GaneshShivalingappa/Parametric-NN-Models
Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network
This project helps engineers and material scientists identify specific material properties by analyzing how materials respond to forces. You input data from material tests, and it outputs the identified material parameters, effectively solving inverse problems. It's designed for professionals working with material characterization or structural analysis.
Use this if you need to determine unknown material parameters from observed physical behavior, particularly when dealing with mechanical structures like a 1D bar under stress.
Not ideal if you are looking for a general-purpose simulation tool or if your primary interest is in forward engineering problems rather than inverse material identification.
Stars
20
Forks
—
Language
Python
License
GPL-3.0
Category
Last pushed
Nov 26, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/GaneshShivalingappa/Parametric-NN-Models"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
NVIDIA/physicsnemo
Open-source deep-learning framework for building, training, and fine-tuning deep learning models...
SciML/NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for...
NVIDIA/physicsnemo-sym
Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to...
idrl-lab/idrlnet
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural...
mathLab/PINA
Physics-Informed Neural networks for Advanced modeling