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The substructuring methods have been popularly used in model updating, system identification and damage assessment.
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This work focuses on the model updating of rotor systems at various speeds as well as at different modes of vibration.
In the proposed iterative method, each of the improved equations is solved by a robust iterative technique named as least squares minimal residual (LSMR) to compute structural discrepancy matrices after transforming linear matrix systems of the model updating equations into linear vector systems.
This paper focuses on the model updating of complex structural systems.
This work attempts experimental studies in finite element model updating of an actual rotor system mounted on ball bearings by using Inverse Eigen Sensitivity Method (IESM).
Markov chain Monte Carlo (MCMC) simulation is applied for model updating of the coupled-slab system of a building structure based on field test data following the Bayesian theory.
This paper proposes data fusion of translational and rotational responses for improved system identification using FE model updating technique.
A probabilistic system identification technique is employed for model updating using incomplete noisy measurements only.
Model updating is, therefore necessary so that updated model should replicate the physical system.
The updated results have shown that the complex updating finite element model updating procedure can be used to derive an accurate model of the system.
The updated system reliability is then obtained through coupling the updated deterioration model with a probabilistic structural model.
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