Smooth, second order, non‐negative meshfree approximants selected by maximum entropy

We present a family of approximation schemes, which we refer to as second-order maximum-entropy (max-ent) approximation schemes, that extends the first-order local max-ent approximation schemes to second-order consistency. This method retains the fundamental properties of first-order max-ent schemes, namely the shape functions are smooth, non-negative, and satisfy a weak Kronecker-delta property at the boundary. This last property makes the imposition of essential boundary conditions in the numerical solution of partial differential equations trivial. The evaluation of the shape functions is not explicit, but it is very efficient and robust. To our knowledge, the proposed method is the first higher-order scheme for function approximation from unstructured data in arbitrary dimensions with non-negative shape functions. As a consequence, the approximants exhibit variation diminishing properties, as well as an excellent behavior in structural vibrations problems as compared with the Lagrange finite elements, MLS-based meshfree methods and even B-Spline approximations, as shown through numerical experiments. When compared with usual MLS-based second-order meshfree methods, the shape functions presented here are much easier to integrate in a Galerkin approach, as illustrated by the standard benchmark problems.

[1]  Magdalena Ortiz,et al.  Local maximum‐entropy approximation schemes: a seamless bridge between finite elements and meshfree methods , 2006 .

[2]  I. Babuska,et al.  Acta Numerica 2003: Survey of meshless and generalized finite element methods: A unified approach , 2003 .

[3]  M. Born,et al.  Dynamical Theory of Crystal Lattices , 1954 .

[4]  Michael Ortiz,et al.  Local Maximum-Entropy Approximation Schemes , 2007 .

[5]  T. Belytschko,et al.  THE NATURAL ELEMENT METHOD IN SOLID MECHANICS , 1998 .

[6]  E. Jaynes Information Theory and Statistical Mechanics , 1957 .

[7]  W. Boehm,et al.  Bezier and B-Spline Techniques , 2002 .

[8]  T. Belytschko,et al.  Element‐free Galerkin methods , 1994 .

[9]  R. DeVore The Approximation of Continuous Functions by Positive Linear Operators , 1972 .

[10]  M. Ortiz,et al.  Subdivision surfaces: a new paradigm for thin‐shell finite‐element analysis , 2000 .

[11]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[12]  Wing Kam Liu,et al.  Reproducing kernel particle methods , 1995 .

[13]  Klaus Höllig,et al.  Introduction to the Web-method and its applications , 2005, Adv. Comput. Math..

[14]  Alessandro Reali,et al.  Isogeometric Analysis of Structural Vibrations , 2006 .

[15]  Ding-Xuan Zhou,et al.  Global smoothness preservation and the variation-diminishing property , 1999 .

[16]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[17]  T. Hughes,et al.  Isogeometric analysis : CAD, finite elements, NURBS, exact geometry and mesh refinement , 2005 .

[18]  N. Sukumar Construction of polygonal interpolants: a maximum entropy approach , 2004 .

[19]  R. Wright,et al.  Overview and construction of meshfree basis functions: from moving least squares to entropy approximants , 2007 .