TY - JOUR
T1 - Stochastic topology design optimization for continuous elastic materials.
AU - Carrasco, Miguel
AU - Ivorra, Benjamin
AU - Ramos, Angel Manuel
N1 - Funding Information:
This work was carried out thanks to the financial support of the “Universidad de los Andes”; the Spanish “Ministry of Economy and Competitiveness” under project MTM2011-22658; the research group MOMAT (Ref. 910480) supported by “Banco Santander” and “Universidad Complutense de Madrid”; the “Junta de Andalucía” and the European Regional Development Fund under project P12-TIC301; and the “FONDECYT” under grant 1130905.
Publisher Copyright:
© 2015 Elsevier B.V.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - In this paper, we develop a stochastic model for topology optimization. We find robust structures that minimize the compliance for a given main load having a stochastic behavior. We propose a model that takes into account the expected value of the compliance and its variance. We show that, similarly to the case of truss structures, these values can be computed with an equivalent deterministic approach and the stochastic model can be transformed into a nonlinear programming problem, reducing the complexity of this kind of problems. First, we obtain an explicit expression (at the continuous level) of the expected compliance and its variance, then we consider a numerical discretization (by using a finite element method) of this expression and finally we use an optimization algorithm. This approach allows to solve design problems which include point, surface or volume loads with dependent or independent perturbations. We check the capacity of our formulation to generate structures that are robust to main loads and their perturbations by considering several 2D and 3D numerical examples. To this end, we analyze the behavior of our model by studying the impact on the optimized solutions of the expected-compliance and variance weight coefficients, the laws used to describe the random loads, the variance of the perturbations and the dependence/independence of the perturbations. Then, the results are compared with similar ones found in the literature for a different modeling approach.
AB - In this paper, we develop a stochastic model for topology optimization. We find robust structures that minimize the compliance for a given main load having a stochastic behavior. We propose a model that takes into account the expected value of the compliance and its variance. We show that, similarly to the case of truss structures, these values can be computed with an equivalent deterministic approach and the stochastic model can be transformed into a nonlinear programming problem, reducing the complexity of this kind of problems. First, we obtain an explicit expression (at the continuous level) of the expected compliance and its variance, then we consider a numerical discretization (by using a finite element method) of this expression and finally we use an optimization algorithm. This approach allows to solve design problems which include point, surface or volume loads with dependent or independent perturbations. We check the capacity of our formulation to generate structures that are robust to main loads and their perturbations by considering several 2D and 3D numerical examples. To this end, we analyze the behavior of our model by studying the impact on the optimized solutions of the expected-compliance and variance weight coefficients, the laws used to describe the random loads, the variance of the perturbations and the dependence/independence of the perturbations. Then, the results are compared with similar ones found in the literature for a different modeling approach.
KW - Finite element method
KW - Stochastic programming
KW - Structural optimization
KW - Topology optimization
UR - http://www.scopus.com/inward/record.url?scp=84924149481&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2015.02.003
DO - 10.1016/j.cma.2015.02.003
M3 - Article
AN - SCOPUS:84924149481
SN - 0045-7825
VL - 289
SP - 131
EP - 154
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
ER -