximate the state and adjoint equations (the dual weighted residual method), update the boundary, and compute the geometric functional. We present a novel algorithm that equidistributes the errors due to shape optimization and discretization, thereby leading to coarse resolution in the early stages and fine resolution...

Adapting meshes and time-steps for phase change problems

Ricardo H. NochettoAlfred SchmidtClaudio Verdi — 1997

Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti Lincei. Matematica e Applicazioni

We address the numerical approximation of the two-phase Stefan problem and discuss an adaptive finite element method based on rigorous a posteriori error estimation and refinement/coarsening. We also investigate how to restrict coarsening for the resulting method to be stable and convergent. We review implementation issues associated with bisection and conclude with simulations of a persistent corner singularity, for which adaptivity is an essential tool.

A finite element scheme for the evolution of orientational order in fluid membranes

Sören BartelsGeorg DolzmannRicardo H. Nochetto — 2010

ESAIM: Mathematical Modelling and Numerical Analysis

We investigate the evolution of an almost flat membrane driven by competition of the homogeneous, Frank, and bending energies as well as the coupling of the local order of the constituent molecules of the membrane to its curvature. We propose an alternative to the model in [J.B. Fournier and P. Galatoa, (1997) 1509–1520; N. Uchida, (2002) 040902] which replaces a Ginzburg-Landau penalization for the length of the order parameter by a rigid constraint. We introduce...

Error Control and Andaptivity for a Phase Relaxation Model

Zhiming ChenRicardo H. NochettoAlfred Schmidt — 2010

ESAIM: Mathematical Modelling and Numerical Analysis

The phase relaxation model is a diffuse interface model with small parameter which consists of a parabolic PDE for temperature and an ODE with double obstacles for phase variable . To decouple the system a semi-explicit Euler method with variable step-size is used for time discretization, which requires the stability constraint . Conforming piecewise linear finite elements over highly graded simplicial meshes with parameter are further employed for space discretization. error estimates...

error control for the Allen–Cahn problem: circumventing Gronwall's inequality

Daniel KesslerRicardo H. NochettoAlfred Schmidt — 2010

ESAIM: Mathematical Modelling and Numerical Analysis

Phase-field models, the simplest of which is Allen–Cahn's problem, are characterized by a small parameter that dictates the interface thickness. These models naturally call for mesh adaptation techniques, which rely on error control. However, their error analysis usually deals with the underlying non-monotone nonlinearity via a Gronwall argument which leads to an exponential dependence on ε. Using an energy argument combined with a topological continuation argument and a spectral estimate,...

error analysis for parabolic variational inequalities

Kyoung-Sook MoonRicardo H. NochettoTobias von PetersdorffChen-song Zhang — 2007

ESAIM: Mathematical Modelling and Numerical Analysis

Motivated by the pricing of American options for baskets we consider a parabolic variational inequality in a bounded polyhedral domain Ω d with a continuous piecewise smooth obstacle. We formulate a fully discrete method by using piecewise linear finite elements in space and the backward Euler method in time. We define an error estimator and show that it gives an upper bound for the error in (Ω)). The error estimator is localized in the sense that the size of the elliptic residual is only relevant...

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