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Methods for nonlinear vibration characterization by decomposing dynamic responses using the Hilbert–Huang transform and a sliding-window fitting technique are presented.
The material non-linearity was considered to get the static and dynamic responses using DDM.
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The natural frequencies, the corresponding modes and the dynamic responses used for the condensation can be obtained from finite element analysis of the original structure.
3D stochastic finite element method is employed to obtain the stochastic dynamic response using explicit time domain solver.
Two techniques, a joint input-state estimation algorithm (JIS) and a dual Kalman filter (DKF), are used to estimate the full-field dynamic response using data measured at the bridge and a reduced order structural model.
Main focus of the present study is to estimate vehicle parameters from bridge dynamic response using particle filtering technique.
Recognizing the practical significance of the research on moving load identification, efforts have been made to estimate vehicle load from the bridge dynamic response using various techniques to improve the accuracy.
On the opposite, monitoring the dynamic response using more than one time samples after the stimulus allows detecting these genes as differentially expressed and provides a description of the transcriptional expression patterns of the response.
Hence, for a set of appropriate initial conditions, the simulation of the dynamic response using either the model recast as a rGMA or the original model will produce the same trajectory.
For example, in 2010 she co-created Flock Logic, an art-making project that explored what happens when dancers carry out the mathematical rules for dynamic response used to model flocking birds.
In this paper, an experimental damage identification procedure based on structural dynamic responses and using smart sensors is conducted.
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