Variational Multiscale Proper Orthogonal Decomposition with Modular Regularization

Güler Eroğlu, Fatma
Kaya Merdan, Songül
Rebholz, Leo


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This paper presents the variational bases for the non-linear force-based beam elements. The element state determination of these elements is obtained exactly from a two-field functional with independent stress and strain fields. The variational base of the non-linear force-based beam elements implemented in a general purpose displacement-based finite element program requires the inclusion of independent displacement field in the formulation. For this purpose, a three-field functional is considered with inde...
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In this thesis, two Bayesian smoothers are proposed for random matrix based extended target tracking (ETT). The proposed smoothers are based on the variational Bayes techniques and they are derived for an extended target model without and with orientation. The random matrix models of Feldman et al. and Tuncer and Özkan are used as the extended target models without and with orientation, respectively. The performance of both smoothers is evaluated using simulation results on two different scenarios. It is se...
Citation Formats
F. Güler Eroğlu, S. Kaya Merdan, and L. Rebholz, “Variational Multiscale Proper Orthogonal Decomposition with Modular Regularization,” presented at the International Conference on Computational and Mathematical Methods in Science and Engineering (2017), Costa Ballena, Cádiz, Spain, 2017, Accessed: 00, 2021. [Online]. Available: