In this paper a numerical method is developed to find the eigenvalues of the Laplacian matrix for near-regular graph models. Considering the similarity between the pattern of the
IntroductionAlthough the advent of powerful computers have smoothened the way for the swift computations structural/mechanical systems, the analysis of complicated systems are still laborious and time-consuming. Many algorithms for the solutions of largescale structural/mechanical systems have been developed over the past three decades. These algorithms have mainly aimed to find efficient solutions for the structural governing equations (i.e. F = K∆) and/or eigensolution of a system (i.e. frequencies of free vibration). However, due to the variety of systems and lack of general patterns, most algorithms are limited to partial applications. The most successful advancements were achieved in the solution of symmetric and regular patterns wherein linear algebra, graph products, group theoretical method, U-transformation etc. were employed to divide complicated large problems into sub-systems and solve the smaller parts with less computational complexity and then combine the solutions (i.e. divide and conquer methods) [1][2][3][4][5][6][7].There are various structural/mechanical systems with geometries close to those of regular structures, but not satisfying the required mathematical conditions to be considered as regular. A model is called regular if it can be considered as the product of two or three graphs [1]. A near regular model consists of a regular submodel with limited number of members and/or nodes being added or removed. Recent efforts have been devoted to realize, classify and solve these near-regular patterns efficiently through the available solution of the regular part [8][9][10][11][12]. While several flexibility and stiffness methods, and finite difference and finite element formulations were developed to solve the final governing equation F = K∆, less success were achieved for the eigensolution of the near-regular systems [8][9][10][11][12]. Compared to the solution of F = K∆, eigenvalue problems are more sensitive to the algebraic manipulations. This often leads to matrices with general patterns that cannot usually be solved using specific efficient solvers.In this paper a numerical algorithm is presented for obtaining the eigenvalues of near-regular structures. In this method utilizing the decomposition of block matrices, a determinant equation is obtained. This equation includes separate submatrices corre-