lsdo_rotor

This is a python package for low-fidelity rotor aerodynamic analysis and design. This package includes (differentiable) implementations of blade element momentum (BEM) theory, Pitt--Peters dynamic inflow model (solved for steady state), and a recently developed rotor design method, based on an ideal-loading assumption. Please refer to the project website for more information on installation, usage, theory, and example scripts.

Installation

Step 0: Install miniconda

Next, we recommend the usage of Python environments. Miniconda is a compact version of the Anaconda Python distribution. Please see the link to find detailed installation instructions and verify that the commands below to install Miniconda are up-to-date.

NOTE that in the commands below, the assumed operating system is Linux. If you are on MacOS or Windows, refer to the Miniconda link for OS specific instructions.

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh

Step 1: Create conda environment

Now, create a Conda environment. We recommend Python 3.9. Afterward, activate the environment.

conda create --name lsdo_rotor python==3.9
conda activate lsdo_rotor

Note that in the command above lsdo_rotor is the name of the environment and be anything. Next, we need to install a couple of packages that lsdo rotor depends on. We recommend creating an easily accessable directory on your local machine where you install LSDO rotor and any other packages that may be necessary. The command mkdir packages will make a sub-directory called 'packages' inside your current direcory and you can change your directory accordingly by typing cd packages. If you already have central directory where you would like to install all your packages in, change the directory by typing cd path/to/desired/directory. Once you are in the right directory execute the following commands.

Step 2: Install CSDL and python CSDL backend

LSDO Rotor is written the Computational System Design Language (CSDL), which is a python-based algebraic modeling language for defining mathemtical models using intuitive and familiar syntax. The critical feature of CSDL is that all operations are differentiable, which enables large-scale gradient-based design optimization.

git clone https://github.com/LSDOlab/csdl.git
cd csdl
pip install -e .
cd ..
git clone https://github.com/LSDOlab/python_csdl_backend.git
cd python_csdl_backend
pip install -e .
cd ..

step 3: Install m3l

This package is needed only temporarily and will not be required long-term.

git clone https://github.com/LSDOlab/m3l.git
cd m3l
pip install -e .
cd ..

step 4: Install modOpt

modOpt is an optimizaiton library through which we can make use of state-of-art optimization algorithms and even create our own optimizaiton algorithms.

git clone https://github.com/LSDOlab/modopt.git
cd modopt
pip install -e .
git checkout 3cd2de77b6a551b208501d395fa970b511998b8b
cd ..

Step 5: Install LSDO Rotor

Lastly, we are ready to install LSDO Rotor:

git clone https://github.com/LSDOlab/lsdo_rotor.git
cd lsdo_rotor
pip install -e .
cd ..

Note that this installs lsdo_rotor into the specified Conda enveironment and everytime you open a new terminal window, you need to activate the conda environment. Future versions of lsdo_rotor can be 'pulled' from github by navigating into the local (your machine) directory containing lsdo_rotor by typing

git pull

Step 6: Running an example script

To see whether the installation was successful, you can try running an example script by typing the following commands

cd lsdo_rotor
cd examples
python ex_BEM_rotor_optimization.py