By Fikret Necati Catbas
This fourth quantity of 8 from the IMAC - XXXII convention, brings jointly contributions to this crucial quarter of study and engineering. the gathering provides early findings and case stories on primary and utilized features of Structural Dynamics, together with papers on:
- Linear Systems
- Substructure Modelling
- Adaptive Structures
- Experimental Techniques
- Analytical Methods
- Damage Detection
- Damping of fabrics & Members
- Modal Parameter Identification
- Modal trying out Methods
- System Identification
- Active Control
- Modal Parameter Estimation
- Processing Modal Data
Read or Download Dynamics of Civil Structures, Volume 4: Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014 PDF
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Extra info for Dynamics of Civil Structures, Volume 4: Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014
Following the control law defined by Fig. 5, and using Rmi n D 7 and Rmax D 100 we obtain the experimental results are gathered in Fig. 8. A passive device was also tested by setting an optimal RL D 21 . A reduction of the primary system response between 3 and 15 % is achieved by using the adaptive control law instead of a passive device, the minimum reduction corresponding to the neighbourhood of the fixed points. The harvested power when using the adaptive scheme is above the 50 mW limit for all tested frequencies.
In this paper we consider replacing the damper in the TMD with an electrical generator device. In its simplest form this device could be a motor/generator with a resistive load such that the velocity- force relationship is approximately proportional hence mimicking a viscous damper. Here we consider using a voice-coil linear actuator connected to an impedance emulator, which is capable of harvesting, rather than dissipating, some of the vibrational energy. We discuss how this harvested power can then be used to modify the resistive loading in real-time and hence allow a wider bandwidth of operation.
40 GHz) machine with 16 GB working memory. The step size s of the predictor is reduced if there is no convergence in the corrector steps or there is a too big deviation from the calculated solutions to the step size criterion. The adoption of s for the next steps depends on the iterations done in the last turn and the target number of iterations. In Fig. 3 the frequency range of the turning point is shown. The continuous line corresponds to the exact curve in FEP (calculated by very small predictor steps).