KTH-FlowAI / DeepReinforcementLearning_RayleighBenard2D_ControlLinks
Control of 2D Rayleigh Benard Convection using Deep Reinforcement Learning with Tensorforce and Shenfun.
☆20Updated 2 years ago
Alternatives and similar repositories for DeepReinforcementLearning_RayleighBenard2D_Control
Users that are interested in DeepReinforcementLearning_RayleighBenard2D_Control are comparing it to the libraries listed below
Sorting:
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- ☆22Updated 4 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- Nonlinear proper orthogonal decomposition for convection-dominated flows☆14Updated 3 years ago
- A multi-agent reinforcement learning environment to design and benchmark control strategies aimed at reducing drag in turbulent open chan…☆61Updated last year
- ☆21Updated 5 years ago
- code for active flow control of flow around cynder using Deep Reinforcement Learning☆50Updated 3 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- Pseudospectral Kolmogorov Flow Solver☆41Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Tensor Basis Neural Network for Scalar Mixing☆10Updated 2 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆12Updated 4 years ago
- POD-PINN code and manuscript☆54Updated 11 months ago
- The MegaFlow2D dataset package☆23Updated 2 years ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆21Updated 4 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 2 years ago
- Multi-fidelity Generative Deep Learning Turbulent Flows☆38Updated 4 years ago
- ☆26Updated 7 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆95Updated 6 years ago
- Direct Numerical Simulation of Fluid Flow with IBM Using Python☆32Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Repository from the paper https://arxiv.org/abs/1908.04127, to train Deep Reinforcement Learning in Fluid Mechanics Setup.☆66Updated 4 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆20Updated 4 years ago
- In computational fluid dynamics (CFD), the SIMPLE algorithm is a widely used numerical procedure to solve the Navier–Stokes equations. SI…☆16Updated 4 years ago
- Using NVIDIA modulus for airfoil optimizations at different angles.☆23Updated 2 years ago
- ☆14Updated 11 months ago