Aeroelastic Design and Comprehensive Analysis of Composite Rotor Blades Through Cluster-Based Kriging

Abstract

Excessive vibration during high-speed flights is a critical issue in modern rotorcraft. The aeroelastic design of the composite rotor blades can relieve the hub vibratory loads of the rotor that are a dominant source of these vibrations. However, it has many technical problems, such as a high-dimensional design space, narrow and discontinuous feasible regions, and highly nonlinear design indices. Although the surrogate-based design is known to improve the design results, the conventional surrogate models have an insufficient capacity to represent the nonlinearity of aeroelastic responses. Because the inaccuracy of the surrogate model is combined with the discontinuity of feasible regions during the optimization process, it is likely to converge to local optima. Cluster kriging could accurately represent the complicated physical relations using machine learning techniques, such as soft clustering and classification algorithms. The accurate surrogate model results in a global optimization with 56% vibration reduction, whereas the global approximation using a single kriging yields local optima with 39% vibration reduction. Furthermore, a comprehensive design analysis, conducted to investigate the underlying physics of the vibration reduction, confirms the global optimization. The proposed design method can fully use the multidisciplinary nature of aeroelastic responses, which is not considered in conventional design methods.