Robust topology optimization for fiber-reinforced composite structures under loading uncertainty

This paper focuses on robust topology optimization for fiber-reinforced composite structures under loading uncertainty. An effective method is presented for simultaneous optimization of fiber angles and structural topology. Specifically, a new parameterization scheme is developed to obtain the continuous spatial variation of fiber angles. The solid isotropic material with penalization method is employed to obtain the material distribution. The Monte Carlo simulation method is adopted to handle the uncertainty of loading magnitude and direction with probabilistic distributions. Subject to a volume fraction constraint, the problem of minimizing a weighted sum of the mean and standard deviation of structural compliance is investigated. Sensitivity analysis is conducted. To reduce the computational cost, Kriging metamodel is constructed to calculate the objective value and sensitivity information. Numerical examples are provided to demonstrate the effectiveness of the proposed method. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper focuses on robust topology optimization for fiber-reinforced composite structures under loading uncertainty, presenting an effective method for simultaneous optimization of fiber angles and structural topology. The study uses a new parameterization scheme and Monte Carlo simulation method to handle the optimization problem, sensitivity analysis, and Kriging metamodel for reducing computational cost.