Resistance prediction of ships using computational fluid dynamics has gained popularity over the years because of its high accuracy and low cost. This paper conducts numerical estimations of the ship resistance and mo...Resistance prediction of ships using computational fluid dynamics has gained popularity over the years because of its high accuracy and low cost. This paper conducts numerical estimations of the ship resistance and motion of a Japan bulk carrier model using SHIP_Motion, a Reynolds-averaged Navier–Stokes (RaNS)-based solver, and HydroSTAR, a commercial potential flow (PF)-based solver. The RaNS solver uses an overset-structured mesh and discretizes the flow field using the finite volume method, while the PF-based solver applies the three-dimensional panel method. In the calm water test, the total drag coefficient, sinkage, and trim were predicted using the RaNS solver following mesh dependency analysis, and the results were compared with the available experimental data. Next, calm water resistance was investigated for a range of Froude numbers. The added resistance in short-wave cases was simulated using both RaNS and PF solvers, and the results were compared. The PF solver showed better agreement with the RaNS solver for predicting motion responses than for predicting added resistance. While the added resistance results could not be directly validated because of the absence of experimental data, considering the previous accuracy of the RaNS solver in added resistance prediction and general added resistance profile of similar hull forms (bulk carriers), the prediction results could be concluded to be reliable.展开更多
文摘Resistance prediction of ships using computational fluid dynamics has gained popularity over the years because of its high accuracy and low cost. This paper conducts numerical estimations of the ship resistance and motion of a Japan bulk carrier model using SHIP_Motion, a Reynolds-averaged Navier–Stokes (RaNS)-based solver, and HydroSTAR, a commercial potential flow (PF)-based solver. The RaNS solver uses an overset-structured mesh and discretizes the flow field using the finite volume method, while the PF-based solver applies the three-dimensional panel method. In the calm water test, the total drag coefficient, sinkage, and trim were predicted using the RaNS solver following mesh dependency analysis, and the results were compared with the available experimental data. Next, calm water resistance was investigated for a range of Froude numbers. The added resistance in short-wave cases was simulated using both RaNS and PF solvers, and the results were compared. The PF solver showed better agreement with the RaNS solver for predicting motion responses than for predicting added resistance. While the added resistance results could not be directly validated because of the absence of experimental data, considering the previous accuracy of the RaNS solver in added resistance prediction and general added resistance profile of similar hull forms (bulk carriers), the prediction results could be concluded to be reliable.
