Короткий опис(реферат):
EN: A challenging problem of Civil Engineering is the protection of buildings against dynamic loads and earthquake impacts. The advanced solutions employ
lightweight, material saving structures equipped with special damping devices. These devices
can be active or passive and their application depends, in general, on the investments for the
project. The active devices change their properties depending on the structural response and they
are the most expensive ones. On the other hand, passive devices are essentially cheaper and, in
many cases, require minimal costs of installation and maintenance.
Last decades, passive friction dampers are widely used for the earthquake protection of
multi-storey buildings . The friction dampers make use of the effect of solid friction to
dissipate the mechanical energy and to reduce the amplitude of the vibration of the structure. The
friction is developed between two solid bodies sliding in relation to one another. As usual, pairs
of metal, polymer or concrete components can be utilized. Determination of the optimal location
of friction dampers inside the building presents a complicated task for the practical design.
Purpose of the study. Several studies have been devoted to predicting the best properties
and placements of friction dampers (e.g., see papers and references therein). From the
mathematical point of view, this is a non-linear optimization problem and, in generally, such
problems can be nonconvex. They may be treated by different methods; for a general overview
of the subject we refer, for example, to the well-known books . In recent years, the methods
of artificial collective intelligence are rapidly developed providing a number of advantages
comparing to the classical procedures . In this study, a new approach to determine the optimal
location of friction dampers is proposed basing on the method of particle swarm optimization
(PSO). The PSO method presents an artificial simulation of the phenomenon of collective
intelligence, which is observed in many decentralized biological systems like ant colonies, bee
swarms, flocks of birds and even social groups of human individuals.
