Analysis of manoeuvring characteristics through sea trials and simulations

Abstract

In recent years, Autonomous Surface Vehicles have secured the focus of major research and industrial initiatives around the world. Following this trend in the wake of fourth industrial revolution of oceans, Marine Autonomous Surface Ships (MASS) have become the focus of numerous research. In order to shift from conventional ships to autonomous transportation, manoeuvring data collected through real-ship trials have to be available, and analysed. In this study, manoeuvring characteristics of a real ship were studied over a period of three years, data were collected and analysed to identify changes of manoeuvring characteristics over time. Real-ship data were then compared with simulation data to validate a manoeuvring simulator program. Through the real-ship experiments, not only the simulation results were validated, but also the possibility of predicting ship manoeuvrability using simulations in controlled environments was identified. In addition, the importance of accumulation of manoeuvring data in helping future designs of ships with similar characteristics is identified.

The Dynamics of a Turning Ship: Mathematical Analysis and Simulation Based on Free Body Diagrams and the Proposal of a Pleometric Index

“…The turning radius calculated from the ship data provided by Gug et al [29] was 179.7 m (Figure 15); the corresponding angle of attack AoA at steady state that resulted from the simulation was 4.07° (Figure 15). Despite the use of flat plate CD, CL, and COP data, the calculated turning radius R correlated well with the average radius of the turning circles (163.28 m and 183.56 m) experimentally determined from GPS data by Gug et al [29] (p. 10, Table 7).…”

“…The right-hand side of Equation (29), in antilogarithmic form of 𝑚 𝐴 𝜌 = 𝑚 𝐿 𝐷 𝜌 (30) but best expressed in the logarithmic form of Equation ( 29), explains the turning dynamics from the physical data of the ship or input data of the model. Increasing the mass m has the same dynamic effect as reducing any of the three parameters in the denominator of Equation (30), that is, length L, draught D, or water density .…”

“…Table 1), ed by randomly changing the combinations of m, L, and D (Monte Carlo method). h an initial speed of 9 m/s [29] (p. 3, Table 2). Gug et al [29] calculated the mean f the turning circle from the ship's GPS-data, which were 163.28 m and 183.56 m on e and starboard side, respectively [29] (p. 10, Table 7).…”

“…h an initial speed of 9 m/s [29] (p. 3, Table 2). Gug et al [29] calculated the mean f the turning circle from the ship's GPS-data, which were 163.28 m and 183.56 m on e and starboard side, respectively [29] (p. 10, Table 7). The simulation was lated with the ship properties and initial speed provided by Gug et al [29] as input f the model, and the radius of the turning circle as well as the AoA were determined he input data.…”

Effect of Sampling Rate in Sea Trial Tests on the Estimation of Hydrodynamic Parameters for a Nonlinear Ship Manoeuvring Model

“…Sea trials play a crucial role in ensuring the effective manoeuvring and overall performance of a ship before it is put into service [24][25][26]. These trials provide an opportunity to assess the vessel's handling characteristics, responsiveness, and stability in real-world maritime conditions.…”