# parablade **Repository Path**: ustczzh/parablade ## Basic Information - **Project Name**: parablade - **Description**: No description available - **Primary Language**: Unknown - **License**: GPL-3.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-01-15 - **Last Updated**: 2021-01-15 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README
ParaBlade is an open-source Python library for the parametrization of turbomachinery blades design using gradient-based optimization algorithms.    [](https://zenodo.org/badge/latestdoi/268081609) ## Description #### Unified parametrization ParaBlade uses an unified parametrization method to describe the geometry of a wide range of turbomachinery blades including axial, radial, and mixed flow machines.
#### Meridional channel ParaBlade allows the user to specify an arbitrary shape of the blade in the axial-radial plane. The meridional channel is described by a set of four B-Splines that define the: - Leading edge - Trailing edge - Hub surface - Shroud surface
#### Blade sections ParaBlade also allows the user to specify a wide range of geometries for the blade sections. Each blade section is defined by a set of B-Spline curves and the control points of these curves are computed using engineering parameters such as metal angles and thickness distribution. At the moment, there are two available section parametrizations: - Connecting arcs (G1 continuous) - Camberline and thickness (G2 continuous)
#### CAD sensitivity ParaBlade is able to provide the sensitivity of the surface with respect to the design variables using the complex step method. This information is required to solve shape optimization problems (e.g. maximize the blade isentropic efficiency) using gradient-based algortithms.
## Blade matching ParaBlade is capable to finda parametrization to fit an given blade geometry. The solution of this _inverse problem_ is necessary to optimize the shape of an existing industrial design.
# Pre-requisites Important: MAC users, please use pip to install python packages as anaconda can give conflicts when using tecplot library. ### Pip3 ``` sudo apt-get install python-setuptools python-dev build-essential ``` ### MatPlotLib Use pip3 to install matplotlib. For more information on matplotlib visit [here]. [](https://matplotlib.org/) ``` sudo pip3 install matplotlib ``` ### NumPy Use pip3 to install numpy. For more information on numpy visit [](https://www.numpy.org/). ``` sudo pip3 install numpy ``` ### SciPy Use pip3 to install CoolProp. For more information on SciPy visit [here] [](https://www.scipy.org/). ``` sudo pip3 install scipy ``` ### Slack Client If you wish to get notification on slack for your optimization. Please install the slack client else, just continue using the code as it is. It would have no influence. Use pip3 to install slack-client. For more information on slack-client visit [here]. []() ``` sudo pip3 install slackclient ``` Also add ``` export SLACK_API_TOKEN="