5 papers · 1 filter
Full-Field Calibration of Coupled Thermomechanical Material Models at Finite Strain
L. River Spencer, William D. Meador, Adrian Buganza Tepole +5
Calibrating thermomechanical material models from experiments is challenging because deformation, temperature, and force responses are strongly coupled, while measurements are usua…
Stable Long-Horizon Neural ODE Reduced-Order Models via Learned Feedback for Biological Growth and Remodeling
Joel Laudo, Adrian Buganza Tepole
Reduced-order models (ROMs) are essential for rapid simulation of complex biomechanical systems and for bridging the gap between high fidelity models and clinical application. Howe…
A Differentiable Framework for Gradient Enhanced Damage with Physics-Augmented Neural Networks in JAX-FEM
Mark Wilkinson, Amirhossein Amiri-Hezaveh, Adrian Buganza Tepole
Soft materials such as rubbers, hydrogels, and biological tissues undergo damage in the form of stiffness degradation without apparent changes in their stress-free geometry. Accura…
Polyconvex Physics-Augmented Neural Network Constitutive Models in Principal Stretches
Adrian Buganza Tepole, Asghar Jadoon, Manuel Rausch +1
Accurate constitutive models of soft materials are crucial for understanding their mechanical behavior and ensuring reliable predictions in the design process. To this end, scienti…
A universal material model subroutine for soft matter systems
Mathias Peirlinck, Juan A. Hurtado, Manuel K. Rausch +2
Soft materials play an integral part in many aspects of modern life including autonomy, sustainability, and human health, and their accurate modeling is critical to understand thei…