25 citations · 36 across the 3 of their papers we have counts for
5 papers
Well-posed by Design: Learning Constitutive Laws from Velocity Data using Convex Neural Network Potentials
Gonzalo G. de Diego, Georg Stadler
Learning constitutive laws of complex fluids from velocity data (i.e. indirect observations) is a PDE-constrained inverse problem in which expressive neural parameterizations risk…
Transform before linearizing: robust Newton methods for singular -Laplace and -Stokes equations
Gonzalo G. De Diego, Fortino Garcia, Georg Stadler +1
For , the -Laplace equation and its -Stokes generalization are difficult to solve numerically. Newton's method converges rapidly only close to the solution, with itera…
Modeling sea ice in the marginal ice zone as a dense granular flow with rheology inferred from discrete element model data
Gonzalo G. de Diego, Mukund Gupta, Skylar A. Gering +2
The marginal ice zone (MIZ) represents the periphery of the sea ice cover. In this region, the macroscale behavior of the sea ice results from collisions and enduring contact betwe…
Numerical approximation of viscous contact problems applied to glacial sliding
Gonzalo G. de Diego, Patrick E. Farrell, Ian J. Hewitt
Viscous contact problems describe the time evolution of fluid flows in contact with a surface from which they can detach and reattach. These problems are of particular importance i…
On the finite element approximation of a semicoercive Stokes variational inequality arising in glaciology
Gonzalo G. de Diego, Patrick E. Farrell, Ian J. Hewitt
Stokes variational inequalities arise in the formulation of glaciological problems involving contact. We consider the problem of a two-dimensional marine ice sheet with a grounding…