It’s often thought if a particular solution is good for one problem it’ll be good for another. Unfortunately this is not always the case, especially when applying CFD to boats; different problems lend themselves to different solution techniques.

For example a linear wave making method can give good results if you’re interested in how the wash from a boat may impact on the shoreline but won’t give good results as to the effect on performance of many detailed hull features. A RANS code, on the other hand, will be able to quantify the effects of details with a high degree of accuracy but is likely to dampen out the wave pattern a significant distance away from the hull surface. See whole thread

One downside of RANS codes in general is their tendency to be diffusive. In the case of a vessel with multiple hulls like a catamaran, this can be a huge source of uncertainty as the interference between the wave patterns of the two hulls has a pronounced effect on the resistance of the vessel as a whole. To determine the suitability of RANS in resolving these effects a set of simulations was conducted, calculating the resistance of a catamaran for a series of demi-hull spacings. Read more

Continuing on from the last newsletter...

The first simplification is applied to turbulence. To solve the navier-stokes equations directly for all scales of turbulence in a fluid would require mesh resolution too fine to be practical. To get around this, time averaged equations such as RANS (Reynolds-averaged navier-stokes) are used in conjunction with turbulence models. Turbulence modeling is complicated but in its simplest form model the energy dissipated through small scales of turbulence as a transportable quantity that can be resolved throughout the fluid and likewise be affected by and effect the flow.

An even bigger simplification is to ignore viscosity entirely. With the Navier-Stokes equation simplifies to the Euler equation. Euler codes are unpopular primarily due to the difficulty getting stable results in practical geometries.