Cyclic behavior of materials is complex and difficult to model. A combination of hardening
rules in classical plasticity is one possibility for modeling this complex material behavior …

The computer simulation is replacing mechanical experiments in many cases due to its cost-
effectiveness and improved accuracy. Nevertheless, its application fields are still limited to …

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems.
The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous …

Hysteresis is a highly nonlinear phenomenon, which is observed in different branches of
sciences. The behavior of the hysteretic systems is usually controlled by some …

Several different data-driven strategies for nonlinear identification are applied to
experimental data exhibiting various types of hysteretic behavior. The experimental data …

A novel and simple approach to modeling hysteresis nonlinearities is proposed. The
continuous transformation technique is used to construct an elementary hysteresis model …

In this paper, a new kind of activation function using a particular combination of stop and
play operators is proposed and used in a feedforward neural network to improve its learning …

Neural network (NN) based constitutive models can capture non‐linear material behaviour.
These models are versatile and have the capacity to continuously learn as additional …

Due to the increasing use of complex materials in lightweight structures, the development
and identification of proper material models for the prediction of damage and failure within …

An evolutionary algorithm-based artificial neural network (ANN) to identify structural damage
and nonlinear hysteresis parameters simultaneously is presented. To avoid the 'dimensional …