Digital-Twin-Operational-Platform / CristalloLinks
☆35Updated last year
Alternatives and similar repositories for Cristallo
Users that are interested in Cristallo are comparing it to the libraries listed below
Sorting:
- This repository contains the scripts and preprocessed data to recreate the figures and results presented in the paper: A Comprehensive Re…☆36Updated 2 years ago
- In this repo we will show how to build a simple but useful Digital Twin using python. Our asset will be a Li-ion battery. This Digital Tw…☆86Updated 6 months ago
- This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and…☆28Updated 2 years ago
- Physics informed neural networks for control-oriented building thermal models☆29Updated 3 years ago
- ☆14Updated last year
- Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation☆38Updated last year
- Fuhrländer FL2500 2.5MW wind turbine dataset + pre-processing functions R MATLAB☆15Updated 2 years ago
- Digital Twin of an Induction Motor: Fault Analysis and Predictive Maintenance☆16Updated last year
- The NASA Prognostic Python Packages is a Python framework focused on defining and building models and algorit for prognostics (computatio…☆97Updated last month
- Digital twins in machining process by Generative Adversarial Nets☆47Updated 6 years ago
- This is a project to forecast Fuel Cell Performance☆15Updated 3 years ago
- list of papers, code, and other resources☆67Updated 3 years ago
- ☆43Updated 2 months ago
- Dashboard designed to demonstrate the power of Machine Learning to predict failures (Remaining Useful Life (RUL)) in wind turbines. To pr…☆47Updated 2 years ago
- Machine learning applied to wind turbines incipient fault detection.☆89Updated 3 years ago
- TESPy model of a refrigeration machine☆13Updated 3 years ago
- PI Controller vs Reinforcement Learning to control temperature inside a room☆27Updated 4 years ago
- a novel framework based on a physics-informed neural network dubbed as PhysCon that combines the interpretable ability of physical laws a…☆13Updated 2 years ago
- Predicting energy efficiency from Energy Performance Certificates (EPC) using machine learning☆16Updated 5 years ago
- The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining…☆125Updated last year
- physics-guided neural networks (phygnn)☆93Updated last month
- Thermal Neural Networks - Learn dynamic thermal networks from data. Application demo on an electric motor.☆46Updated this week
- ☆12Updated 3 years ago
- My master's dissertation on wind turbine fault prediction using machine learning☆57Updated last year
- Physics-guided data-driven solutions for the wind energy industry☆24Updated 3 weeks ago
- The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering …☆58Updated last year
- This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Sup…☆26Updated 3 years ago
- list of open wind turbine data sets☆155Updated 2 months ago
- Energy consumption prediction using LSTM/GRU networks in PyTorch☆58Updated 2 years ago
- A wind turbine digital twin based on YAMS☆28Updated 3 years ago