Abstract
Hypersonic vehicle has gained increasing attention due to its high cruise speed and long voyage. In this paper, an enhanced Sequential Approximate Optimization method is proposed for aerodynamic optimization of a hypersonic vehicle. In this method, a constrained design of experiment method is adopted to generate the initial sampling set with adequate number of feasible points. A field metamodel is proposed to surrogate the aerodynamic parameters distributions in the flow field obtained by the aerodynamic simulation. A hybrid metamodel combing radial basis functions and polynomial chaos expansion is applied to construct the field metamodel with good approximate performance. A robust mesh morphing scheme based on radial basis functions is developed to generate high-quality meshes for the sequential optimization scheme. The hypersonic vehicle aerodynamic optimization problem is performed using the proposed optimization framework and satisfactory results are obtained with limited computational budgets. Results show that the proposed field metamodel-enhanced Sequential Approximate Optimization method possesses powerful optimization performance and promising prospects in the field of hypersonic vehicle optimization design.
Highlights
Over recent decades, hypersonic vehicles have generally gained increasing attention because of potentially significant increases in range capabilities provided by their high lift-todrag ratio and superior break-defense capabilities provided by their high cruise speeds [1]
The aerodynamic optimization design problem of the hypersonic vehicle is carried out using the field metamodelenhanced Sequential Approximate Optimization (SAO) introduced in this paper
It is worth mentioning that, since there is no project background in this paper, the lifting body optimization design problems, including the lifting body shape, the objective function, and the constraints, are all built by the authors to verify the field metamodel and its enhanced SAO optimization framework proposed in this paper
Summary
Hypersonic vehicles have generally gained increasing attention because of potentially significant increases in range capabilities provided by their high lift-todrag ratio and superior break-defense capabilities provided by their high cruise speeds [1]. In modern aerodynamic design optimization applications, the high-fidelity computational fluid dynamic (CFD) simulation models have been widely used to improve the confidence and accuracy of analysis [12]. The conventional numerical optimization techniques such as evolutionary algorithms, which normally require thousands of model evaluations to yield an optimized design [14], are practically unacceptable in high-fidelity CFD simulation modeldriven aerodynamic optimization problems, especially for hypersonic vehicle optimization design problems, since that the CFD simulations of high-Mach number are time-consuming [15, 16]. The effectiveness and efficiency of SAO can be further improved in the sense that the coupling between the metamodel and the high-fidelity model can be further enhanced In this present paper, a field metamodel-enhanced SAO method is proposed for a hypersonic vehicle aerodynamic optimization design problem.
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