imental results for essentially all the turbulence models and grid densities considered, was consider good. The numerical results in the shaded plots in Figure 8 used the fine grid Baldwin-Lomax algebraic turbulence model.

4.0 OBSERVATIONS AND COMMENTS

The organizing committee asked that certain questions be addressed in this paper. Among these questions are: (1) what are the limitations of RANS codes and how well do they approximate the physics of real flows, (2) how well do the various turbulence models approximate the physics of flows, and for what type of flows of interest are the various turbulence models applicable, (3) how does grid selection influence the solution, (4) how does one check on uncertainty in the calculation, (5) have RANS codes been pushed as far as they can be and what future research needs to be done for development of RANS codes, and (6) what will be the new tools for the future? The authors do not feel qualified, capable, nor comfortable in attempting to answer these questions in a definitive way. However, something will be said about each topic, in no particular order, if for no other purpose than to stimulate thinking in those that may be capable of answering these questions.

4.1 An Application-Oriented Perspective on Flow Simulations and Turbulence Models

The resolution needed for flow simulations (number of points and local distributions) is affected by both geometric and physical factors. The geometry introduces its own length scales and resolution requirements. For example, a submarine geometry typically has elements such as a hull, sail, sail/bow planes, stern appendages, propulsor, control surfaces and gaps, and corner regions near adjoining surfaces.

Although the physical flow structure varies widely from problem to problem, external flow problems often have a uniform free stream (potential flow) with shear-layer development (laminar, transitional or turbulent) near solid surfaces. These surface layers require local resolution and also have important influences on the remaining flow structure. Vorticity generated on surfaces is transported by convection and diffusion, and the surface shear layers may themselves separate, detach or lift off of the surface, transporting vorticity and turbulence well away from the surface. This in turn generates new flow structures requiring local resolution, including vortices and wakes.

If a surface layer is turbulent, then turbulent correlations or shear stresses arising from time averaging (RANS) or space averaging (LES) exert an important local influence on the flow. Once a surface layer detaches, the vorticity transported into the flow can manifest itself as regions of rotational inviscid flow in which turbulence itself (if present) may have negligible

Figure 8. Numerical and Experimental Data Comparisons for Propeller P5168



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