The fundamental solution, or Green's function, for 3D anisotropic elastostatics as derived by Ting and Lee (1997) [Q.J. Mech. Appl. Math.; 50: 407-426] is one that is fully explicit and algebraic in form. It has, however, only been utilized in boundary element method (BEM) formulations quite recently even though it is relatively straightforward and direct to implement. This Green's function and its derivatives are necessary items in this numerical analysis technique. By virtue of the periodic nature of the angles when it is expressed in the spherical coordinate system, the present authors have very recently represented the Green's function as a double Fourier series for their efficient numerical evaluation. The Fourier coefficients are determined only once, independent of the total number of field points involved in the BEM analysis of a problem. The derivatives of the fundamental solution can also be obtained simply by direct spatial differentiation of the double Fourier series without further numerical or significant analytical steps. This paper presents a re-formulation of the same scheme by taking advantage of some characteristic features of the Fourier coefficients and re-arranging and simplifying the terms. In so doing, the total number of terms necessary for the series summation is significantly reduced thereby enhancing further its computational efficiency, especially when large number of field points are involved as is typically the case when modeling practical engineering problems. Numerical examples are presented to demonstrate the veracity of the proposed scheme. It is also simpler to implement into BEM codes because of the formulation is considerably less elaborate as compared to the direct evaluation approaches of the exact analytical solution, its full explicit algebraic form notwithstanding.
|Number of pages||22|
|Journal||CMES - Computer Modeling in Engineering and Sciences|
|Publication status||Published - 2012 Dec 19|
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Computer Science Applications