This work presents a general and efficient way of computing both diffuse an
d full derivatives of shape functions for meshless methods based on moving
least-squares approximation (MLS) and interpolation. It is an extension of
the recently introduced consistency approach based on Lagrange multipliers
which provides a general framework for constrained MLS along with robust al
gorithms for the computation of shape functions and their diffuse derivativ
es. The particularity of the proposed algorithms is that they do not involv
e matrix inversion or linear system solving. The previous approach is limit
ed to diffuse derivatives of the shape functions and not their full derivat
ives which are usually much more expensive to obtain. In the present paper
we propose to efficiently compute the full derivatives by a new algorithm b
ased on the formal differentiation of the previous one. In this way, we obt
ain a unified low-cost consistent methodology for evaluating the shape func
tions and both their diffuse and full derivatives. In the second part of th
e paper we introduce explicit forms of MLS shape functions in 1D, 2D and 3D
for an arbitrary number of nodes. These forms are especially useful for co
mparing finite element and MLS approximations. Finally we present a general
architecture of an MLS program. Copyright (C) 2000 John Wiley & Sons, Ltd.