Abstract
This paper presents a numerical strategy for reliability-based design optimisation of an aircraft wing structure using a surrogate-assisted approach. The design problem is set to minimise aircraft wing mass subject to structural and aeroelastic constraints, while design variables are structural dimensions. The problem has uncertainties in the material properties. The Kriging model is used for estimating the values of design functions. Two strategies of sampling technique are used, i.e., optimum Latin hypercube sampling (OLHS) with and without infill sampling. Uncertainty quantification is achieved by means of optimum normal distribution Latin hypercube sampling. The original design problem is converted to be a multiobjective optimisation problem. Optimum results show that OLHS with infill sampling gives a more accurate surrogate model; however, OLHS without infill sampling results in the better design solutions based on actual function evaluations.
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