Smart materials are upcoming in many industries due to their unique properties and wide range of applicability. These materials have the potential to transform traditional engineering practices by enabling the development of more efficient, adaptive, and responsive systems. However, smart materials are characterized by nonlinear behaviour and complex constitutive models, posing challenges in modelling and simulation. Therefore, understanding their mechanical properties is crucial for model-based design. This review aims for advancements in numerically implementing various smart materials, especially focusing on their nonlinear deformation behaviours. Different mechanisms and functionalities, classification, constitutive models and applications of smart materials were analyzed. In addition, different numerical approaches for modelling across scales were investigated. This review also explored the strategies and implementations for mechanically intelligent structures using smart materials. In conclusion, the potential model-based design methodology for the multiple smart material-based structures is proposed, which provides guidance for the future development of mechanically intelligent structures in industrial applications.

Grippers are widely used in many industrial applications, but are limited due to their rigid constructions and no adaptability to varying stiffness. The solution for this would be the use of soft grippers. One way to design soft grippers is to use smart materials, such as hydrogels. Hydrogel soft grippers, unlike their rigid counterparts, take advantage of smart materials' inherent responsiveness and adaptability, removing the need for external power components. To explore the possibilities of using smart hydrogel as the actuator in the soft gripper, we proposed a bilayer structure including temperature sensitive hydrogel and silicone. In order to get insight into the design of these configurations for a gripper, a model consisting of hydrogel was proposed to execute simulations using Finite Element Method (FEM) in Abaqus. The results show, that by modelling different configurations with temperature as input, information can be obtained about mechanical properties such as expansion and bending. Moreover, various forms of deformation can be attained through the utilization of programmable configurations. These configurations can be tailored to achieve deformations in diverse scenarios, including bulk material conveying or underwater applications.