Non-probabilistic reliability-based topology optimization against loading uncertainty field with a bounded field model

This paper presents a non-probabilistic reliability-based topology optimization under the distributed loading uncertainty, in which the loading uncertainty is described as the non-probability bounded field model. The reliability-based optimization model is a nested optimization process, in which the inner-loop optimization problem is to evaluate the structural reliability under the loading field uncertainty. Based on material-field series-expansion (MFSE) optimization method, the outer-loop optimization problem is expressed as determining the optimum structural topology that minimizes structural volume under the non-probability reliability index constraint. The nested optimization problem is solved via a gradient-based optimization algorithm. To reduce the computational cost of the optimization model, the concerned performance approach is employed to transform the non-probabilistic reliability-based optimization model equivalently. Three numerical examples considering uncertain loading field (including 2D and 3D structures) are given to illustrate the validity of the proposed method.

Automated summary

This paper presents a non-probabilistic reliability-based topology optimization method under distributed loading uncertainty, evaluating the structural reliability and determining the optimum topology to minimize structural volume. The nested optimization problem is solved using a gradient-based algorithm, and the computational cost is reduced using the concerned performance approach. Numerical examples demonstrate the effectiveness of the proposed method.