TY - JOUR
T1 - Robust topology optimization of continuous structures using the Bernstein approximation
AU - Canelas, Alfredo
AU - Carrasco, Miguel
AU - López, Julio
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/10
Y1 - 2025/10
N2 - We propose a robust formulation for the topology optimization of continuous structures. The objective is to determine the optimal distribution of a linear elastic material within a reference domain subjected to both stochastic and deterministic external loads. A key feature of this formulation is the incorporation of a failure probability constraint defined in terms of compliance. The Bernstein approximation is used to derive an upper bound on the failure probability, yielding a more tractable formulation. By using the Solid Isotropic Material with Penalization (SIMP) method, where the material density is the main design variable, we reformulate the original stochastic optimization problem into a standard nonlinear optimization problem. We develop a numerical algorithm to solve this reformulation by iteratively solving a sequence of linear conic subproblems, which can be efficiently handled in polynomial time via interior-point methods. Numerical experiments demonstrate the effectiveness of the proposed approach.
AB - We propose a robust formulation for the topology optimization of continuous structures. The objective is to determine the optimal distribution of a linear elastic material within a reference domain subjected to both stochastic and deterministic external loads. A key feature of this formulation is the incorporation of a failure probability constraint defined in terms of compliance. The Bernstein approximation is used to derive an upper bound on the failure probability, yielding a more tractable formulation. By using the Solid Isotropic Material with Penalization (SIMP) method, where the material density is the main design variable, we reformulate the original stochastic optimization problem into a standard nonlinear optimization problem. We develop a numerical algorithm to solve this reformulation by iteratively solving a sequence of linear conic subproblems, which can be efficiently handled in polynomial time via interior-point methods. Numerical experiments demonstrate the effectiveness of the proposed approach.
KW - Bernstein approximation
KW - Chance constrained optimization
KW - Conic programming
KW - Topology optimization
UR - https://www.scopus.com/pages/publications/105014472542
U2 - 10.1016/j.compstruc.2025.107939
DO - 10.1016/j.compstruc.2025.107939
M3 - Article
AN - SCOPUS:105014472542
SN - 0045-7949
VL - 317
JO - Computers and Structures
JF - Computers and Structures
M1 - 107939
ER -