Drag force-internal volume relationship for underwater gliders and drag coefficient estimation using machine learning

The relationship between drag force and internal volume of torpedo shaped underwater glider hulls has been investigated using an ensemble analysis method. Basis dimensions of 1.50 m for length and 0.20 m for diameter are selected by considering dimensions of commercial and academic gliders. 9 different forms are used for analyses in two groups (constant length and constant diameter). Nose and back sections are kept constant for all forms. The forms are analyzed in 4 different velocities and 6 different angles of attacks using the open source CFD (Computational Fluid Dynamics) software OpenFOAM. The ensemble resulted in 216 simulations. Simulation results are then used to estimate volumetric drag coefficient values for streamlined body of revolution hull forms under angle of attack. Multivariate linear regression machine learning method was used for the estimations and generation of empirical relation. The results show that volume increase effects gliders much more when angle of attack and glider velocity increases. However, for glider with velocities ranging from 0.3 to 0.6 m/s the increase in the volume does not contribute to drag force as much. Resulting empirical formula gives accurate estimation of drag coefficients for bodies of revolution experiencing 0–10 degrees of attack angle.