Abstract
A new multi-fidelity modelling-based probabilistic optimisation framework for composite structures is presented in this paper. The multi-fidelity formulation developed herein significantly reduces the required computational time, allowing for more design variables to be considered early in the design stage. Multi-fidelity models are created by the use of finite element models, surrogate models and response correction surfaces. The accuracy and computational efficiency of the proposed optimisation methodology are demonstrated in two engineering examples of composite structures: a reliability analysis, and a reliability-based design optimisation. In these two benchmark examples, each random design variable is assigned an expected level of uncertainty. Monte Carlo Simulation (MCS), the First-Order Reliability Method (FORM) and the Second-Order Reliability Method (SORM) are used within the multi-fidelity framework to calculate the probability of failure. The reliability optimisation is a multi-objective problem that finds the optimal front, which provides both the maximum linear buckling load and minimum mass. The results show that multi-fidelity models provide high levels of accuracy while reducing computation time drastically.
Highlights
The conventional design approach for composite structures may cause the structures to be overdesigned because this approach involves the use of conservative safety factors to prevent structural failure
The multi-fidelity models were applied to the reliability analysis of the composite panel with respect to the linear buckling under eccentric load
The reliability analysis was carried out using Monte Carlo Simulation (MCS), First-Order Reliability Method (FORM) and SecondOrder Reliability Method (SORM)
Summary
The conventional design approach for composite structures may cause the structures to be overdesigned because this approach involves the use of conservative safety factors to prevent structural failure. The reliability analysis, which considers the uncertainty of each design variable, calculates the probability of failure of structures. Reliability-based design optimisation (RBDO), a probabilistic optimisation method involving reliability analysis, has been applied in the field of engineering because it provides the best possible design through considering each design uncertainty in random design variables during the optimisation process. The finite element method (FEM) and reliability analysis were used to conduct structural analyses and consider design uncertainties, respectively. This methodology provided reasonable solutions and proved to have a more economical computational cost. Lopez et al [5] applied RBDO and deterministic optimisation to a composite stiffened panel design. The hybrid mean value algorithm to find the most probable
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