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For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system.
Simultaneously, the computation speed of improved mass model is 5 times more than that of initial mass model.
A simplified lumped mass model is proposed to study the two degree of freedom (dof) structural oscillator.
The deficiency of the moving mass model is principally that it fails to predict stresses in the supporting structure.
The lumped mass model is applied and an averaged tangential vector technique is included in the three-dimensional dynamic response equations of the cable-segments.
The lumped mass model is presented along with algorithms to solve the inverse problem, including truncated singular value decomposition, truncated generalized singular value decomposition and Tikhonov׳s method.
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Data gathered from the mass model are illustrated in Figure 2.
A mechanistic neural mass model was recently shown to display intermittent dynamic transitions reminiscent of absence seizures [7, 13].
Additionally, a lumped mass model was employed to determine the dynamic parameters of the heat exchanger using the experimental data.
Nonlinear static and dynamic state feedback linearization control for power optimization is addressed in [9, 10], where both the single and two mass model are taken into consideration and the wind speed is estimated by Newton Rapshon (NR) method.
We first consider the dynamics of individual nodes, which in the neural mass model were close to a bifurcation between qualitatively different oscillations, with a region of bistability between the two.
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