Wave added resistance implementation in a routing software

Abstract

In the context of global warming, all sectors must rapidly decrease their dependence on fossil fuels in order to cut down their CO2 emissions. Naturally, the maritime sector is no exception and is actively looking for carbon free alternatives. Among the different technologies developed to achieve this goal, the Wind Assisted Ship Propulsion is quite promising as it could cut down a ship’s fuel consumption by up to 30%.
VPLP design aims to develop such technology. However in the performance prediction phase, the company needs to be able to assess the wave added resistance. The scientific literature has provided us with a good knowledge of this resistance and some semi-empirical methods to evaluate it. Yet, these models can be quite different and it is important to test which one is the most efficient for a RoRo ship depending on the case study. A python package has been made to compute it easily depending on simple ship parameters and sea conditions. Furthermore, four methods are included in the program and the latter can choose which one is best adapted depending on the case study.
Another challenge with wind assisted propulsion is the need for an adapted routing system. It needs to be able to find the best route to optimize the use of sails and thus reduce the fuel consumption. As an input, it requires a polar matrix with fuel consumption depending on the wind conditions and the ship’s speed. The wave added resistance can have a large impact on fuel consumption (around 20%more than only calm water resistance) therefore, it was implemented and added. The program now takes 6D polar matrices which also include the significant wave height, the wave length and the wave angle. It enables to have a more realistic and relevant routing system. Furthermore, a study on routing software’s space step was conducted to find its influence on the results.
Eventually, the company often needs to perform statistical weather studies. These studies can improve the performance prediction loop by showing the most frequent weather conditions and their impact on a ship or a ship’s journey. It can be used to implement the wave added resistance or even for engine/propeller matching. The study usually use data from the last years. However, the polar matrices can be quite large with many improbable cases which ought to be optimized. A program was coded to retrieve wave data and perform studies on the different sea conditions a ship could encounter over a journey. One can now check for the most frequent wind/wave combinations and adjust the design or the VPP loop.
Eventually, some of the limits of this project are mentioned. First of all, the wave added resistance program requires to be validated more thoroughly and it is planned to be compared with future onboard data. Furthermore, many steps in the routing software or within the statistical study tools have a large computational time. Some solutions are suggested but there is still room for improvement. Eventually, some files are getting particularly large and programs struggle to handle it. A judicious choice in the number of data could help reduce the sizes of some documents.
Overall, the tasks were completed and the new programs are currently being used by the company. Although validation measures and improvements must be done, this thesis can help companies to improve sailing cargo ships’ VPP. With the right routing software, wind assisted propulsion can be used to their full potential and help reduce the shipping industry’s carbon footprint.
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