Active learning-based optimization of hydroelectric turbine startup to minimize fatigue damage
- DOI
- 10.1016/j.renene.2025.124088
- Published
- 2026-01
- Container
- Renewable Energy
- Publisher
- Elsevier BV
- Open access
- unknown
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uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.renene.2025.124088,
title = {Active learning-based optimization of hydroelectric turbine startup to minimize fatigue damage},
author = {Vincent Mai and Quang Hung Pham and Arthur Favrel and Jean-Philippe Gauthier and Martin Gagnon},
year = {2026},
journal = {Renewable Energy},
doi = {10.1016/j.renene.2025.124088},
url = {https://doi.org/10.1016/j.renene.2025.124088}
}RIS
TY - JOUR TI - Active learning-based optimization of hydroelectric turbine startup to minimize fatigue damage AU - Vincent Mai AU - Quang Hung Pham AU - Arthur Favrel AU - Jean-Philippe Gauthier AU - Martin Gagnon PY - 2026 JO - Renewable Energy DO - 10.1016/j.renene.2025.124088 UR - https://doi.org/10.1016/j.renene.2025.124088 ER -
APA
Mai, V., Pham, Q. H., Favrel, A., Gauthier, J., & Gagnon, M. (2026). Active learning-based optimization of hydroelectric turbine startup to minimize fatigue damage. Renewable Energy. https://doi.org/10.1016/j.renene.2025.124088
Source records
- crossref · retrieved 2026-11-08T16:24:41.599Z