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This paper presents a new method for topology optimization of geometrical non- linear compliant mechanisms using the element-free Galerkin method(EFGM).The EFGM is employed as an alternative scheme to numerically solve the state equations by fully taking ad- vantage of its capability in dealing with large displacement problems.In the meshless method, the imposition of essential boundary conditions is also addressed.The popularly studied solid isotropic material with the penalization(SIMP)scheme is used to represent the nonlinear depen- dence between material properties and regularized discrete densities.The output displacement is regarded as the objective function and the adjoint method is applied to finding the sensitivity of the design functions.As a result,the optimization of compliant mechanisms is mathematically established as a nonlinear programming problem,to which the method of moving asymptotes (MMA)belonging to the sequential convex programming can be applied.The availability of the present method is finally demonstrated with several widely investigated numerical examples.
This paper presents a new method for topology optimization of geometrical non- linear compliant mechanisms using the element-free Galerkin method (EFGM). The EFGM is employed as an alternative scheme to numerically solve the state equations by fully taking advanage of its capability in dealing with large displacement problems. the meshless method, the imposition of essential boundary conditions is also addressed. popularly studied solidlyotropic materials with the penalization (SIMP) scheme is used to represent the nonlinear dependency between material properties and regularized discrete densities. the output displacement is regarded as the objective function and the adjoint method is applied to finding the sensitivity of the design functions. As a result, the optimization of compliant mechanisms is mathematically established as a nonlinear programming problem, to which the method of moving asymptotes (MMA) belonging to the sequential convex programming can be applied. availability of the present method is finally demonstrated with several widely investigated numerical examples.