From e28ac9f22e6a1a55b4037ec6bd9353c55fb13ae1 Mon Sep 17 00:00:00 2001 From: HAN LI Date: Wed, 27 Dec 2023 16:03:28 +0800 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d7764af3..6a81ce7c 100644 --- a/README.md +++ b/README.md @@ -21,7 +21,7 @@ DeepFlame is a deep learning empowered computational fluid dynamics package for single or multiphase, laminar or turbulent, reacting flows at all speeds. It aims to provide an open-source platform to combine the individual strengths of [OpenFOAM](https://openfoam.org), [Cantera](https://cantera.org), and [PyTorch](https://pytorch.org/) libraries for deep learning assisted reacting flow simulations. It also has the scope to leverage the next-generation heterogenous supercomputing and AI acceleration infrastructures such as GPU and FPGA. -The neural network models used in the tutorial examples can be found at– [AIS Square](https://www.aissquare.com/). To run DeepFlame with DNN, download the DNN model [dfODENet](https://www.aissquare.com/models/detail?pageType=models&name=dfODENet_DNNmodel_V0.1&id=181) into the case folder you would like to run. +The neural network models used in the tutorial examples can be found at– [AIS Square](https://www.aissquare.com/). To run DeepFlame with DNN, download the DNN model [DF-ODENet](https://www.aissquare.com/models/detail?pageType=models&name=DF-ODENet_DNNmodel&id=197) into the case folder you would like to run. ## Documentation Detailed guide for installation and tutorials is available on [our documentation website](https://deepflame.deepmodeling.com).