CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
Common file format and data structure to represent flow input and wind turbine representation (i.e., multi-dimensional power, thrust and load surrogate models) will be decided. This will allow to simplify model interfacing in the wind farm flow prediction tool developed within FLOW.
Standardisation activities report (opens in new window)This deliverable will consist of a plan of standardization activities will be deployed and regularly monitored based on (i) the identification of key standards and regulation under FLOW’s technology innovation, (ii) monitoring of these and (iii) assessment about the creation of new standards/protocols including the main benefits generated in the project on technology scale-up. To ensure relevance and compliance of the project achievements, working meetings with key actors and a procedure for standards mapping and status check will be planned and implemented.
First update of Data Management Plan (opens in new window)Data Management Plan (opens in new window)
The DMP will determine how research data will be handled and shared during the project and after its completion considering the implementation of open science practices.
PEDR – Plan for Exploitation and Dissemination of Results (opens in new window)The report will describe the internal rules and procedures for project dissemination of results, including the identification and analysis of potential external activities in which FLOW members could participate. In PEDR, it will include the communication materials to be used throughout the project duration, including project branding setup (logo, motto, and templates for external communication documents), digital brochures, semi-annuals digital newsletters, promotional videos, roll-ups and digital posters. To support project dissemination, it will be continuously monitored online channels (project website (with all relevant information about the project, updates, outcomes, publication of deliverables and announcements), LinkedIn page (for regular communication), Twitter (to announce key achievements and internal events, including conferences and the final workshop).
Specialized training and courses report (opens in new window)Preparation and workplan for the open access training will be described in this deliverable. The training activities – including materials from specialised training courses on the FLOW forecasting tool. - within FLOW includes three main modules: The course includes i) an overview of the models in the FLOW tool and their computational efficiency and limitations; ii) training for using the FLOW tool for wind farm siting; and iii) training for using the FLOW uncertainty predictor and building your own uncertainty predictor with SCADA datasets. FLOW will engage stakeholders both from industry and academia as open science and open innovation best practices.
Meeting Plan for External Expert Advisory Board (opens in new window)EEAB members will be contacted and a plan will be delivered.
First update of PEDR (opens in new window)Update of FlowHUB database with both experimental and modelling dataPartners will generate high quality datasets from new experiments focused on high-impact phenomena as well as gathering of existing datasets.
FlowHUB database with both experimental and modelling data (opens in new window)Partners will generate high quality datasets from new experiments focused on high-impact phenomena as well as gathering of existing datasets.
Release of the open-source wind farm flow prediction tool, based on python interfacing of ML, engineering, and CFD models with commonly defined modelling standards (opens in new window)An open-source wind farm flow prediction tool, allowing to interface and benchmark different codes and libraries, is released. The tool will offer three levels of fidelities, ranging from Machine Learning model, to engineering, and CFD models.
Categorization of the data types and definition of necessary processing steps to accommodate various levels of data confidentiality
Publications
Author(s):
Abdul Haseeb Syed, Jakob Mann
Published in:
Boundary-Layer Meteorology, Issue 190, 2024, ISSN 0006-8314
Publisher:
Springer Science and Business Media LLC
DOI:
10.1007/S10546-023-00850-W
Author(s):
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan T. Kral, and Joachim Reuder
Published in:
Atmospheric Measurement Techniques, Issue 1546, 2023, ISSN 1867-8610
Publisher:
Egusphere
DOI:
10.5194/EGUSPHERE-2023-1546
Author(s):
Bjarke T. E. Olsen; Andrea N. Hahmann; Nicolas G. Alonso-de-Linaje; Mark Žagar; Martin Dörenkämper
Published in:
Geoscientific Model Development, Issue 18, 2025, ISSN 1991-9603
Publisher:
Copernicus Publications
DOI:
10.5194/GMD-18-4499-2025
Author(s):
Abdul Haseeb Syed; Jakob Mann
Published in:
Wind Energy Science, 2023, ISSN 2366-7451
Publisher:
European Academy of Wind Energy
DOI:
10.5194/WES-2023-142
Author(s):
L. Lanzilao; J. Meyers
Published in:
Journal of Fluid Mechanics, Issue 979, 2024, ISSN 1469-7645
Publisher:
Cambridge University Press
DOI:
10.1017/jfm.2023.1088
Author(s):
Koen Devesse, Sebastiano Stipa, Joshua Brinkerhoff, Dries Allaerts, Johan Meyers
Published in:
Journal of Physics: Conference Series, Issue 2767, 2024, ISSN 1742-6588
Publisher:
IOP Publishing
DOI:
10.1088/1742-6596/2767/9/092079
Author(s):
Julian Quick, Rem-Sophia Mouradi, Koen Devesse, Antoine Mathieu, M. Paul Van Der Laan, Juan Pablo Murcia Leon, Jonas Schulte
Published in:
Journal of Physics: Conference Series, Issue 2767, 2024, ISSN 1742-6588
Publisher:
IOP Publishing
DOI:
10.1088/1742-6596/2767/9/092074
Author(s):
Jan Friedrich, Joachim Peinke
Published in:
Journal of Physics: Conference Series, Issue 2507, 2023, ISSN 1742-6588
Publisher:
IOP Publishing
DOI:
10.1088/1742-6596/2507/1/012017
Author(s):
Jörge Schneemann, Frauke Theuer, Andreas Rott, Martin Kühn
Published in:
Journal of Physics: Conference Series, Issue 3016, 2025, ISSN 1742-6588
Publisher:
IOP Publishing
DOI:
10.1088/1742-6596/3016/1/012012
Author(s):
Daniela Moreno; Jan Friedrich; Matthias Wächter; Jörg Schwarte; Joachim Peinke
Published in:
Wind Energy Science, 2025, ISSN 2366-7451
Publisher:
Wind Energy Science
DOI:
10.5194/WES-2024-32
Author(s):
Nikolas Angelou; Jakob Mann; Camille Dubreuil-Boisclair
Published in:
Wind Energy Science, Issue 8, 2023, ISSN 2366-7451
Publisher:
Wind Energy Science
DOI:
10.5194/wes-8-1511-2023
Author(s):
Limas Coimbra, Isadora; Mann, Jakob; Palma, José Laginha; Batista, Vasco
Published in:
Atmospheric Measurement Techniques, Issue 18, 2025, ISSN 1867-8548
Publisher:
EGUsphere
DOI:
10.5194/AMT-18-287-2025
Author(s):
Sebastiani, Alessandro; Bleeg, James; Peña, Alfredo
Published in:
Wind Energy Science, 2023, ISSN 2366-7451
Publisher:
Wind Energy Science
DOI:
10.5194/WES-2023-34
Author(s):
Xiaonan Wang, Hui Liu, Mingshui Li, Jakob Mann, Shaopeng Li
Published in:
Physics of Fluids, Issue 37, 2025, ISSN 1070-6631
Publisher:
AIP Publishing
DOI:
10.1063/5.0246592
Author(s):
J Bleeg, P Vishwakarma, M Del Hoyo and L Simmons
Published in:
Journal of Physics: Conference Series, Issue 2767, 2024, ISSN 1742-6596
Publisher:
IOP Publishing Ltd
DOI:
10.1088/1742-6596/2767/4/042026
Author(s):
Andrew Kirby; Takafumi Nishino; Luca Lanzilao; Thomas D. Dunstan; Johan Meyers
Published in:
Wind Energy Science, 2024, ISSN 2366-7451
Publisher:
Wind Energy Science
DOI:
10.5194/WES-2024-79
Author(s):
Devesse, Koen; Lanzilao, Luca; Meyers, Johan
Published in:
Fluid Dynamics, 2023
Publisher:
Cornell University - Fluid Dynamics
DOI:
10.48550/arxiv.2310.18748
Author(s):
Bjarke Tobias Eisensøe Olsen; Andrea Noemi Hahmann; Nicolás González Alonso-de-Linaje; Mark Žagar; Martin Dörenkämper
Published in:
eISSN:, 2024
Publisher:
Copernicus Publications
DOI:
10.5194/EGUSPHERE-2024-3123
Author(s):
Sanz Rodrigo, Javier; Oxley, G.; Tobias Olsen, Bjarke
Published in:
Journal of Physics: Conference Series, Issue 2767, 2024
Publisher:
The Science of Making Torque from Wind
DOI:
10.1088/1742-6596/2767/9/092077
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