Model-order Reduction using Operator Inference Approach for Aeromechanics Analysis of Rotorcraft

Forward flight rotorcraft analyses typically require time-marching aeroelastic trim of coupled rotor-airframe models, which is expensive for repeated evaluations. This paper presents a non-intrusive model-order reduction framework based on Dynamic Mode Decomposition with control (DMDc) identified from snapshot data. A POD projection reduces the state dimension; the DMDc operators are identified in the reduced coordinates and used for fast time-marching. Two sequential maps are constructed: DMDc-A reconstructs aeroelastic sectional airloads from low-cost rigid-blade airloads, and DMDc-S predicts coupled deformation, including blade and airframe degrees of freedom (DOFs), from the reconstructed airloads. The method is demonstrated for the XV-15 airplane mode configuration using a stick airframe model and a coupled rotor-airframe solver. Over 160-400 knots, it is found that the surrogate reproduces blade airloads and structural deformation of blade and airframe.