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This study presents a comparison of the hydrodynamic responses generated by a boundary element method with linear free-surface boundary conditions and a volume of fluid RANSE CFD method with nonlinear surface capturing for a shallowly submerged prolate spheroid travelling with constant forward velocity. Observing the effects of free-surface proximity and forward velocity on the hydrodynamic forces and wave disturbance between the two numerical methods reveals the influence and importance of considering a nonlinear free-surface. The forces and moments acting on the spheroid using the nonlinear method are generally larger than the linear method showing that nonlinear effects are important in the calculation of wave making resistance. The difference between the linear and nonlinear methods grows as submergence decreases or wave making increases. An additional phenomenon is shown where the difference between the methods displays a trend with respect to Froude number and depth that is similar to the values being compared. The physical response of these nonlinear effects is seen in the steepening of surface waves near the body, which breaks some of the assumptions made in the linear boundary element method.

This study concerns CFD-informed methods to obtain the derivatives of lumped parameters maneuvering models for underwater vehicles. The uncertainty in maneuvering predictions due to the method of obtaining hydrodynamic derivatives is discussed and assessed. Hydrodynamic derivatives are typically obtained from planar motion mechanism tests in both planes. Unsteady RANSE solvers offer the possibility to simulate the same captive steady and unsteady maneuvers to obtain these derivatives by identification procedures. Upon comparing some general representations of such identification procedures, it is found that the values of the estimated coefficient vary due to the method used. The uncertainty affecting the derivatives is propagated onto standard maneuvering predictions. This article discusses the level of uncertainty related to each method and offers insight based on the type of derivatives that vary as well as the type of maneuvers that are affected through the application on two different underwater vehicles. It is observed that there is a recognizable difference in the accuracy and applicability of these methods and a possible way forward is proposed.

The current study is carried out to investigate complex near-wall flow effects like separation and cross-flow and their impact on UAV performance. Furthermore, the study proposes using the novel SSG/LRR-ω-γ model, which is a second-order closure, Reynolds stress transport-based transition turbulence model, that can help capture the near-wall flow observed in low Reynolds number flows. To prove the credibility of the model, it is validated against experimental data available for the DJI Phantom 3 propeller. The SSG/LRR-ω-γ model is then compared against other transition models as well as fully turbulent models and was found to show better performance when assessed on their ability to predict rotor performance characteristics as well as near-wall flow behavior.