Applications of level set methods in computational biophysics

Authors:
Emmanuel Maitre;Thomas Milcent;Georges-Henri Cottet;Annie Raoult;Yves Usson
Affiliations:
Université de Grenoble and CNRS, Laboratoire Jean Kuntzmann, France;Université de Grenoble and CNRS, Laboratoire Jean Kuntzmann, France;Université de Grenoble and CNRS, Laboratoire Jean Kuntzmann, France;Université Paris Descartes and CNRS, Laboratoire MAP5, France;Université de Grenoble and CNRS, Laboratoire TIMC, France
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2009

Citing 2
Cited 3

Accurate projection methods for the incompressible Navier—Stokes equations

Journal of Computational Physics
Essentially Non-Oscillatory and Weighted Essentially Non-Oscillatory Schemes for Hyperbolic Conservation Laws

Essentially Non-Oscillatory and Weighted Essentially Non-Oscillatory Schemes for Hyperbolic Conservation Laws

An unstructured solver for simulations of deformable particles in flows at arbitrary Reynolds numbers

Journal of Computational Physics
An immersed boundary method for simulating the dynamics of three-dimensional axisymmetric vesicles in Navier-Stokes flows

Journal of Computational Physics
Computing the dynamics of biomembranes by combining conservative level set and adaptive finite element methods

Journal of Computational Physics

Quantified Score

Hi-index	0.99

Visualization

Abstract

We describe in this paper two applications of Eulerian level set methods to fluid-structure problems arising in biophysics. The first one is concerned with three-dimensional equilibrium shapes of phospholipidic vesicles. This is a complex problem, which can be recast as the minimization of the curvature energy of an immersed elastic membrane, under a constant area constraint. The second deals with isolated cardiomyocyte contraction. This problem corresponds to a generic incompressible fluid-structure coupling between an elastic body and a fluid. By the choice of these two quite different situations, we aim to bring evidence that Eulerian methods provide efficient and flexible computational tools in biophysics applications.