Projects

Machine Learning Constitutive Response of Multiscale Fibrous Materials

Hi-fidelity multiscale simulations using frameworks such as MuMFiM are necessary to develop an understanding of fibrous materials on an engineering or biological scale. However, they require significant computational resources and HPC expertise that are out of reach for most biomechanicians. This project seeks to develop constitutive models for fibrous materials making use of machine learning methodologies.

Machine Learning Constitutive Response of Multiscale Fibrous Materials