Abstract

PurposeThis paper aims to develop a new method of fuselage drag optimization that can obtain results faster than the conventional methods based on full computational fluid dynamics (CFD) calculations and can be used to improve the efficiency of preliminary design.Design/methodology/approachAn efficient method for helicopter fuselage shape optimization based on surrogate-based optimization is presented. Two numerical simulation methods are applied in different stages of optimization according to their relative advantages. The fast panel method is used to calculate the sample data to save calculation time for a large number of sample points. The initial solution is obtained by combining the Kriging surrogate model and the multi-island genetic algorithm. Then, the accuracy of the solution is determined by using the infill criteria based on CFD corrections. A parametric model of the fuselage is established by several characteristic sections and guiding curves.FindingsIt is demonstrated that this method can greatly reduce the calculation time while ensuring a high accuracy in the XH-59A helicopter example. The drag coefficient of the optimized fuselage is reduced by 13.3%. Because of the use of different calculation methods for samples, this novel method reduces the total calculation time by almost fourfold compared with full CFD calculations.Originality/valueTo the best of the authors’ knowledge, this is the first study to provide a novel method of fuselage drag optimization by combining different numerical simulation methods. Some suggestions on fuselage shape optimization are given for the XH-59A example.

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