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Monotone schemes for curvature-driven PDEs

by Jeff Calder (UMN) and Wonjun Lee (UMN)

  • Paper: arXiv
  • Jeff Calder, School of Mathematics, University of Minnesota: website
  • Wonjun Lee, Institute for Mathematics and Its Applications, Uniersity of Minnesota: website

Introduction

This repository contains C++ and python codes for running the monotone algorithm to solve curvature-driven PDEs. Here are list of PDEs that can be solved using this algorithm. Let $\Omega = [0,1]^d$ be a domain in $\mathbb{R}^d$ and $\partial \Omega$ be a boundary of $\Omega$.

Eikonal equation

$$ |\nabla u(x)| = f(x),\quad x \in \Omega $$

$$ u(x) = 0,\quad x \in \partial \Omega $$

Mean curvature PDE

$$|\nabla u(x)|\kappa(x) = f(x),\quad x \in \Omega $$

$$ u(x) = 0,\quad x \in \partial \Omega $$

where $\kappa(x) = - \text{div}\left( \frac{\nabla u}{|\nabla u|} \right)$ is the mean curvature of the level set surface of $u$ passing through $x$.

Affine flows PDE

$$|\nabla u(x)|\kappa(x)_+^{\alpha} = f(x),\quad x \in \Omega $$

$$u(x) = 0,\quad x \in \partial \Omega $$

where $\alpha \in (0,1]$ is a constant depending on the dimension $d$ and $(t)_+ := \max(0,t)$.

Tukey Depth

$$ |\nabla u(x)| = \int_{(y-x)\cdot \nabla u(x) = 0} \rho(y) dS(y),\quad x \in \Omega $$

$$ u(x) = 0,\quad x \in \partial \Omega $$


Tutorial

Prerequisites

  • pip
  • python >= 3.6

Follow this link to see the instruction for the installation of pip: https://pip.pypa.io/en/stable/installation/.

Installing the package

Install the package by running the following command:

    pip install monotonescheme

Running the codes

You can find the example python script files and notebook files in tests folder. The notebook files in the folder solve the following problems:

  1. Affine flows in 2D Cartesian grid.
  1. Tukey depth eikonal equation in 2D Cartesian grid.
  1. Motion by curvature PDE in 3D Cartesian grid.
  1. Eikonal equation and Tukey depth eikonal equation in unstructured grids

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