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Florian Hammer

Data-Driven wind turbine performance assessment and quantification using SCADA data and field measurements
2022 · Yu Ding, Sarah Barber, et al. · Frontiers in Energy Research · 37
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Enabling Co-Innovation for a Successful Digital Transformation in Wind Energy Using a New Digital Ecosystem and a Fault Detection Case Study
2022 · Sarah Barber, Luiz Lima, et al. · Energies · 22
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Improving Site-Dependent Wind Turbine Performance Prediction Accuracy Using Machine Learning
2022 · Sarah Barber, Florian Hammer, et al. · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering · 18
Graph machine learning for predicting wake interaction losses based on SCADA data
2023 · Florian Hammer, Nora Helbig, et al. · Journal of Physics Conference Series · 9
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Large Eddy Simulations of a Low-Pressure Turbine: Roughness Modeling and the Effects on Boundary Layer Transition and Losses
2018 · F. Hammer, Neil D. Sandham, et al. · ASME Turbo Expo: Turbomachinery Technical Conference and Exposition (GT) · 7
Comparison Metrics Microscale Simulation Challenge for Wind Resource Assessment
2023 · Florian Hammer, Sarah Barber, et al. · 4
Data imputation for SCADA data using Graph Neural Networks
2025 · Florian Hammer, Sarah Barber · Journal of Physics Conference Series · 3
Aventa AV-7 (6kW) IET-OST Research Wind Turbine SCADA
2023 · Barber, Sarah, Hammer, Florian, et al. · Zenodo (CERN European Organization for Nuclear Research) · 2
DEVINE
2026 · Helbig, Nora, Hammer, Florian · Zenodo (CERN European Organization for Nuclear Research) · 1
Transferability of site-dependent wind turbine performance predictions using machine learning
2022 · Florian Hammer, Sarah Barber · Journal of Physics Conference Series · 1
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The Influence Of Different Wake Profiles On Losses In A Low Pressure Turbine Cascade
2017 · Florian Hammer, Neil D. Sandham, et al. · Proceedings of ... European Conference on Turbomachinery Fluid Dynamics & Thermodynamics · 1
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Supplementary material to "Deep learning-based high-resolution downscaling of terrain-driven near-surface winds"
2026 · Nora Helbig, Florian Hammer, et al.
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Deep learning-based high-resolution downscaling of terrain-driven near-surface winds
2026 · Nora Helbig, Florian Hammer, et al.
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Potential and limitations of efficient machine-learning wind downscaling for energy-relevant applications in mountainous environments
2026 · Nora Helbig, Florian Hammer, et al. · EGU General Assembly Conference Abstracts
Graph Neural Networks for SCADA data imputation
2026 · Hammer, Florian, Barber, Sarah · Zenodo (CERN European Organization for Nuclear Research)
Pretrained GNN model weights for SCADA data imputation (Kelmarsh and Penmanshiel wind farms)
2026 · Hammer, Florian, Barber, Sarah · Zenodo (CERN European Organization for Nuclear Research)
Towards efficient methods for estimating spatio-temporal wind energy yields in mountainous regions
2024 · Nora Helbig, Florian Hammer, et al. · EGU General Assembly Conference Abstracts
Reply on RC1
2023 · Florian Hammer
Reply on RC2
2023 · Florian Hammer
Comparison Metrics Microscale Simulation Challenge for Wind Resource Assessment - Perdigão
2023 · Hammer, Florian, Barber, Sarah, et al. · Zenodo (CERN European Organization for Nuclear Research)
Characterizing the impact of spatial scales on near-surface wind speed and wind power generation in a mountainous environment
2023 · Nora Helbig, Florian Hammer, et al. · EGU General Assembly Conference Abstracts
Works count: 25
Citation count: 108
H-index: 5
I10-index: 3
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