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
pippython >= 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:
- Affine flows in 2D Cartesian grid.
- Tukey depth eikonal equation in 2D Cartesian grid.
- Motion by curvature PDE in 3D Cartesian grid.
- Eikonal equation and Tukey depth eikonal equation in unstructured grids
- Eikonal equations
- Tukey depth eikonal equations
Metadata
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Total release size: 135.0 kB
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