felipefr/deepbnd

Stars
1
Language
Python
License
MIT License
Created about 4 years ago
Updated almost 2 years ago

felipefr/deepbnd

felipefr

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Implementation of the DeepBND method based on FEniCs and Tensorflow

micmacsfenics

micmacsfenics: a FEniCs-based implementation of two-level finite element simulations (FE2) using computational homogenization.

ddfenics

a FEniCs-based (Model-Free) Data-driven Computational Mechanics implementation

Jupyter Notebook

gpmaterials

GPMaterials implements a rich set of finite element formulations for finite strain hyperelasticity, damage, multi-scale solid mechanics in both continuum and discrete level (truss-like network of fibres). This library was developed during my master and PhD studies at LNCC. Particularly this version is more related with my PhD and indeed it is the last stable version from late 2018, before starting writing up the thesis.

galerkinML_EAMC2021

Repositório com os arquivos usados no Workshop : "Galerkin convida Mr. Deep para um café", na edição de 2021 do EAMC realizado no LNCC. Autor : Felipe Figueredo Rocha.

fetricks

Useful tricks and some extensions for FEniCs and other FEM-related utilities (fe + tricks: where "fe" stands for FEM, FEniCs and me :) )

optfem

Identifying material properties via optimisation algorithms and finite elements

netfibGen

Library to generate fibre networks used in computational homogenisation analysis.

Piola

Piola aims at mimetising SolverGP to provide a simple, C++, opensource alternative to it. I developed during my PhD at LNCC (2015-2019) for debug purposes. Please consider compilating a version of GPMaterials in a .so file, to be able to call the library from Piola. This version specifically relies on a valid Armadillo instalation for linearalgebra routines.

mp2

Enseignement Mécanique du Point 2