Prediction of Heavy Weather Seakeeping of a Destroyer Hull Form by Means of Time Domain Panel and CFD Codes

The focus of the present paper is the assessment of deterministic and stochastic methods for the prediction of large amplitude ship motions in heavy weather, including comparison with experimental fluid dynamics (EFD) data. The research was conducted under the auspices of NATO AVT-280 on "Evaluation of Prediction Methods for Ship Performance in Heavy Weather." EFD data are obtained from free-running model tests of a naval destroyer hull form. Namely, an appended 5415M model is assessed for course keeping in irregular stern-quartering waves at target Froude number equal to 0.33. Irregular waves are based on the JONSWAP spectrum. The static stability, forward speed, wave direction, and wave spectrum were set such that large amplitude roll motions were recorded, including a number of capsizes. Dynamic stability phenomena witnessed during the experiments include resonant roll, loss of static stability, and significant deck edge immersion. Deterministic validation is performed for a weakly non-linear as well as a body-exact time domain panel code. Results show fairly good predictions for roll, heave and pitch motions, and forward speed variations. Sway velocity, yaw motions, and deck edge immersion heights are seen to be more difficult to predict accurately. Next, stochastic validation and deterministic reconstruction of severe (large roll angles) and rare (capsizing) events are assessed by free-running CFD (URANS) simulations. Validation against EFD data includes roll decay at zero speed and self-propulsion revolution per minute studies in calm water. The stochastic validation of free-running CFD is achieved by statistical assessment of EFD data and CFD results by large-sample uncertainty quantification methods for input wave and ship response via spectrum, autocovariance, and bootstrap analysis. CFD results are in a very good agreement with EFD, showing satisfactory outcomes of the stochastic validation procedure. EFD and CFD data are used to identify wave sequences causing large roll angles. These are based on expected value and standard deviation of wave amplitude and encounter period. As proof of concept, this sequence is used for the deterministic reconstruction of severe (large roll angles) and rare (capsizing) events by CFD simulations.