Simulation of multi – field coupling damping characteristics of magnetorheological damper in ring system by artificial intelligence method

Abstract

A new kind of smart material called Magnetorheological (MR) has attracted a lot of attention among designers due to its mechanical properties that can alter in a controlled fashion by an external magnetic field. Regarding this issue, in the current work, for the first attempt, the dynamic stability of a sandwich shell made of MR core and graphene nanoplatelets reinforced composite (GPLRC) face sheets is presented. Using the role of the mixture and modified Halpin–Tsai model, the effective material properties of GPLRC face sheets are presented. Via Hamilton’s principle and linear viscoelastic theory, the governing equations of the current sandwich structure are developed. Also, compatibility equations for accurate modeling of the sandwich structure are presented. The discrete singular convolution integration method (DSC-IM) for prediction of nth-order derivatives of a sufficiently smooth function via weighted linear sum function of the amounts at each separated point in the throughout allowable input range is presented. For more verification, a deep neural network as an artificial intelligence method is presented. Finally, the results show that GPL’s weight fraction, viscoelastic foundation, the geometry of GPLs, and geometry of the structure have an important role in dynamic stability and modal loss factor parameter of sandwich shells.