A novel multi-fidelity modelling-based framework for reliability-based design optimisation of composite structures

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.

Condition Assessment Techniques for Aged Fixed-Type Offshore Platforms Considering Decommissioning: a Historical Review

“…It helps to approximate the probability of an event from a stochastic process. Many researchers utilised this technique in offshore engineering as an alternative to evaluate the safety of the structures (Kolios 2010;Cossa et al 2012;Kurian et al 2013a;Yoo et al 2020). Though it is believed to give crude values, yet it is well adopted due to its simplicity (Veritas 1992).…”

How machine learning can help the design and analysis of composite materials and structures?

“…Another solution is to keep developing more efficient yet accurate multiscale modeling approaches such as MSG, MHT and some reduced-order models (e.g., self-consistent clustering analysis [106], proper orthogonal decomposition (POD) reduced model [107], and non-uniform transformation field analysis [108]). Recently, the multi-fidelity modeling has been used to effectively generate training data for ANN models in composite materials and structures [109][110][111], which provides another approach to balance the accuracy and efficiency in training an ANN model [112]. Also, it would be attractive if a model can be tuned for both low-and high-fidelity models [113].…”

“…The former one concerns the probability of constraints satisfaction because of the randomness of variables, while the latter one tries to reduce the effects from random variables on the change of objectives. For the ANN-based composites design community, though RBDO has received much attention in recent years [110,123,145,146], research on RDO is still in its very early stage. Besides, regarding to the source of uncertainties, most studies focused on the design variables, and little has been done for quantifying uncertainties of the ANN model itself.…”

Reliability-based bottom-up manufacturing cost optimisation for composite aircraft structures

“…Although it is important to take into account manufacturing cost when designing a composite part, the safety/ reliability of the part is also a very important consideration to take into account as well, especially for parts used in aircraft. There are many examples in which the reliability of a structure is optimised under the presence of uncertainties (Farokhi et al 2020;Yoo et al 2020;Bacarreza et al 2014;Lopez et al 2016;Simoes et al 2006;Hu et al 2016). One notable example is (Farokhi et al 2020) in which the geometric design of an aircraft mono-stringer compositestiffened panel was optimised based on reliability.…”

“…Reliability was estimated based on buckling behaviour and under the presence of uncertainties in composite material properties. Another notable example is (Yoo et al 2020) in which a multi-fidelity modelling-based approach was taken to the reliability optimisation of another composite aircraft mono-stringer composite-stiffened panel. The multi-fidelity approach was found to significantly improve the efficiency of the optimisation process.…”