URANS prediction of roll damping for a ship hull section at shallow draft


YILDIZ B., ÇAKICI F., KATAYAMA T., YILMAZ H.

JOURNAL OF MARINE SCIENCE AND TECHNOLOGY, vol.21, no.1, pp.48-56, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 1
  • Publication Date: 2016
  • Doi Number: 10.1007/s00773-015-0331-4
  • Journal Name: JOURNAL OF MARINE SCIENCE AND TECHNOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.48-56
  • Keywords: Roll damping, Shallow draft, URANS, Ikeda's method, SURFACE COMBATANT
  • Yıldız Technical University Affiliated: Yes

Abstract

It is analytically difficult to calculate roll damping of ships due to the effects of viscosity. Therefore, computational fluid dynamics (CFD) has become a powerful tool in predicting roll damping recently. The unsteady flow around a forced rolling hull section with bilge keels can be calculated using a commercial URANS code which includes the viscous effects. In this study, two-dimensional (2D) roll damping calculations for a S60 midsection with bilge keels including free surface effects are performed for shallow draft case. The first objective of the study is to show whether the URANS code can be used to predict roll damping coefficient correctly. The second one is to show why Ikeda's estimation method is insufficient at shallow draft case. Sinusoidal forced roll motion calculation method of roll damping moment with the help of a sliding interface and a fixed roll axis is successfully applied to predict roll damping coefficient. The calculations are carried out for different roll motion periods and amplitudes to validate the accuracy of the URANS code for different cases. Numerical results are compared with experiments, which were carried out at the towing tank facility of Osaka Prefecture University (OPU), and Ikeda's estimation method. The results show that the URANS code is capable of predicting roll damping coefficients in a good agreement with experimental results and can be used further to develop a better model for prediction of roll damping.