Data-driven modelling of smart materials

Data-driven models and computational methods exhibit outstanding potential for future advancements in the modelling and simulation of complex and challenging engineering systems.

The ultimate goal of this project is to establish a data-driven modelling and simulation framework to predict complex electromechanical coupling phenomena in solids under complex electromechanical loading.

Thereby, classic constitutive models are replaced by (suitable) data and, as a long term goal, a computationally efficient prediction of electromechanical devices and systems is enabled.

Dissipative phenomena, as induced by microstructure evolution in, e.g., ferroelectrics, crucially influence the performance and efficiency of related smart devices. This similarly applies to time, respectively rate dependent phenomena in this class of materials.

Such dissipative phenomena as well as the prediction of complex, i.e. inhomogeneous states of deformation under electromechanical loading shall be included in the data-driven modelling approach in order to establish a powerful (next generation) simulation framework for advanced smart electromechanical systems and devices.