pranaymodukuru / Concrete-compressive-strengthLinks
Concrete Compressive Strength Prediction using Machine Learning
☆25Updated 5 years ago
Alternatives and similar repositories for Concrete-compressive-strength
Users that are interested in Concrete-compressive-strength are comparing it to the libraries listed below
Sorting:
- ☆14Updated 6 years ago
- Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the co…☆23Updated 5 years ago
- code_sample☆19Updated 2 years ago
- Code for the paper "A physics-informed neural network framework for laminated composite plates under bending"☆13Updated 9 months ago
- ☆30Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- EP-PINNs implementation for 1D and 2D forward and inverse solvers for the Aliev-Panfilov cardiac electrophysiology model. Also includes M…☆28Updated 2 years ago
- Extraction of mechanical properties of materials through deep learning from instrumented indentation☆70Updated 3 years ago
- Implementation of PINNs in TensorFlow 2☆81Updated 2 years ago
- Python scripts for physics-informed neural networks for corrosion-fatigue prognosis☆41Updated 3 years ago
- This repository contains code for predicting multiaxial fatigue life of metals using deep learning models (CNN, LSTM, and GRU) combined w…☆20Updated last year
- ☆10Updated 2 years ago
- PINN for obtaining WSS from sparse data☆68Updated last year
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆45Updated last week
- A Machine Learning approach to Finite Element Methods, using U-Net inspired architectures.☆29Updated 6 years ago
- MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning☆38Updated 3 years ago
- A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis☆29Updated 7 years ago
- A General Framework Combining Generative Adversarial Networks and Mixture Density Networks for Inverse Modeling in Microstructural Materi…☆10Updated 2 years ago
- Basic implementation of physics-informed neural networks for solving differential equations☆95Updated 10 months ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆145Updated last year
- ☆18Updated 2 years ago
- ☆194Updated 2 years ago
- In this repository, we present an Semantic Segmentation code, based on U-net architecture, that is used for the topographic characterizat…☆15Updated 4 years ago
- Code for 'Unifying the design space of truss metamaterials by generative modeling'☆18Updated last month
- Hands-on tutorial for implementing Physics Informed Neural Networks in Pytorch☆52Updated 6 months ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆77Updated 4 years ago
- ☆117Updated last year
- A Physics-Informed Neural Network for solving Burgers' equation.☆32Updated last year
- A place to share problems solved with SciANN☆292Updated last year