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Finite Element Model Updating in Structural Dynamics

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TLDR
A comparison of Numerical Data with Test Results and Iterative Methods Using Modal Data for Model Updating shows that the former is more accurate than the latter.
Abstract
Preface. 1. Introduction. 2. Finite Element Modelling. 3. Vibration Testing. 4. Comparing Numerical Data with Test Results. 5. Estimation Techniques. 6. Parameters for Model Updating. 7. Direct Methods Using Modal Data. 8. Iterative Methods Using Modal Data. 9. Methods Using Frequency Domain Data. 10. Case Study: an Automobile Body M. Brughmans, J. Leuridan, K. Blauwkamp. 11. Discussion and Recommendations. Index.

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Journal ArticleDOI

An optimization technique for damped model updating with measured data satisfying quadratic orthogonality constraint

TL;DR: This contribution includes mathematically proved results to demonstrate that Stage I is essential to obtain a symmetric updated matrix K in Stage II, unless, of course, the measured eigenvector matrix is such that the orthogonality constraint has been already satisfied, which is extremely unlikely to happen in practice.
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Finite element method based Monte Carlo filters for structural system identification

TL;DR: In this article, the authors combine finite element method (FEM) for structural analysis and particle filtering for dynamic state estimation to tackle the problem of structural system parameter identification based on a set of noisy measurements on static and dynamic structural responses.
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Improving Knowledge of Structural System Behavior through Multiple Models

TL;DR: An analysis of error sources that are used to define model populations is presented, showing the need for such an approach even when a single conservative model has been appropriate for design.
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Long-Term Modal Analysis of Wireless Structural Monitoring Data from a Suspension Bridge under Varying Environmental and Operational Conditions: System Design and Automated Modal Analysis

TL;DR: Structural monitoring systems installed on cable-supported bridges have the potential to generate large data repositories from which a deeper understanding of bridge behavior can be obtaine... as mentioned in this paper, which can be used for bridge behavior analysis.
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Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions

TL;DR: A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation in structural dynamics.