Summary
In this paper, experimental data from tests of a helical fluid inerter are used to model the observed hysteretic behavior. The novel idea is to test the feasibility of employing mem‐models, which are time‐invariant herein, to capture the observed phenomena by using physically meaningful state variables. First, we use a Masing model concept, identified with a multilayer feedforward neural network to capture the physical characteristics of the hysteresis functions. Following this, a more refined problem formulation based on the concept of a multi‐element model including a mem‐inerter is developed. This is compared with previous definitions in the literature and shown to be a more general model. Throughout this paper, numerical simulations are used to demonstrate the type of dynamic responses anticipated using the proposed time‐invariant mem‐models. Corresponding experimental measurements are processed to demonstrate and justify the new mem‐modeling concepts. Focusing on identifying the unknown function forms in the proposed problem formulations, the results show that it is possible to formulate a unified model constructed using both the damper and inerter from the mem‐model family. This model captures many of the more subtle features of the underlying physics, not captured by other forms of existing model.