C and Python examples from my book on using PETSc and Firedrake to solve PDEs
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Updated
Oct 30, 2024 - C
C and Python examples from my book on using PETSc and Firedrake to solve PDEs
Wave propagators for seismic domains with application to full waveform inversion.
A shape optimisation toolbox built on the Firedrake finite element library.
Codes for finite element method
Finite Element Method for Electrochemical Transport (EchemFEM)
Slides/notes and Jupyter notebook demos for an introductory course of numerical methods for PDEs
FEMlium – interactive visualization of finite element simulations on geographic maps with folium
Differentiable interface to Firedrake for JAX
Easy interoperability with Automatic Differentiation libraries through NumPy interface to Firedrake and FEniCS
Automatic differentiation of FEniCS and Firedrake models in Julia
The firedrake-ts library provides an interface to PETSc TS for the scalable solution of DAEs arising from the discretization of time-dependent PDEs.
Physics-driven machine learning using PyTorch and Firedrake
Goal-oriented error estimation and mesh adaptation for finite element problems solved using Firedrake
Seismic inversion using a neural network regulariser implemented as an ExternalOperator in Firedrake
Mesh adaptation utilities for coastal ocean modelling in Firedrake and Thetis.
Mesh movement methods for finite element problems solved using Firedrake
[NeurIPS 2024 Spotlight] Towards Universal Mesh Movement Networks
viskex - interactive visualization for firedrake and FEniCSx
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