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Yves Govers
Researcher at German Aerospace Center
Publications - 60
Citations - 584
Yves Govers is an academic researcher from German Aerospace Center. The author has contributed to research in topics: Modal analysis & Modal. The author has an hindex of 11, co-authored 58 publications receiving 481 citations.
Papers
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Journal ArticleDOI
Stochastic model updating—Covariance matrix adjustment from uncertain experimental modal data
Yves Govers,Michael Link +1 more
TL;DR: In this paper, a method to adjust design parameter means and their related covariance matrix from multiple sets of experimental modal data is presented. But this method is restricted to a single set of test data.
Journal ArticleDOI
Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data
Edoardo Patelli,Yves Govers,Matteo Broggi,Herbert Martins Gomes,Michael Link,John E. Mottershead +5 more
TL;DR: In this article, two currently prominent stochastic model updating techniques (sensitivity-based updating and Bayesian model updating) are described and applied to the DLR AIRMOD structure.
Journal ArticleDOI
A multivariate interval approach for inverse uncertainty quantification with limited experimental data
Matthias Faes,Matteo Broggi,Edoardo Patelli,Yves Govers,John E. Mottershead,Michael Beer,Michael Beer,Michael Beer,David Moens +8 more
TL;DR: An improved version of a novel inverse approach for the quantification of multivariate interval uncertainty for high dimensional models under scarce data availability and a conceptual and practical comparison with the Bayesian results revealed that the selection of the most appropriate method depends largely on the desired information and availability of data.
Journal ArticleDOI
A comparison of two stochastic model updating methods using the DLR AIRMOD test structure
TL;DR: The interval method is found to be more conservative than the covariance approach but still provides useful estimates without restriction by any assumption of probability distribution.
A Review of Experimental Modal Analysis Methods with respect to their Applicability to Test Data of Large Aircraft Structures
TL;DR: In this paper, different modal analysis tools are investigated with respect to their applicability to test data from ground vibration tests (GVT) of large aircraft, including the Frequency Domain Direct Parameter Identification (FDPI), Least-Squares complex Exponential method (LSCE), and Least Squares Complex Frequency Domain method (LSCF or Poly MAX).