This article presents two approaches to simulate maneuvers of a model radio-controlled submarine In the direct simulation approach, rudders, stern planes, and propellers are gridded and treated as moving objects using dynamic overset technology The second approach couples the overset computational fluid dynamics (CFD) solver and a potential flow propeller code, with both codes exchanging velocities at the propeller plane and wake, body forces, and propeller forces and moments, whereas rudders and stern planes are still explicitly resolved It is shown that during the maneuvers, the range of advance coefficients does not deviate much from the design point, making a coupled approach a valid choice for standard maneuvering simulations By allowing time steps about an order of magnitude larger than for the direct simulation approach, the coupled approach can run about five times faster The drawback is a loss of resolution in the wake as the direct propeller simulation can resolve blade vortical structures Open water propeller curves were simulated with both the direct propeller approach and the coupled approach, showing that the coupled approach can match the direct approach performance curves for a wide range of advance coefficients Simulations of a horizontal overshoot maneuver at two approach speeds were performed, as well as vertical overshoot and controlled turn maneuvers at high speed Results show that both CFD approaches can reproduce the experimental results for all parameters, with errors typically within 10%

Submarine Maneuvers Using Direct Overset Simulation of Appendages and Propeller and Coupled CFD/Potential Flow Propeller Solver

A survey on energy efficiency in underwater wireless communications

Underwater Free-Space Optical Power Transfer: An Enabling Technology for Remote Underwater Intervention

This paper presents a docking station heave motion prediction method for dynamic remotely operated vehicle (ROV) docking, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). Due to the limited power onboard the subsea vehicle, high hydrodynamic drag forces, and inertia, work-class ROVs are often unable to match the heave motion of a docking station suspended from a surface vessel. Therefore, the docking relies entirely on the experience of the ROV pilot to estimate heave motion, and on human-in-the-loop ROV control. However, such an approach is not available for autonomous docking. To address this problem, an ANFIS-based method for prediction of a docking station heave motion is proposed and presented. The performance of the network was evaluated on real-world reference trajectories recorded during offshore trials in the North Atlantic Ocean during January 2019. The hardware used during the trials included a work-class ROV with a cage type TMS, deployed using an A-frame launch and recovery system.

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J. Siesjo

Papers

Resident Autonomous Underwater Vehicle Systems – A Review of Drivers, Applications, and Integration Options for the Subsea Oil and Gas Market