Eco-friendly and customer-driven Sail plan optimisation service

Project Information

EcoSail

Grant agreement ID: 820593

DOI

10.3030/820593

Project closed

EC signature date 25 June 2018

Start date 1 November 2018

End date 31 October 2021

Funded under

• Horizon 2020 Framework Programme

Total cost

€ 3 903 142,50

EU contribution

€ 2 986 937,25

Coordinated by

O.M. OFFSHORE MONITORING LIMITED
Cyprus

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

Websites, patent fillings, videos etc. (3)

4 EcoSail service information/demo videos; final

4 EcoSail service information/demo videos; final (M26)

Report on EcoSail ‘Training Portal’
4 EcoSail service information/demo videos; interim

4 EcoSail service information/demo videos; interim (M14)

Demonstrators, pilots, prototypes (2)

Sail plan training programme for ship operators
EcoSail project webpage

Publications

Thesis and dissertations (2)

Development of Speed-power Performance Models for Ship Voyage Optimization

Author(s): Xiao Lang
Published in: Licentiate Thesis, Issue 2021, January, 2021, Page(s) 120
Publisher: Chalmers University of Technology

Development of voyage optimization algorithms for sustainable shipping and their impact to ship design

Author(s): Wang, Helong
Published in: Book (dissertation), Issue 1, 2020, Page(s) 68, ISBN 978-91-7905-259-1
Publisher: Chalmers University of Technology

Peer reviewed articles (5)

Voyage optimization combining genetic algorithm and dynamic programming for fuel/emissions reduction

Author(s): Helong Wang, Xiao Lang, and Wengang Mao
Published in: Transportation Research Part D: Transport and Environment, 2021, Page(s) 102670, ISSN 1361-9209
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.trd.2020.102670

Effectiveness of 2D optimization algorithms considering voluntary speed reduction under uncertain metocean conditions

Author(s): Helong Wang, Xiao Lang, Wengang Mao, Di Zhang, Gaute Storhaug
Published in: Ocean Engineering, Issue 200, 2020, Page(s) 107063, ISSN 0029-8018
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.oceaneng.2020.107063

Efficiency of a Voluntary Speed Reduction Algorithm for a Ship’s Great Circle Sailing

Author(s): Helong Wang, Wengang Mao, Leif Eriksson
Published in: TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Issue 14/2, 2020, Page(s) 301-308, ISSN 2083-6473
Publisher: TransNav, Faculty of Navigation
DOI: 10.12716/1001.14.02.04

A semi-empirical model for ship speed loss prediction at head sea and its validation by full-scale measurements

Author(s): Xiao Lang, Wengang Mao
Published in: Ocean Engineering, Issue 209, 2020, Page(s) 107494, ISSN 0029-8018
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.oceaneng.2020.107494

Impact of ship operations aided by voyage optimization on a ship’s fatigue assessment

Author(s): Xiao Lang, Helong Wang, Wengang Mao, Naoki Osawa
Published in: Journal of Marine Science and Technology, 2020, ISSN 0948-4280
Publisher: Springer Verlag
DOI: 10.1007/s00773-020-00769-8

Conference proceedings (4)

A Simplified Ship Wave Induced Added Resistance Calculation Method and Full-scale Measurements Validation in Head Sea

Author(s): Xiao Lang, Wengang Mao
Published in: Proceedings of the International Offshore and Polar Engineering Conference, 2020
Publisher: The International Society of Offshore and Polar Engineers

Multimodel Superensembling Using Convolutional Neural Networks

Author(s): Erik Larsson (1), Andrea Littardi (2, 3), Mihalis Nicolaou (2), Leif E. B. Eriksson (1), and Waqas Qazi (3) 1 Chalmers University of Technology, Sweden 2 The Cyprus Institute 3 Offshore Monitoring Ltd.
Published in: The 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS), Issue 16 - 17 June 2020, 2019
Publisher: Swedish Artificial Intelligence Society (SAIS)

Multimodel Superensembling Using Convolutional Neural Networks

Author(s): E Larsson, A Littardi, M Nicolaou, L Eriksson and W Qazi
Published in: SAIS, 2021, Page(s) 1-4
Publisher: Chalmers University of Technology

A Spatio-Temporal statistical model to simulate long-term wave environments along ship routes

Author(s): Wengang Mao, Naoki Osawa, Shengzheng Wang, Di Zhang
Published in: . Proceeding of the annual meeting of the Japan Society of Naval Architects and Ocean Engineers, 2019
Publisher: Japan Society of Naval Architects and Ocean Engineers