Mattias Liefvendahl

Implicit and Explicit Subgrid Modeling in LES Applied to a Marine Propeller

The flow around a four-bladed marine propeller in homogeneous inflow and in non-cavitating conditions is investigated using Large Eddy Simulation, LES. Explicit, using a k-equation eddy viscosity model, and implicit subgrid modeling are compared for both the standard LES formulation as well as a mixed formulation containing the, so called, scale similarity term. A wall-modeled approach is used on a relatively coarse grid, containing 5.5 million cells, for the full propeller in order to mimic a future applied computation including the ship hull. The implicit modeling is of particular interest in cavitation simulation, where the interaction between an explicit subgrid model and the liquid-vapor interface may cause numerical and modeling problems. All simulations yield fairly similar results, although the implicit LES gives better prediction of the global performance of the propeller. The agreement with experimental data is good close to the propeller, but the simulated flow structures diffuses quickly at the present grid resolution.

LES and DES of high Reynolds Number Wall Bounded Flows

High Reynolds number wall bounded flow is here investigated using Large Eddy Simulation (LES), Detached Eddy Simulation (DES) and Reynolds Averaged Navier Stokes (RANS). The first case considered is the fully developed turbulent channel flow at Re 395, 590, 1800 and 10,000. This flow clearly indicates the development of the undisturbed boundary layer and related events, such as streaky structures, hairpin vortices and ejection events. The second case is the flow over an axisymmetric hill in a channel, here the flow contains complex structures such as a turbulent boundary layer with several unsteady separations and reattachments. It is three-dimensional due to both streamwise and spanwise pressure gradients on the lee-side of the hill. The shallowness of the separation region makes the flow a demanding test case for any computational fluid dynamics model. The third case is the flow past an axisymmetric submarine hull with an elliptic forebody and a smoothly tapered stern the DARPA Suboff model AFF-1. This flow case is highly demanding due to the long midship section, on which the boundary layer is developed, in combination with the elliptic forebody and the tapered stern. Both LES and DES performs well in all cases considered, while RANS has slightly lower accuracy in the channel flow and the axisymmetric hull, and fails to predict some flow features for the axisymmetric hill. Also DES has some problems with the axisymmetric hill case, related to the inlet condition of the modified eddy viscosity.

Large Eddy Simulation of High Re Number Partially Separated Flow

The predictive capability for Large Eddy Simulation (LES) for flows with unsteady separation at curved surfaces is investigated. LES with near wall modeling is applied and a range of subgrid models is evaluated for four different validation cases for which experimental flow measurement data is available. A novel model for the simulation of the effect of boundary layer tripping devices used in experiments is also proposed and evaluated. The validation focuses on the mean velocity distribution in the region of separation, as well as on the skin friction and the surface streamlines. The flow physics of separation for these four cases is illustrated and discussed in detail.

Estimates of source spectra of ships from long term recordings in the Baltic sea

Estimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the Island Oland. Data from over 2000 close-by passages were recorded during a five month period from August to December 2014. For each passage, ship-to-hydrophone transmission loss (TL) spectra were computed by sound propagation modelling using 1. bathymetry data from the Baltic Sea Bathymetry Database (BSBD) 2. sound speed profiles from the HIROMB oceanographic model, 3. seabed parameters obtained by acoustic inversion of data from a calibrated source and 4. AIS data providing information on each ships position. These TL spectra were then subtracted from the received noise spectra to estimate the free field source level (SL) spectra for each passage. The SL were compared to predictions by some existing models of noise emission from ships. Input parameters to the models, including e.g. ship length, width, speed, displacement and engine mass, were obtained from AIS data and the STEAM database of the Finnish Metereological Institute (FMI).