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@gabrielewig gabrielewig released this 16 Nov 05:12
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Aquaculture

This repository contains a Python to model an offshore aquaculture farm with co-located wave energy converters and determine potential sites using marine spatial planning.

File Structure

This repository consists of the following files:

  • modules: scripts and functions to define "Wave-powered Aquaculture" optimization problem.
  • objects: scripts and functions to define aquaculture and wave energy converter objects and their parameters.
  • optimization: scripts and functions to perform a single objective optimization using brute-force.
  • env_bruteforce: script to perform brute-force for defined net pen parmeters.
  • run_sim_env: top-level script to perform the "marine spatial planning" optimization code using default values for defined environment with rasters and vectors of data.
  • gis_handler: object to handle connection between GIS data and Python functions
  • scripts/: relevant scripts including examples of how to use the GIS handler to query and save data
  • data/: GIS files used in analysis including conflicts (.geojson) and conditions (.tif) (stored externally on Zenodo)
  • requirements.txt: list of the required libraries.

How to use

Relevant data files must be first downloaded from the Zenodo at https://zenodo.org/records/10140826 and placed in the data folder of this repository. In order to run the marine spatial planning optimization code and find optimal location for wave-powered aquaculture farm (WPAF) for constant net pen within the Northeast U.S, open and run the run_sim_env (.ipynb) file.

Dependencies

Python 3.9.18 is used to develop this package.
For other required libraries, please refer to requirements.txt file.

Context

The project is part of research in the Symbiotic Engineering Analysis (SEA) Lab and is published in the Oceans 2023.

Citation

Hasankhani, A., Ewig, G., McCabe, R., Won, E. T., & Haji, M. (2023, June). Marine Spatial Planning of a Wave-Powered Offshore Aquaculture Farm in the Northeast US. In OCEANS 2023-Limerick (pp. 1-10). IEEE.

Authors

Funding Acknowledgement

This material is based upon work supported by the Sea Grant Regional Research Project No.: R/ATD-18-NESG.

License

This project is released open-source under the MIT License. Processed GIS data included in the repository is from publicly available sources, but may have different license terms.

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