113 citations · 243 across the 18 of their papers we have counts for
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Fully differentiable framework for inverse identification of geometry and material parameters with application to determining stress-free configuration of soft tissues
Hyunoh Bae, Tianyi Hu, Adrian Buganza Tepole +1
Medical images of soft tissues typically depict loaded configurations rather than true unloaded (stress-free) states, which can bias biomechanical simulations and inverse material…
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…