Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling
This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture.
The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.
Citation Formats
TY - DATA
AB - This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture.
The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.
AU - Kimball, Chelsea
A2 - Swift, Rob
A3 - Wosnik, Martin
DB - Marine and Hydrokinetic Data Repository
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15473/2000556
KW - MHK
KW - Marine
KW - Hydrokinetic
KW - energy
KW - power
KW - wave energy
KW - WEC
KW - point absorber
KW - aquaculture
KW - upweller
KW - DAQ module
KW - WEC-Sim
KW - field testing
KW - performance
KW - Maine
KW - east coast
KW - wave energy converter
KW - Isles of Shoals
KW - Appledore Island
KW - technology
KW - code
KW - AMEC
KW - Powering the Blue Economy
KW - macroalgal aquaculture
KW - raw data
KW - processed data
KW - blue economy
LA - English
DA - 2023/03/21
PY - 2023
PB - University of New Hampshire, Atlantic Marine Energy Center (AMEC)
T1 - Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling
UR - https://doi.org/10.15473/2000556
ER -
Kimball, Chelsea, et al. Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling. University of New Hampshire, Atlantic Marine Energy Center (AMEC), 21 March, 2023, Marine and Hydrokinetic Data Repository. https://doi.org/10.15473/2000556.
Kimball, C., Swift, R., & Wosnik, M. (2023). Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling. [Data set]. Marine and Hydrokinetic Data Repository. University of New Hampshire, Atlantic Marine Energy Center (AMEC). https://doi.org/10.15473/2000556
Kimball, Chelsea, Rob Swift, and Martin Wosnik. Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling. University of New Hampshire, Atlantic Marine Energy Center (AMEC), March, 21, 2023. Distributed by Marine and Hydrokinetic Data Repository. https://doi.org/10.15473/2000556
@misc{MHKDR_Dataset_499,
title = {Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling},
author = {Kimball, Chelsea and Swift, Rob and Wosnik, Martin},
abstractNote = {This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture.
The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.},
url = {https://mhkdr.openei.org/submissions/499},
year = {2023},
howpublished = {Marine and Hydrokinetic Data Repository, University of New Hampshire, Atlantic Marine Energy Center (AMEC), https://doi.org/10.15473/2000556},
note = {Accessed: 2025-04-25},
doi = {10.15473/2000556}
}
https://dx.doi.org/10.15473/2000556
Details
Data from Mar 21, 2023
Last updated Sep 18, 2023
Submitted Aug 18, 2023
Organization
University of New Hampshire, Atlantic Marine Energy Center (AMEC)
Contact
Chelsea Kimball
603.553.7237
Authors
Keywords
MHK, Marine, Hydrokinetic, energy, power, wave energy, WEC, point absorber, aquaculture, upweller, DAQ module, WEC-Sim, field testing, performance, Maine, east coast, wave energy converter, Isles of Shoals, Appledore Island, technology, code, AMEC, Powering the Blue Economy, macroalgal aquaculture, raw data, processed data, blue economyDOE Project Details
Project Name Atlantic Marine Energy Center
Project Lead Lauren Ruedy
Project Number EE0009450
