CFD-BASED SIMULATION OF THE FLOW AROUND A SHIP IN OBLIQUE MOTION AT LOW SPEED

Ships tend to maneuver in oblique motion at low speed in situations such as turning in a harbor, or during offloading, dynamic positioning and mooring processes. The maneuverability criteria proposed by IMO are valid for ships sailing with relatively high speeds and small drift angles, which are inadequate to predict ship maneuverability in low speed condition. Hydrodynamic performance of ships maneuvering at low speed is needed to know for safety issues. A CFD-based method is employed to predict the flow around an Esso Osaka bare hull model in oblique motion at low speed, where the drift angle varies from 0° to 180°. The URANS method with the SST k-ω model is used for simulating ship flows with drift angles 0°~30° and 150°~180°, and DES method for simulating ship flows with drift angles 40°~150°. Verification and validation studies are conducted for drift angles of 0° and 70°. The vortex structures at typical drift angles of 0°, 30°, 50°, 70°, 90° and 180° are analyzed. The effects of drift angle and ship speed are demonstrated.

The Impact of Augmented Reality Techniques on Cartographic Visualization

Augmented reality (AR) is playing an increasingly important role in a variety of everyday application scenarios. Users are not completely disconnected from the current sensory influences of reality. They are merely confronted with additional virtual objects that are projected into reality. This allows users to obtain additional spatial information, which makes this technology interesting for cartographic applications (e.g. navigation). The dynamic positioning of the superimposed image in the scene being viewed is crucial for the generation of AR elements displayed correctly in terms of perspective. Understanding these technical basics is an important prerequisite for the cartographic use of augmented reality. The different techniques influence the visualization and the perception of AR elements in 3D space. This article highlights important visualization properties of current augmented reality techniques.

Synchronization Control of Dynamic Positioning Ships Using Model Predictive Control

Underway replenishment is essential for ships performing long-term missions at sea, which can be formulated into the problem of leader-tracking configuration. Not only the position and orientation but also the velocities are required to be controlled for ensuring the synchronization; additionally, the control inputs are constrained. On this basis, in this paper, a novel synchronization controller on account of model predictive control (MPC) for dynamic positioning (DP) ships is devised to achieve underway replenishment. Firstly, a novel synchronization controller based on MPC is devised to ensure the synchronization of not only the position and orientation but the velocities; furthermore, it is a beneficial solution for its advantages in handling the control input constraints ignored in most studies of underway replenishment. Secondly, a neurodynamic optimization system is applied to the implementation of MPC, which can improve the computational efficiency and shorten the simulation time. Thirdly, stability, frequently neglected by traditional MPC, is ensured by the means of adding a terminal cost function exported from the Lyapunov equation into the objective function. Finally, the effectiveness and advantages of the proposed control design are illustrated by extensive simulations.

Tuning for robust and optimal dynamic positioning control in BlueROV2

A tuning approach for the robust and optimal dynamic positioning control of BlueROV2 subjected to currents with varying speeds and headings is presented. A 2D planar dynamic model of BlueROV2 is developed in Matlab/Simulink and used for the study. The surge, sway and yaw motions are controlled by individual PID controllers. An extensive sensitivity study is carried out on a total of nine cases with different current speeds, current headings, and measurement noise levels. The results show that tuning a model solely using step responses from a linearized model might not produce optimal results. Further it is important to verify the system responses in time domain after tuning. Finally, it is observed that re-tuning the controllers for each simulation case may lead to better performance. However, it is also shown that the base case controller gains are sufficiently robust and lead to good performances for the other simulation cases.