cfl-minds / drl_shape_optimization
Deep reinforcement learning to perform shape optimization
☆65Updated 3 years ago
Alternatives and similar repositories for drl_shape_optimization
Users that are interested in drl_shape_optimization are comparing it to the libraries listed below
Sorting:
- Parallelizing DRL for Active Flow control☆66Updated last year
- Airfoil shape optimization using Reinforcement Learning☆18Updated last year
- code for active flow control of flow around cynder using Deep Reinforcement Learning☆47Updated 3 years ago
- Robust active flow control over a range of Reynolds numbers using artificial neural network trained through deep reinforcement learning☆31Updated 4 years ago
- Repository from the paper https://arxiv.org/abs/1908.04127, to train Deep Reinforcement Learning in Fluid Mechanics Setup.☆64Updated 4 years ago
- ☆16Updated last year
- An open-source Python platform of coupling deep reinforcement learning and OpenFOAM☆150Updated 2 months ago
- reinforcement learning for active fluid control☆31Updated 4 years ago
- Deep reinforcement learning with OpenFOAM☆43Updated this week
- Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"☆70Updated last month
- code for performing active flow control of the 2D Karman street using Deep Reinforcement Learning☆160Updated last year
- Official repository of paper, entitled "Airfoil’s Aerodynamic Coefficients Prediction using Artificial Neural Network".☆32Updated last year
- Policy-based optimization : single-step policy gradient seen as an evolution strategy☆21Updated last year
- A multi-agent reinforcement learning environment to design and benchmark control strategies aimed at reducing drag in turbulent open chan…☆57Updated last year
- I am doing a surrogate optimization of a transonic airfoil. I am using an artificial neural network as my surrogate model to approximate …☆8Updated 4 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆48Updated 2 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆65Updated 3 years ago
- DRLFluent: a distributed co-simulation framework coupling reinfocement learning and computational fluids dynamics on HPC.☆10Updated last year
- ☆38Updated 3 years ago
- A framework to design and develop reinforcement learning environments for single- and multi-physics active flow control.☆27Updated last year
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- Deep Learning for Reduced Order Modelling☆99Updated 3 years ago
- A benchmark library for DRL-based flow control☆13Updated 3 months ago
- Genetic algorithms applied in Computer Fluid Dynamics for multiobjective optimization - Senior Thesis in Mechanical Engineering at the Un…☆59Updated 6 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆15Updated 4 years ago
- ☆20Updated 3 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆65Updated last year
- Multi-fidelity reduced-order surrogate modeling☆22Updated 2 weeks ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆35Updated 9 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year