On the estimation of the curvatures and bending rigidity of membrane networks via a local maximum-entropy approach

Fraternali, F. and Lorenz, C.D. and Marcelli, Gianluca (2012) On the estimation of the curvatures and bending rigidity of membrane networks via a local maximum-entropy approach. Journal of Computational Physics, 231 (2). pp. 528-540. ISSN 0021-9991. (doi:https://doi.org/10.1016/j.jcp.2011.09.017) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1016/j.jcp.2011.09.017

Abstract

We present a meshfree method for the curvature estimation of membrane networks based on the local maximum entropy approach recently presented in [1]. A continuum regularization of the network is carried out by balancing the maximization of the information entropy corresponding to the nodal data, with the minimization of the total width of the shape functions. The accuracy and convergence properties of the given curvature prediction procedure are assessed through numerical applications to benchmark problems, which include coarse grained molecular dynamics simulations of the fluctuations of red blood cell membranes [2] and [3]. We also provide an energetic discrete-to-continuum approach to the prediction of the zero-temperature bending rigidity of membrane networks, which is based on the integration of the local curvature estimates. The local maximum entropy approach is easily applicable to the continuum regularization of fluctuating membranes, and the prediction of membrane and bending elasticities of molecular dynamics models.

Item Type: Article
Uncontrolled keywords: Membrane networks; Principal curvatures; Bending rigidity; Maximum information entropy; Minimum width; Red blood cell membrane
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Tina Thompson
Date Deposited: 24 Oct 2013 13:39 UTC
Last Modified: 30 May 2014 11:02 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35619 (The current URI for this page, for reference purposes)
  • Depositors only (login required):