Introduction - Hydrofoils are often used for high-performance craft. They enable the hull to rise out of the water and reduce drag. A recurring problem is ventilation, this is the presence of a cavity filled with ambient air on the lifting surface. Ventilation causes the lift of the hydrofoil to decrease drastically. A lot of research has been done on ventilation behaviour. Ventilation remains a stochastic phenomenon to this day. The same operational conditions do not yield the same flow behaviour, a correlation between the pressure on the lifting surface and ventilation behaviour might exist. This research is an intermediate step towards finding a correlation between pressure on the surface of a foil and ventilation, making ventilation repeatable. The main goal of this research is to find out if a full surface pressure reconstruction can aid the search for a correlation between pressure and ventilation.

Method - The test geometry is a NACA0012 surface-piercing hydrofoil with pressure measured using 2 rows of 15 pressure tappings. Extension pieces are used to obtain the span-wise pressure distribution while keeping the submerged span constant. The test program has three sets: all vertical runs (Set 1), high roll angle runs (Set 2), and runs with ventilation (Set 3). During the experiment, the loads are measured with force transducers on a frame that measures forces in 6 degrees of freedom. The calibration of the force transducers is performed prior to the experiment. The calibration of the pressure sensors is done first using a 9 meter water column before the experiment and during the experiment in the towing tank, extra re-calibration (stepped runs) data is collected. The collected force measurement data is processed to attain the lift and drag coefficients. The pressure measurements are translated to the pressure coefficient and placed in a matrix on the right location of the lifting surface.

Results - Based on repeated experimental runs the percentage differences are obtained on sensor and array levels. 30% of the sensors have a percentage difference of more than 10%, while the maximum difference for an entire array is 2.5%. A cross-check between the upper and lower arrays showed a percentage difference above 15% for 28% of the sensors, with a maximum difference of 1.2% at the array level. The pressure distributions at 0∘ roll angle, from Set 1, match the general pressure distribution characteristics. Comparing the 3D lift coefficient computed from the pressure measurements to that of the force data or an empirical method yields ambiguous results. The 3D lift coefficient based on the pressure measurement is within a 4% difference to Xfoil. The result of the high roll angle runs, Set 2, show the effect free-surface proximity has on the chord-wise pressure distribution. For the shallowest pressure reconstructions, close to the free-surface, the pressure distribution shows a minor peak near the leading edge after which the curve drops to near zero quickly. The operational conditions do not affect the quality of measurements. During two runs ventilation occurred, this is Set 3. The time-traces of the three forwardmost sensors show a dip prior to ventilation, with one sensor displaying an oscillating response. It is hypothesised that this is the position where ventilation is induced, but based on the results this can not be proven. All sensor response follows the same pattern when the ventilation bursts over the surface. The set-up is able to capture quick pressure changes.

Conclusion -The percentage difference is too high for too many sensors. On the array level, however, the difference is considered small enough. The results of set 1 are in good agreement with known data. The results obtained at 60∘ roll angle are concluded to be of the same quality as for 0∘ roll. The method is capable of providing results in a wide range of operational conditions. Based on the ventilation runs, no correlation to pressure reading has been found. The time-traces of the sensors near the leading edge of these runs do show fluctuations prior to ventilation. With more ventilation runs available, it is highly likely that a correlation can be established. Due to the slim data set, it is possible that the conclusions drawn will be refuted in the future when a larger data set is available. Currently, the goal has not been achieved, and it cannot be stated with certainty that the method used here to attain a full surface pressure reconstruction can be used to correlate pressure to ventilation.