Niko Schmidt | Searcharxiv

arXiv2024

Coefficient identification of the regularized p-Stokes equations

The Antarctic and Greenland ice sheet simulation is challenging due to unknown parameters in the $p$-Stokes equations. In this work, we prove the existence of a solution to a parameter identification for the ice rheology and the friction coefficient. Additionally, we verify G\^ateaux differentiability of the coefficient-to-state operator by extending a similar result for distributed control. Moreover, we have more complicated boundary conditions. We only have to add a small diffusion term and assume the nonlinear exponent, which is given in applications, to be small enough to obtain the results. Finally, we state the adjoint equation and prove existence and uniqueness of a solution for this equation.

math.OC↗

arXiv2023

Global convergence of Newton's method for the regularized $p$-Stokes equations

The motion of glaciers can be simulated with the $p$-Stokes equations. Up to now, Newton's method to solve these equations has been analyzed in finite-dimensional settings only. We analyze the problem in infinite dimensions to gain a new viewpoint. We do that by proving global convergence of the infinite-dimensional Newton's method with Armijo step sizes to the solution of these equations. We only have to add an arbitrarily small diffusion term for this convergence result. We prove that the additional diffusion term only causes minor differences in the solution compared to the original $p$-Stokes equations under the assumption of some regularity. Finally, we test our algorithms on two experiments: A reformulation of the experiment ISMIP-HOM $B$ without sliding and a block with sliding. For the former, the approximation of exact step sizes for the Picard iteration and exact step sizes and Armijo step sizes for Newton's method are superior in the experiment compared to the Picard iteration. For the latter experiment, Newton's method with Armijo step sizes needs many iterations until it converges fast to the solution. Thus, Newton's method with approximately exact step sizes is better than Armijo step sizes in this experiment.

math.NA↗