Effect of a propeller duct on AUV maneuverability

A number of autonomous underwater vehicles, AUV, are equipped with commercial ducted propellers, most of them produced originally for the remote operated vehicle, ROV, industry. However, AUVs and ROVs are supposed to work quite differently since the ROV operates in almost the bollard pull condition, while the AUV works at larger cruising speeds. Moreover, they can have an influence in the maneuverability of AUV due to the lift the duct generates in the most distant place of the vehicle's center of mass. In this work, it is proposed the modeling of the hydrodynamic forces and moment on a duct propeller according to a numerical (CFD) simulation, and analytical and semi-empirical, ASE, approaches. Predicted values are compared to experimental results produced in a towing tank. Results confirm the advantages of the symbiosis between CFD and ASE methods for modeling the influence of the propeller duct in the AUV maneuverability. (C) 2012 Elsevier Ltd. All rights reserved.

Numerical analysis of control surface effects on AUV

Computational fluid dynamics, CFD, is becoming an essential tool in the prediction of the hydrodynamic efforts and flow characteristics of underwater vehicles for manoeuvring studies. However, when applied to the manoeuvrability of autonomous underwater vehicles, AUVs, most studies have focused on the de- termination of static coefficients without considering the effects of the vehicle control surface deflection. This paper analyses the hydrodynamic efforts generated on an AUV considering the combined effects of the control surface deflection and the angle of attack using CFD software based on the Reynolds-averaged Navier–Stokes formulations. The CFD simulations are also independently conducted for the AUV bare hull and control surface to better identify their individual and interference efforts and to validate the simulations by comparing the experimental results obtained in a towing tank. Several simulations of the bare hull case were conducted to select the k –ω SST turbulent model with the viscosity approach that best predicts its hydrodynamic efforts. Mesh sensitivity analyses were conducted for all simulations. For the flow around the control surfaces, the CFD results were analysed according to two different methodologies, standard and nonlinear. The nonlinear regression methodology provides better results than the standard methodology does for predicting the stall at the control surface. The flow simulations have shown that the occurrence of the control surface stall depends on a linear relationship between the angle of attack and the control surface deflection. This type of information can be used in designing the vehicle’s autopilot system.