14 citations · 16 across the 4 of their papers we have counts for
6 papers
A structure-preserving discretisation of SO(3)-rotation fields for finite Cosserat micropolar elasticity
Lucca Schek, Peter Lewintan, Wolfgang Müller +5
We introduce a new method, dubbed Geometric Structure-Preserving Interpolation (-SPIN) to preserve physics-constraints inherent in the material parameter limits of the finite-st…
Cosserat micropolar and couple-stress elasticity models of flexomagnetism at finite deformations
Adam Sky, David Codony, Stephan Rudykh +3
We propose geometrically nonlinear (finite) continuum models of flexomagnetism based on the Cosserat micropolar and its descendent couple-stress theory. These models introduce the…
Hierarchical poromechanical approach to investigate the impact of mechanical loading on human skin micro-circulation
Thomas Lavigne, Stéphane Urcun, Bérengère Fromy +6
Research on human skin anatomy reveals its complex multi-scale, multi-phase nature, with up to 70% of its composition being bounded and free water. Fluid movement plays a key role…
Intrinsic mixed-dimensional beam-shell-solid couplings in linear Cosserat continua via tangential differential calculus
Adam Sky, Jack S. Hale, Andreas Zilian +2
We present an approach to the coupling of mixed-dimensional continua by employing the mathematically enriched linear Cosserat micropolar model. The kinematical reduction of the mod…
Enhancing Biomechanical Simulations Based on A Posteriori Error Estimates: The Potential of Dual Weighted Residual-Driven Adaptive Mesh Refinement
Huu Phuoc Bui, Michel Duprez, Pierre-Yves Rohan +4
The Finite Element Method (FEM) is a well-established procedure for computing approximate solutions to deterministic engineering problems described by partial differential equation…
A graph-based probabilistic geometric deep learning framework with online enforcement of physical constraints to predict the criticality of defects in porous materials
Vasilis Krokos, Stéphane P. A. Bordas, Pierre Kerfriden
Stress prediction in porous materials and structures is challenging due to the high computational cost associated with direct numerical simulations. Convolutional Neural Network (C…