Frank Giraldo
Distinguished Professor of Applied Mathematics
Naval Postgraduate School
Monterey, California 93943 USA
Stable Entropy Aware Differentiable Ocean Galerkin (SEADOG) Model
Welcome to the SEADOG page (under construction).
What's new with SEADOG
SEADOG is a collection of solvers under one framework for solving various problems in fluid dynamics. SEADOG is written in Julia and is fully GPU-capable. It is also designed to be fully differentiable.
Publications
SEADOG is derived from the entropy-stable discontinuous Galerkin (ESDG) models found in the following papers:
-
ESDG for non-conservative terms for 3D global atmospheric modeling [JCP].
-
GPU performance of ESDG for a 3D atmospheric model [arXiv].
Documentation
Documentation will be made available in the near future.
What is SEADOG
The collection of solvers currently available include: space-time DG for simple flow problems, a 3D Euler solver, and a 3D hydrostatic ocean solver (multilayer shallow water equations).
What can SEADOG be used for
The goal is to make SEADOG usable for interesting problems in atmospheric and ocean modeling, with special emphasis on the ocean processes. The fully-differentiable capability of SEADOG allows the construction of data assimilation and neural network models for developing a digital twin of the ocean.
What can SEADOG do
The 3D Euler solvers are capable of running global atmospheric simulations (e.g., baroclinic instability) and LES simulations (e.g., rising thermal bubble). The 3D hydrostatic ocean model can run a series of tests including manufactured solutions to confirm the theoretical order of accuracy of the model. The ocean solver can also run well-balancing tests over bathymetry, baroclinic wave propagation problems, and the double-gyre problem (that involves a 20-year simulation of the 3D ocean with wind stresses, Coriolis, bottom friction, and viscosity).
Numerical Methods in SEADOG
SEADOG uses entropy-stable discontinuous Galerkin methods. SEADOG also relies on both explicit, fully implicit, and IMEX time-integrators, in addition to space-time DG.
Who built SEADOG
The main developer of this code is Henry Waterhouse (UC Santa Cruz PhD student in the Department of Applied Mathematics working under my supervision), with some of the infrastructure developed by Maciek Waruszewski (now at Sandia), Jeremy Kozdon (now at NVIDIA), and Lucas Wilcox (at NPS).
Who funded SEADOG
The SEADOG atmospheric solver (ESDG) was developed with funding from Schmidt Futures and the National Science Foundation Division of Atmospheric and Geospace Sciences. The ocean solver is currently unfunded.
SEADOG Development
SEADOG is the combination of a ESDG framework developed by Henry Waterhouse and Raven.jl available on Github. SEADOG is housed in a private Github repo and will be released piecemeal with each publication.
