Performances of Different Turbulence Models for Simulating Shallow Water Sloshing in Rectangular Tank

Mohammad Kazem Tahmasebi , Rahim Shamsoddini , Bahador Abolpour

Journal of Marine Science and Application ›› 2020, Vol. 19 ›› Issue (3) : 381 -387.

PDF
Journal of Marine Science and Application ›› 2020, Vol. 19 ›› Issue (3) : 381 -387. DOI: 10.1007/s11804-020-00162-2
Research Article

Performances of Different Turbulence Models for Simulating Shallow Water Sloshing in Rectangular Tank

Author information +
History +
PDF

Abstract

Liquid sloshing is a common phenomenon in the transportation of liquid-cargo tanks. Liquid waves lead to fluctuating forces on the tank walls. If these fluctuations are not predicted or controlled, for example, by using baffles, they can lead to large forces and momentums. The volume of fluid (VOF) two-phase numerical model in OpenFOAM open-source software has been widely used to model the liquid sloshing. However, a big challenge for modeling the sloshing phenomenon is selecting a suitable turbulence model. Therefore, in the present study, different turbulence models were studied to determine their sloshing phenomenon prediction accuracies. The predictions of these models were validated using experimental data. The turbulence models were ranked by their mean error in predicting the free surface behaviors. The renormalization group (RNG) kε and the standard kω models were found to be the best and worst turbulence models for modeling the sloshing phenomena, respectively; moreover, the SST kω model and v2-f k-ε results were very close to the RNG kε model result.

Keywords

Volume of fluid / Turbulence models / Shallow water sloshing / Free surface / OpenFOAM / Liquid tanks / Renormalization group

Cite this article

Download citation ▾
Mohammad Kazem Tahmasebi,Rahim Shamsoddini,Bahador Abolpour. Performances of Different Turbulence Models for Simulating Shallow Water Sloshing in Rectangular Tank. Journal of Marine Science and Application, 2020, 19(3): 381-387 DOI:10.1007/s11804-020-00162-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

AI Summary AI Mindmap
PDF

104

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/