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13 January 2012Determining the optimal number and position of damping viscose (MR) in seismic vibration control of buildings to use genetic algorithms (fuzzy engineering application)
In this paper, study optimization performance of damping semi-active viscose MR in order to reduce the seismic
vibrations of a building with 12 floors. For this purpose, we used genetic algorithms to obtain optimal number and
optimal situation in 15 major earthquakes with different frequency content through which final status damping are
determined. Investigating the influence of this type of damper on the construct dynamic response, the construct equation
has been written regarding dampers .Then, the aforesaid equation has been transmitted to the situational setting ,the
optimum quantity of each damper in the form of time function has been computed using optimization algorithm genetic
and, the construct response has been determined. The results show that different positions of optimal in the structure
height can have different effects on different responses. In a way that aligned damping in the upper parts of structures
although much reduced Roof floor shift but are less than the rate of decline in shear force base. It also aligned damping
in the bottom parts of structures are less than the rate of decline in base shear force roof and floor shift. Therefore, by
determining optimized position of optimal by genetic algorithms that can simultaneously optimize the rate of reduction
in the structure response.
Farzad Hatami andEsmail Karimi
"Determining the optimal number and position of damping viscose (MR) in seismic vibration control of buildings to use genetic algorithms (fuzzy engineering application)", Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83492M (13 January 2012); https://doi.org/10.1117/12.920259
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Farzad Hatami, Esmail Karimi, "Determining the optimal number and position of damping viscose (MR) in seismic vibration control of buildings to use genetic algorithms (fuzzy engineering application)," Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83492M (13 January 2012); https://doi.org/10.1117/12.920259