Evaluation of hybrid RANS/LES models for prediction of flow around surface combatant and Suboff geometries

• Published in: Computers & fluids Vol. 88; pp. 834 - 849
• Main Authors: Bhushan, S., Alam, M.F., Walters, D.K.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15-12-2013
• Subjects: Computational fluid dynamics; Detached eddy simulation; Fluid flow; Hybrid RANS/LES; Mathematical analysis; Mathematical models; Ship hydrodynamics; Turbulence; Turbulence modeling; Turbulence models; Turbulent flow; Turbulence modeling; Ship hydrodynamics; Hybrid RANS/LES
• ISSN: 0045-7930; 1879-0747
• DOI: 10.1016/j.compfluid.2013.07.020

•Application of recently developed hybrid RANS/LES (DHRL) model for ship flows.•URANS, DES and DHRL predictions are compared for appended DARPA Suboff.•DHRL model addresses the limitation of DES model in triggering resolved turbulence.
Predictive capabilities of hybrid RANS/LES models are compared for single-phase flow over a surface combatant at Re=5.3×106 and an appended DARPA Suboff model at Re=1.2×107. The turbulence models used in the study are: k–ω shear stress transport (SST)-URANS; Spalart Allmaras based detached eddy simulation (SA-DDES); k–ω based improved delayed detached eddy simulation (KW-IDDES); and a dynamic hybrid RANS/LES (DHRL) model coupling SST and implicit LES. For the surface combatant case, both SA-DDES and KW-IDDES predicted <1% resolved turbulence, whereas DHRL predicted up to 70% resolved turbulence. The SST-URANS, SA-DDES, KW-IDDES and DHRL predictions compared within 4.23%, 4.14%, 5.88% and 3.88% of the experimental data, respectively. For the Suboff case, both the SA-DDES and KW-IDDES predicted only limited resolved turbulence in the sail wake and downstream of the fins, whereas DHRL predicted resolved turbulence levels comparable to LES. The averaged error for the mean velocity profile at propeller plane for SST-URANS, SA-DDES, KW-IDDES and DHRL predictions was 6.4%, 8.9%, 13.1% and 3.0%, respectively. The corresponding errors for the turbulence variables were 44%, 70%, >100% and 28%, respectively. Overall, the DHRL model performed best among the turbulence models tested, and KW-IDDES performed worst. The study indicates that the DHRL approach has the potential to provide accurate mean flow predictions while resolving small-scale turbulent structures. Results also highlight the importance of the wall function formulation for accurately resolving mean skin friction coefficient, especially over smooth regions of the hull.