Tanana River Test Site Model Verification Using the Marine and Hydrokinetic Toolkit (MHKiT)
Emily Browning (),
Sterling Olson,
Rebecca Fao,
Adam Keester and
James McVey
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Emily Browning: Water Power Technologies, Sandia National Laboratories, Albuquerque, NM 87185, USA
Sterling Olson: Water Power Technologies, Sandia National Laboratories, Albuquerque, NM 87185, USA
Rebecca Fao: Water Power, National Renewable Energy Laboratory, Golden, CO 80401, USA
Adam Keester: Water Power Technologies, Sandia National Laboratories, Albuquerque, NM 87185, USA
James McVey: Coastal Sciences Division, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
Energies, 2023, vol. 16, issue 8, 1-11
Abstract:
The marine energy (ME) industry historically lacked a standardized data processing toolkit for common tasks such as data ingestion, quality control, and visualization. The marine and hydrokinetic toolkit (MHKiT) solved this issue by providing a public software deployment (open-source and free) toolkit for the ME industry to store and maintain commonly used functionality for wave, tidal, and river energy. This paper demonstrates an initial model verification study in MHKiT. Using Delft3D, a numerical model of the Tanana River Test Site (TRTS) at Nenana, Alaska was created. Field data from the site was collected using an Acoustic Doppler Current Profiler (ADCP) at the proposed Current Energy Converter (CEC) locations. MHKiT is used to process model simulations from Delft3D and compare them to the transect data from the ADCP measurements at TRTS. The ability to use a single tool to process simulation and field data demonstrates the ease at which the ME industry can obtain results and collaborate across specialties, reducing errors and increasing efficiency.
Keywords: MHKiT; marine energy; Tanana River; Delft3D; ADCP; transect; DOLfYN (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:8:p:3326-:d:1118875
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