Improved Nonlinear Analysis of a Propeller Blade Based on Hyper-Reduction

Abstract

In this study, an improved nonlinear-analysis framework capable of predicting geometric nonlinearity and high-speed rotation in rotating structures was developed. A nonlinear time-transient simulation requires large computations owing to an iterative solution algorithm. To reduce the anticipated computational cost, a proper orthogonal decomposition (POD)-based reduced-order modeling (ROM) combined with hyper-reduction is applied. To efficiently perform computations during the online stage, three hyper-reduction techniques were employed to approximate the nonlinear finite-element matrices: discrete empirical interpolation method (DEIM), Gauss–Newton with approximated tensors (GNAT), and energy-conserving sampling and weighting (ECSW). The present frameworks are applied to the time-transient simulation of a propeller, including parametric variations. Compared with the DEIM method, the GNAT and ECSW methods exhibited better enhancement of the accuracy and robustness of the reduced-order representation. Additionally, the computational efficiency of the ECSW method was improved significantly compared with that of other POD-based ROM approaches.