Abstract
In this paper, a new interpolating moving least square (IMLS) method is proposed which has the properties of moving least square (MLS) and the radial basis function (RBF). In the approach, the polynomial and the RBF are combined. The coefficients of the polynomial are obtained by MLS approximation and the coefficients of RBF are obtained through the condition that the interpolation function obtained passes through all scattered nodes in an influence domain. Thus shape functions preserve the Kronecker delta function property which makes the implementation of essential boundary conditions much easier than the meshless methods based on the MLS approximation. In addition, the diffuse derivatives instead of full derivative are applied for the derivatives of shape functions. Thus, the computational efficiency is improved. Examples on elasticity problems show that the present method has the same accuracy and convergence rate as MLS.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
