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.

Clone this repository with

git clone https://github.com/UNH-CORE/RVAT-Re-dep.git

To run the processing/plotting code we recommend the Anaconda Python distribution (Python 3.5) since it includes most dependencies. The remaining can be installed by executing

pip install progressbar33 pxl>=0.0.8

After installing all dependencies, execute python plot.py to generate figures from the experiment.

To contribute to this repository, please create a fork, add changes on a descriptively-named branch, and submit a pull request.

• Uncertainty calculations
• UNH-RVAT CAD models

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.