CalculiX examples by Prof. Martin Kraska from Brandenburg University of Applied Sciences. Excellent starting point to master parametric modelling with CGX and CCX.

spiking-neural-networks

Python executable for design of hollow reinforced concrete sections under combined actions

Efficient meta learning of synaptic plasticity from experimental data using artificial neural network models.

dolfinx_materials is a Python add-on package to the dolfinx interface to the FEniCSx project. It enables the user to define complex material constitutive behaviors which are not expressible using classical UFL operators.

a FreeCAD workbench and solver for performing collapse analysis of structures and soil bodies

The concurrent atomistic-continuum simulation environment

[ICLR 2024] Adaptive Replay Ratio implementation from 'Revisiting Plasticity in Visual RL: Data, Modules and Training Stages'.

FeCLAP: A small solver for the Finite element analysis of Composite Laminate Plates with rectangular geometries. This personal project solver supports static, modal, transient and non linear analysis using a perfectly plastic model.

Discrete Element Method package written in Python and based on fenics

Computational models of the globular bushy cells in the ventral cochlear nucleus

Learning to Predict Crystal Plasticity at the Nanoscale:Deep Residual Networks and Size Effects in UniaxialCompression Discrete Dislocation Simulations

Iterative winners-take-all algorithm

Learning to Predict Crystal Plasticity at the Nanoscale:Deep Residual Networks and Size Effects in UniaxialCompression Discrete Dislocation Simulations

Compartmentalized models with Argiope

Partial information decomposition (PID) analysis of neuronal plasticity model.

NEURON model of inhibitory synaptic plasticity through KCC2 regulation.

This Python code generates a Combinatorial Discrete Cell Complex for the slip planes arrangement in FCC and BCC lattices as a set of Adjacency and Incidence matrices