Multiphysics description of smart materials using a prismatic data-driven approach

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Authors: Vanderson Dornelas, Sergio A. Oliveira, Marcelo A. Savi
Cited by: 5
References: 87

Abstract

Smart materials are characterized by their ability to adapt to environmental changes due to the coupling among different physical domains. The hysteretic response is a typical behavior of smart materials, representing a challenging topic for its mathematical modeling. The literature presents different approaches to deal with this modeling, and the use of data-driven, experimental-based models is an alternative that avoids the characterization of material properties, presenting simplicity as the main advantage. This paper investigates the use of a data-driven prismatic approach for the multiphysics description of the smart material hysteretic behavior. The prismatic approach promotes an extension of the classical Preisach triangular domain, allowing a broader description of material behaviors. The Preisach model is based on mathematical operators that allow the definition of the Everett function to build a surface that describes the material behavior, characterizing the hysteresis. Subsequent interpolations allow the prismatic domain description. Numerical simulations are carried out and compared with experimental data available in the literature to investigate the capabilities of the model to represent the multiphysics hysteretic behavior of smart materials. On this basis, distinct smart materials are evaluated including shape memory alloys, magnetic materials and piezoelectric materials. Results show a close agreement between numerical and experimental data, demonstrating that the proposed model is a powerful tool to describe the multiphysics aspects of smart material complex behaviors.

Fields of Study & Subjects

Piezoelectric Actuators and Control Shape Memory Alloy Transformations Magnetic Properties and Applications

Publication details

Journal / source
International Journal of Mechanical Sciences
Publisher
Elsevier BV
Volume
311
Pages
111180–111180
Publication date
3 January 2026
Language
EN