Topological Optimization of three-dimensional Structures using the methods of moving asymptotes and optimality criteria

Resumo

In structural optimization, one of the most fascinating fields is Topological Optimization (TO). In this
article, the evolutionary topological optimization methods Smoothing Evolutionary Structural Optimization (SESO)
and Sequential Element Rejection and Admission (SERA) are used to minimize the growth of compliance using the
Method of Moving Asymptotes (MMA) and the Optimality Criteria (OC) that applies the deterministic procedure
with lagrangian multipliers. The effect of changing asymptotes is to control the generation of subproblems, which can
both stabilize and accelerate the convergence of the overall process. The three- dimensional topological optimization
of the cantilever beam is performed. Therefore, to optimize the computational solution, such as cost and excess
memory, which occur in these types of problems, a Preconditioned Conjugated Gradient Method (PCG) is used as an
iterative solver. The results obtained are compared with the Solid Isotropic Material with Penalization (SIMP) that
uses for convergence the OC.