Adaptive and Iterative Methods for Simulations of Nanopores with the PNP-Stokes Equations
Gregor Mitscha-Baude, Andreas Buttinger-Kreuzhuber, Gerhard Tulzer,, Clemens Heitzinger

TL;DR
This paper introduces an advanced 3D finite element solver for coupled PNP-Stokes equations, employing goal-oriented adaptive mesh refinement and novel linearization schemes, to simulate nanopore sensors with improved efficiency and physical accuracy.
Contribution
It develops a new adaptive mesh refinement approach using the Poisson-Boltzmann equation and proposes three linearization schemes for the nonlinear system, enhancing simulation efficiency and accuracy.
Findings
Adaptive mesh refinement improves computational efficiency.
Segregated linearization schemes outperform naive Newton's method.
Point-size molecule model misses key physical effects.
Abstract
We present a 3D finite element solver for the nonlinear Poisson-Nernst-Planck (PNP) equations for electrodiffusion, coupled to the Stokes system of fluid dynamics. The model serves as a building block for the simulation of macromolecule dynamics inside nanopore sensors. We add to existing numerical approaches by deploying goal-oriented adaptive mesh refinement. To reduce the computation overhead of mesh adaptivity, our error estimator uses the much cheaper Poisson-Boltzmann equation as a simplified model, which is justified on heuristic grounds but shown to work well in practice. To address the nonlinearity in the full PNP-Stokes system, three different linearization schemes are proposed and investigated, with two segregated iterative approaches both outperforming a naive application of Newton's method. Numerical experiments are reported on a real-world nanopore sensor geometry. We…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
