Fibre ropes for offshore station keeping. Polyarylate

2015 ◽  
Keyword(s):  
Station Keeping ◽  
Offshore Station

DC arcjet system for north-south station keeping of geosynchronous satellite

1987 ◽  
Author(s):  
HIROSHI SUZUKI ◽  
KOICHI MIYOSHI ◽  
TAKAO YOSHIKAWA ◽  
RYUICHI NAGASHIMA
Keyword(s):  
Station Keeping ◽  
Geosynchronous Satellite

Station-keeping control design for Earth-Moon L1 librartion point

2019 ◽  
Author(s):  
Thiago Cesar Lousada Marsola ◽  
Sandro da Silva Fernandes ◽  
José Manoel Balthazar
Keyword(s):  
Control Design ◽  
Station Keeping

scholarly journals Station-keeping analysis of an FPSO to prevent collision with SPM using AHTS

2020 ◽  
Vol 557 ◽  
pp. 012055
Author(s):  
A Baidowi ◽  
B Cahyono ◽  
F Ardhiansyah ◽  
T F Nugroho
Keyword(s):  
Station Keeping

scholarly journals ANN-Based Decision Making in Station Keeping for Geotechnical Drilling Vessel

2021 ◽  
Vol 9 (6) ◽  
pp. 596
Author(s):  
Murugan Ramasamy ◽  
Mohammed Abdul Hannan ◽  
Yaseen Adnan Ahmed ◽  
Arun Kr Dev
Keyword(s):  
Decision Making ◽  
Water Depth ◽  
Business Models ◽  
Cost Benefit ◽  
Cost Effective ◽  
Station Keeping ◽  
Operational Information ◽  
Effective Option ◽  
The Cost ◽  
Cost Factors

Offshore vessels (OVs) often require precise station-keeping and some vessels, for example, vessels involved in geotechnical drilling, generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which system to use for a particular operational scenario depends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station-keeping systems. Operational information and cost data are collected for several field operations, and Artificial Neural Networks (ANN) are trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, fieldwork duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators.

Long-Term Electric-Propulsion Geostationary Station-Keeping via Integer Programming

2019 ◽  
Vol 42 (5) ◽  
pp. 976-991 ◽  
Author(s):  
Clément Gazzino ◽  
Denis Arzelier ◽  
Christophe Louembet ◽  
Luca Cerri ◽  
Christelle Pittet ◽  
...  
Keyword(s):  
Integer Programming ◽  
Electric Propulsion ◽  
Station Keeping

scholarly journals Optimal Control for Minimum-Fuel Geostationary Station Keeping of Satellites Equipped with Electric Propulsion

2016 ◽  
Vol 49 (17) ◽  
pp. 379-384 ◽  
Author(s):  
C. Gazzino ◽  
D. Arzelier ◽  
D. Losa ◽  
C. Louembet ◽  
C. Pittet ◽  
...  
Keyword(s):  
Optimal Control ◽  
Electric Propulsion ◽  
Station Keeping
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