scholarly journals A Combined Analytical Method for Intelligent Control of Friction Damped Structures

2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Kamyar Gharra ◽  
Karen Khanlari ◽  
Jafar Asgari Marnani

Controlling structures and increasing the prognosis of their behaviour before natural disasters are the most critical issues in structural engineering. To that end, predicting the destructive effects of earthquakes on both acceleration and displacement of structures would be beneficial. This paper suggests an intelligent control system that realises simultaneous control of acceleration and displacement parameters. There are two modules in the system. First, the preserving module aims to estimate the crisis thresholds of acceleration and displacement based on the historical seismic data of each area. Second, the processing module finds the optimum value of the slip load of the friction damper so that both acceleration and displacement are controlled. We introduce an analytical method based on a matrix analysis approach and heuristic algorithm (MAHA) as a core of the processing module. MAHA would analyse the structure response, and the friction damper would determine the optimum slip load. The numerical and software simulation results for various one-bay and two-bay steel structures show that the proposed intelligent control system applies to multiple frictions damped structures under different earthquake records. In addition, a control level of 80% in acceleration and displacement of structures is achieved compared to an uncontrolled state. Moreover, the mentioned system enables the engineers to find appropriate friction dampers during the design of structures.

2020 ◽  
pp. 81-86
Author(s):  
Yu.G. Kabaldin ◽  
D.A. Shatagin ◽  
M.S. Anosov ◽  
A.M. Kuz'mishina

The formation of chips during the processing of various materials was studied. The relationship between the type of chips, the type of crystal lattice of the material and the number of sliding systems is shown. A neural network model of chip formation is developed, which allows predicting the type of chips. An intelligent control system for the process of chip formation during cutting is proposed. Keywords: chip formation, crystal lattice, neural network model, type of chips. [email protected]


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