z-logo
open-access-imgOpen Access
Hybrid Simulation of a Frame Equipped with MR Damper by Utilizing Least Square Support Vector Machine
Author(s) -
Arash Sharghi,
Reza Karami Mohammadi,
Mojtaba Farrokh
Publication year - 2018
Publication title -
numerical methods in civil engineering
Language(s) - English
Resource type - Journals
eISSN - 2783-3941
pISSN - 2345-4296
DOI - 10.29252/nmce.2.3.58
Subject(s) - damper , frame (networking) , square (algebra) , support vector machine , computer science , structural engineering , engineering , control theory (sociology) , artificial intelligence , mechanical engineering , mathematics , geometry , control (management)
In hybrid simulation, the structure is divided into numerical and physical substructures to achieve more accurate responses in comparison to a full computational analysis. As a consequence of the lack of test facilities and actuators, and the budget limitation, only a few substructures can be modeled experimentally, whereas the others have to be modeled numerically. In this paper, a new hybrid simulation has been introduced utilizing Least Square Support Vector Machine (LS-SVM) instead of physical substructures. With the concept of overcoming the hybrid simulation constraints, the LS-SVM is utilized as an alternative to the rate-dependent physical substructure. A set of reference data is extracted from appropriate test (neumerical test) as the input-output data for training LS-SVM. Subsequently, the trained LSSVM performs the role of experimental substructures in the proposed hybrid simulation. Onestory steel frame equipped with Magneto-Rheological (MR) dampers is analyzed to examine the ability of LS-SVM model. The proposed hybrid simulation verified by some numerical examples and results demonstrate the capability and accuracy of this new hybrid simulation. D

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom