Buckling analysis of axially functionally graded carbon nanotubes-reinforced columns using the meshless method

The spread of different material processing technologies has led to the novel methods developed for reinforcing structural members. One these approaches is add carbon nanotubes (CNTs) with distributions through matrix phase composite materials improve its properties. Due superior properties such as lightweight and high values elastic modulus, strain, failure CNTs can be used reinforce structures elements. present paper aims investigate effect adding reinforcement on buckling capacity columns. meshless local Petrov-Galerkin (MLPG) method applied analysis CNT-reinforced Since MLPG uses some scattered nodes domain boundaries discretization (rather than meshing), functionally graded (FG) variation conveniently modeled under influence elements (CNTs). Four types volume fraction exponent functions are considered modeling FG CNT examine distribution column determine most optimal CNTs. Effective mechanical estimated based extended rule mixture. Results show that polymer a low appropriate significantly increase capacity. Using obtained results, one best pattern in longitudinal direction at various boundary conditions.