Hydrodynamic design and performance analysis of underwater vehicles using CFD

Hydrodynamic design and performance analysis of underwater vehicles using CFD

Cite as: AIP Conference Proceedings 2116, 030009 (2019); https://doi.org/10.1063/1.5113993

Published Online: 24 July 2019

Talha Atta, Zaib Ali, Syed Mudassir Ali, and Emad Uddin

Abstract. Under Water Vehicles (UWVs) are extensively being used for variety of operations. Recently, there has been an increased interest in the design of autonomous unmanned underwater vehicles design (UUVs) as future generation submarines. The aim of this study is to investigate the effect of the various design parameters on the rotary coefficients of one such UWV i.e. a submarine SUBOFF model. The rotary coefficient has been calculated using the numerical simulations. The effect the wall roughness, linear velocity, rotation speed has been studied using the steady state Reynolds Averaged Navier-Stokes (RANS) simulations. The study helps to understand the underlying hydrodynamic phenomenon showing the dependence of these parameters on the hydrodynamics of the underwater vehicles.

CONCLUSION

A steady state CFD simulation of the rotary arm test on SUBOFF model was performed. Rotary coefficient obtain from graph of sways force and angular velocity shows that the establish models can provide approximation of result within 6.13 % of error when compared to experimental data. The parametric study of the SUBOFF model shows that the increase in linear velocity increases the pressure development on SUBOFF model while an increase in angular velocity will decrease the pressure development of SUBOFF model due to change in windward projected area, local drift angle and change in fluid flow velocity over the SUBOFF model. For the equal amount of change in linear and angular velocity, the linear velocity produces 15 % more pressure difference as compared to angular velocity. Increase in wall roughness produce very minute effect and decrease the pressure of SUBOFF surface. The future work aims to numerically study the effect of other parameters and then to use the results for design optimization using the optimization algorithms.