Clustering Applied to Large Sets of Environmental Conditions for Selecting Typical Scenarios for Ship Maneuvering Real-Time Simulations

The methodology described in this paper is used to reduce a large set of combined wind, waves, and currents to a smaller set that still represents well enough the desired site for ship maneuvering simulations. This is achieved by running fast-time simulations for the entire set of environmental conditions and recording the vessel’s drifting time-series while it is controlled by an automatic-pilot based on a line-of-sight algorithm. The cases are then grouped considering how similar the vessel’s drifting time-series are, and one environmental condition is selected to represent each group found by the cluster analysis. The measurement of dissimilarity between the time-series is made by application of Dynamic Time Warping and the Cluster Analysis is made by the combination of Partitioning Around Medoids algorithm and the Silhouette Method. Validation is made by maneuvering simulations made with a Second Deck Officer.

Scale Effects on Ship Maneuverability Using RANS

Predicting ship maneuverability is one of the important topics in ship engineering. However because of the huge difference between model and full scale Reynolds number (Re), it is almost impossible to predict full scale ship maneuverability using conventional methods such as model test. On the other hands, with the developments of computational technologies and computational fluid dynamics (CFD) techniques, CFD simulations are widely applied on ship maneuvering problems (e.g. Stern et al., 2011). Moreover some of the researchers start the CFD simulation with full scale Re especially on propulsion problems (e.g. Tezdogan et al., 2015) which showing reasonable results. Therefore, in this paper, captive maneuvering simulations (rudder angle test) in model/full scale Re on KVLCC2 are carried out using Reynolds-averaged Navier–Stokes (RANS) solver NAGISA (Ohashi et al., 2014) with the overset gird method UP_GRID (Kodama et al., 2012). And the results between model and full scale simulations are compared in maneuvering coefficients and flow field to reveal the scale effect on ship maneuverability.

Use of Overset Mesh to Allow Dynamic Deflection of Tight-Fitting Control Surfaces in CFD Simulations

The development of vehicle maneuvering simulations based within computational fluid dynamics (CFD) environments demands that vehicle control surfaces be dynamically deflected during such simulations. This paper details the process of developing and testing CFD simulation methods that allow for the deflection of a specific AUV’s control surfaces. This task is made particularly challenging by the geometry of the AUV, as its moving control surfaces fit very closely to stationary fixed strakes and the AUV’s hull (a fairly common trait among this class of vehicles). After ruling out embedded and deformable mesh approaches, an overset mesh method is applied. Steady-state simulations with this overset mesh show general agreement with static mesh simulations. The two approaches do, however, highlight the mesh sensitivity of CFD simulations in their ability to predict the onset of stall.

Review of Hydrodynamic and Nautical Studies for Offshore LNG Operations

In this paper we review hydrodynamic and nautical studies for offshore LNG operations. Based on full mission bridge simulations, model tests campaigns, time domain simulations, fast time maneuvering simulations and downtime assessments, we address the major findings in terms of weather limitations, tugboat requirements and other critical aspects for the berthing and offloading operation.

Submarine Maneuvering Simulations of ONR Body 1

The application of computational fluid dynamics method to the submarine maneuvering simulations of ONR Body 1 is presented. ONR Body 1 is an unclassified submarine radio controlled model with propeller and control surfaces. Unsteady Reynolds-averaged Naviers-Stokes equations of fluid flow is coupled to the six degrees-of-freedom equations of motion of a rigid body via user coding to predict the instantaneous position and body orientation. Propeller and control surface motions are accounted for by using the moving mesh feature integrated into the solution procedure which allows sliding interfaces between different mesh blocks of the computational domain (for propeller rotation), as well as mesh distortion (for control surface deflection). This offers the flexibility of using a single computational grid for the entire simulation period. The maneuvers simulated include a constant depth and heading run as well as a horizontal overshoot maneuver using conditions consistent with the experiment. Predicted results show favorable agreement with experimental measurements.