A surrogate model-based framework to calibrate the turbulence parameters of a vegetative canopy model for a marine turbine simulation-Reference-Cited by-同舟云学术

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A surrogate model-based framework to calibrate the turbulence parameters of a vegetative canopy model for a marine turbine simulation

Published:2023-05-23 Issue:3 Volume:9 Page:531-545
ISSN:2198-6444
Container-title:Journal of Ocean Engineering and Marine Energy
language:en
Short-container-title:J. Ocean Eng. Mar. Energy

Author:

Nurdiansyah Rudi,Su Jack C. P.,Hong I.-Hsuan,Olson Sterling S.,Silva H.

Funder

Ministry of Science and Technology, Taiwan

National Taiwan University

Publisher

Springer Science and Business Media LLC

Subject

Ocean Engineering,Energy Engineering and Power Technology,Water Science and Technology,Renewable Energy, Sustainability and the Environment

Link

https://link.springer.com/content/pdf/10.1007/s40722-023-00282-1.pdf

Reference55 articles.

1. Abdullah FAR, Ningsih NS, Al-Khan TM (2022) Significant wave height forecasting using long short-term memory neural network in Indonesian waters. J Ocean Eng Mar Energy 8(2):183–192

2. Beltramo T, Ranzan C, Hinrichs J, Hitzmann B (2016) Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm. Biosyst Eng 143:68–78

3. Brunetti ANNA, Armenio V, Roman F (2019) Large eddy simulation of a marine turbine in a stable stratified flow condition. J Ocean Eng Mar Energy 5(1):1–19

4. Brutto OAL, Thiébot J, Guillou SS, Gualous H (2016) A semi-analytic method to optimize tidal farm layouts–application to the Alderney Race (Raz Blanchard), France. Appl Energy 183:1168–1180

5. Bryden IG, Couch SJ, Owen A, Melville G (2007) Tidal current resource assessment. Proc Inst Mech Eng Part A J Power Energy 221(2):125–135

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