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Título: Stochastic modeling of uncertainties and experimental identification for complex dynamical structures

Palestrante: PhD. Anas Batou (Université Paris-Est - France)


DATA: Sexta-feira 26/02/2016


LOCAL: Centro de Tecnologia Bloco I, Sala: I241




Computational methods are widely used for the dynamical analysis and the design of complex structures such as automotive vehicles, aircrafts, launch vehicles, complex buildings, … For these structures, recent advances in mechanical modeling, numerical simulation, CAD and machine performance allow very detailed and advanced Finite Element (FE) models or flexible multibody models to be constructed. Ideally, these very large computational models allow to predict  accurately the complex dynamical behavior of these structures. However, the increase of the computational complexity is often accompanied with an increase of the possible sources of uncertainties related to (1) the numerous parameters controlling the computational model and (2) the model-form uncertainties. These uncertainties have to be taken into account in the modeling process in order to predict the quantities of interest with a good confidence.  This presentation is  devoted to some recent advances related to the probabilistic modeling and the experimental identification of uncertainties which are present in the complex computational models of dynamical structures, with a focus on the construction of the probabilistic models, the generators of independent realizations, the propagation of the randomness and the inverse probabilistic methods for the identification of the hyperparameters controlling the levels of fluctuation of the response. The first part of this presentation is devoted to methodologies adapted to the low-frequency range. Several industrial applications will be presented. In the mid-frequency range, the modal density and the sensitivity of the response with respect to uncertainties increase. A global/local probabilistic approach adapted to treat both the low- and the mid-frequency ranges, with separated probabilistic modelings, will also be presented.

Keywords: structural dynamics, uncertainties, model identification, high modal density.

About Prof. Anas Batou

2001--2005 Ecole Normale Supérieure de Cachan - Mechanical Engineering

2005--2008 Ph.D. from Université Paris-Est

2008--Now Assistant professor at Université Paris-Est.

Research interests:

Uncertainty quantification in structural dynamics and multibody dynamics.

Model reduction in LF/MF dynamics.

Generation of seismic accelerogramms.


Vibration and noise reduction.


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