DNV GL is officially starting an advanced hull and propeller performance analytics module along the lines of its new fleet performance ECO Insight management service. The module derives from the use of computational fluid dynamics (CFD) methods aimed at correcting for any changing operational conditions. When compared to existing approximate or experimental methods the new module is actually able to produce far more accurate results.
Fuel efficiency is still a major concern when regarding the purposes of shipping, but tracking hull along with propeller degradation is an issue without any adequate solution. Some experts have suggested that resulting from hull fouling the world fleet could potentially be sailing with roughly 30% of additional resistance and thus significantly higher fuel consumption levels. Performing hull and propeller cleaning procedures on a regular basis has already been acknowledged as an important improvement lever by a large number of shipping companies. The question, however, of when and how the procedure should be properly performed has not yet been a matter that is addressed systematically.
Hull and propeller performance computations are able to display that amount of resistance that is added over a particular time period as a result from fouling, via a thorough analysis of the gap that is evident between a vessel’s theoretical and measured power demand, after correcting for various influences such as speed, draft, trim, weather and other different operating conditions.
“We use information and specific data that is actually already collected by shipping companies,” Dr Torsten Büssow, DNV GL’s Head of Fleet Performance Management, elaborates. “Our CFD capabilities, which we also employ when performing our lines optimisation, retrofit and trim assistant services, enable us to normalize vessel specific power demand under every reported condition with great accuracy.”
DNV GL offers the hull and propeller degradation computation as part of its all new fleet performance ECO Insight management service.