Isnardi, I 
ORCID: 0000-0002-3362-0236, Menga, E, Mottershead, JE ORCID: 0000-0003-1279-2562 and Fichera, S ORCID: 0000-0003-1006-4959
(2021)
MODEL REDUCTION AND STOCHASTIC UPDATING OF A VIBRATING SYSTEM.
In: 32nd Congress of the International Council of the Aeronautical Sciences (ICAS2021), 2021-9-6 - 2021-9-10, Shanghai, China.
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Irma_paper_icas2021_final.pdf - Author Accepted Manuscript Download (1MB) | Preview |
Abstract
A two-level framework is demonstrated for stochastic model updating. At the first level, variance-based global sensitivity analysis is carried out with the purpose of identifying those parameters with significant uncertainty and those that might be considered deterministic and can be eliminated as inputs to the metamodel. Then, at the second level, an inverse problem is solved to determine the statistics of the parameters of a modification that causes numerical metamodel results to converge on experimental data. Model updating is carried on a second metamodel with only the significant parameters retained. The methodology makes use of the Woodbury formula, resulting in a set of nonlinear characteristic equations in the unknown terms. The framework methodology is applied to a simulated three degrees of freedom representation of an experimental rig. Complex-eigenvalue data is generated from known parameter distributions and bivariate output probability density functions are produced using kernel density estimation. By sampling from this data, estimates of the generating parameters and their distributions are recovered.
| Item Type: | Conference or Workshop Item (Unspecified) |
|---|---|
| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 06 Sep 2021 07:15 |
| Last Modified: | 18 Jan 2023 21:30 |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3135964 |
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