Stress-based topology optimization considering error estimates
Guilherme Varella1; Jun Sérgio Ono Fonseca1
1 UFRGS - Dep. Mechanical Engineering
doi:10.20906/CPS/CILAMCE2015-0902
Resumo
This work presents a methodology for stress-constrained topology optimization, focusing on the employment of methodologies to improve the computational processing performance. Structural analysis is accomplished by the finite element method, and stress is computed at the elemental Gaussian integration points, and then smoothed over the mesh. In order to avoid the stress singularity phenomenon a constitutive tensor penalization is employed. A normalized version of the p-norm is used as a global stress measure instead of local stress constraint. A finite element error estimator is considered in the stress constraint calculation. In order to solve the optimization process, Sequential Linear Programming is employed, with all derivatives being calculated analytically. A criterion is proposed to remove low density elements, contributing for well-defined structures and reducing significantly the computational time. Checkerboard instability is circumvented with a linear density filter. To reduce the computational time and enhance the performance of the code, a surrogate model is used in inner iterations of the Sequential Linear Programming. The results obtained applying the present algorithm are compared with results by other authors, thus verifying the validity of the procedure.
Palavras-chave: topology optimization; stress constraint; surrogate model; error estimator