Novel strategies for modal-based structural material identification

Accepted

Journal Article

© 2020 Elsevier Ltd In this work, we present modal-based methods for model calibration in structural dynamics, and address several key challenges in the solution of gradient-based optimization problems with eigenvalues and eigenvectors, including the solution of singular Helmholtz problems encountered in sensitivity calculations, non-differentiable objective functions caused by mode swapping during optimization, and cases with repeated eigenvalues. Unlike previous literature that relied on direct solution of the eigenvector adjoint equations, we present a parallel iterative domain decomposition strategy (Adjoint Computation via Modal Superposition with Truncation Augmentation) for the solution of the singular Helmholtz problems. For problems with repeated eigenvalues we present a novel Mode Separation via Projection algorithm, and in order to address mode swapping between inverse iterations we present a novel Injective mode ordering metric. We present the implementation of these methods in a massively parallel finite element framework with the ability to use measured modal data to extract unknown structural model parameters from large complex problems. A series of increasingly complex numerical examples are presented that demonstrate the implementation and performance of the methods in a massively parallel finite element framework [7,5], using gradient-based optimization techniques in the Rapid Optimization Library (ROL) [21].

Full Text

Duke Authors

Cited Authors

  • Bunting, G; Miller, ST; Walsh, TF; Dohrmann, CR; Aquino, W

Published Date

  • February 15, 2021

Published In

Volume / Issue

  • 149 /

Electronic International Standard Serial Number (EISSN)

  • 1096-1216

International Standard Serial Number (ISSN)

  • 0888-3270

Digital Object Identifier (DOI)

  • 10.1016/j.ymssp.2020.107295

Citation Source

  • Scopus