This repository contains the processing and plotting code, as well as the derived dataset from the UNH-RVAT Reynolds number dependence experiment performed in Spring 2014.
You will need Calkit and its dependencies installed in order to run the pipeline that generates all of the figures. You will also need to have a token set in your config to be able to pull the raw data (necessary for one figure.)
Clone this repository with:
calkit clone https://github.com/UNH-CORE/RVAT-Re-dep.git
After that, call calkit run
.
The statistical data can be read from the CSVs in the Data/Processed
directory.
Each file in there is named according to which "section" of the experiment
it corresponds to (performance or wake measurements,)
and the tow speed at which it was performed.
If you'd like to reuse some of the data loading and plotting functionality in other Python code outside this project, add it as a Git submodule in your own repo with:
git submodule add https://github.com/UNH-CORE/RVAT-Re-dep rvat-re-dep
then install the Python package in local mode with:
pip install -e ./rvat-re-dep
You'll then be able to run code like:
import pyrvatrd
perf_curve = pyrvatrd.load_perf_curve(tow_speed=1.0)
perf_curve.plotcp()
See notebook.ipynb
for more examples.
Also see
this repo
for an example of how this data can be reused in your own project.
To contribute to this repository, please create a fork, add changes on a descriptively-named branch, and submit a pull request.
Please cite
Bachant, P. and Wosnik, M. (2016) UNH-RVAT Reynolds number dependence experiment: Reduced dataset and processing code. figshare. DOI: 10.6084/m9.figshare.1286960.v5
These data were used in the following publications:
Bachant, P. and Wosnik, M. (2016) Effects of Reynolds Number on the Energy Conversion and Near-Wake Dynamics of a High Solidity Vertical-Axis Cross-Flow Turbine. Energies, 9
Bachant, P. and Wosnik, M. (2014) Reynolds Number Dependence of Cross-Flow Turbine Performance and Near-Wake Characteristics. In Proceedings of the 2nd Marine Energy Technology Symposium METS2014, April 15--18, Seattle, WA
Code licensed under the MIT license. See LICENSE
for details.
All other materials licensed under a
Creative Commons Attribution 4.0 International License.