Going with the Flow

Abstract

The goal of achieving net-zero emissions by 2050 requires innovative ways to reduce energy consumption in all sectors. This thesis presents an in-depth analysis on the effect of coastal currents on energy consumption of sailing dredging vessels and the potential to make use of these currents to minimize energy consumption in dredging projects. To model the highly dynamic and time-dependent currents of the North Sea, an analytical solution for the tidal-induced currents and residual density-driven currents was used to create a synthetic 3D flow field, respectively derived by Prandle and Heaps. To quantify the energy consumption of dredging vessels sailing through a 3D flow field, a python-based model was developed. This model utilizes the Holtrop and Mennen method to calculate the sailing speed corresponding to a desired engine power, with a modification to account for current-induced drag resistance on the rudder caused by currents perpendicular to the sailing direction. The model was validated with sensory vessel data of Van Oord containing information of a dredging project in the North Sea, in combination with measured data for the currents at the location of the project. The validated model was used to explore a dredging strategy for a sand nourishment project that minimizes energy consumption by waiting for favourable marine currents before sailing. A sand nourishment project was chosen because the primary cross-shore movement of the vessel interacts with the bi-weekly occurrence of alternating cross-shore currents. Two cases were simulated, a hypothetical case in which the vessel does not consume energy when waiting, and a realistic case in which the vessel's energy consumption continues due to utilities such a lighting and heating of on-board accommodations. The hypothetical case showed a reduction of energy consumption of 3\% when sailing with the cross-shore currents as opposed to neglecting these currents, which is at the lower boundary of the energy reduction due to voyage optimization predicted by IMO (1\% - 10\%). However, the energy reduction was outweighed by energy consumption during waiting in the realistic case, making this strategy unsuitable for conventional dredging vessels. The model developed in this thesis can be of significant value for both dredging companies as well as researchers. These stakeholders can use the model to plan and optimize dredging activities, reduce environmental impact, and identify areas for innovation and improvement in the dredging industry.