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