From bf04fecb046c078d6b886a54976a5584cf213858 Mon Sep 17 00:00:00 2001 From: JX278 Date: Tue, 26 Dec 2023 10:59:35 +0800 Subject: [PATCH] Update document --- README.md | 2 +- docs/source/qs/download_dnn_models.rst | 15 ++++----------- docs/source/qs/install.rst | 5 ++--- 3 files changed, 7 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 2e03ad1a9..d7764af39 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 deep learning algorithms and models used in the DeepFlame tutorial examples are developed and trained independently by our collaborators team – [Intelligent Combustion](https://github.com/intelligent-algorithm-team/intelligent-combustion.git). Please refer to their website for detailed information. +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. ## Documentation Detailed guide for installation and tutorials is available on [our documentation website](https://deepflame.deepmodeling.com). diff --git a/docs/source/qs/download_dnn_models.rst b/docs/source/qs/download_dnn_models.rst index 854b99801..b3a227939 100644 --- a/docs/source/qs/download_dnn_models.rst +++ b/docs/source/qs/download_dnn_models.rst @@ -1,18 +1,11 @@ Download DNN Models ====================================== -The neural network models used in the tutorial examples are indepentently trained -by our collaborators team – `Intelligent Combustion `_. -To run DeepFlame with DNN, first download the DeepCombustion repository into ``deepflame-dev/``: +The neural network models used in the tutorial examples can be found at– `AIS Square `_. +To run DeepFlame with DNN, download the DNN model `dfODENet `_ into the case folder you would like to run. You can either click the 'Download' on the website or: .. code-block:: bash - cd $DF_ROOT - git clone https://github.com/intelligent-algorithm-team/intelligent-combustion.git.git + cd ``case folder`` + wget --content-disposition ``the network's download link`` -Then copy the required DNN model into ``mechanisms/``, for example: -.. code-block:: bash - - cp -r intelligent-combustion/DeePCK/Model/HE04_Hydrogen_ESH2_GMS_sub_20221101/ mechanisms/ - -.. Note:: Here ``HE04_Hydrogen_ESH2_GMS_sub_20221101`` is the default DNN model for all the tutorial cases in ``$DF_ROOT/examples/``. diff --git a/docs/source/qs/install.rst b/docs/source/qs/install.rst index eac531ed1..5ea4a9087 100644 --- a/docs/source/qs/install.rst +++ b/docs/source/qs/install.rst @@ -43,10 +43,9 @@ Alternatively, one can `compile OpenFOAM-7 from source code