Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

Estimatin of roughness lengths with a ship-mounted ADCP from Knudedyb, Denmark in October 2009

The hydraulic effect of asymmetric compound bedforms on tidal currents was assessed from field measurements of flow velocity in the Knudedyb tidal inlet, Denmark. Large asymmetric bedforms with smaller superimposed ones are a common feature of sandy shallow water environments and are known to act as hydraulic roughness elements in dependence with flow direction. The presence of a flow separation zone on the bedform lee was estimated through analysis of the measured velocity directions and the calculation of the flow separation line. The Law of the Wall was used to calculate roughness lengths and shear velocities from log-linear segments sought on transect-averaged and single-location velocity profiles. During the ebb tide a permanent flow separation zone was established over the steep (10-20°) lee sides of the ebb-oriented primary bedforms, which generated a consequent drag on the flow. During the flood, no flow separation was induced by the gentle (2°) lee side of the primary bedforms except over the steepest (10°) part of the lee side where a small separation zone was sometimes observed. As a result, hydraulic roughness was only due to the superimposed bedforms. The parameterized flow separation line was found to underestimate the length of the flow separation zone of the primary bedforms. A better estimation of the presence and shape of the flow separation zone over complex bedforms in a tidal environment still needs to be determined; in particular the relationship between flow separation zone and bedform geometry (asymmetry, relative height or slope of the lee side) is unclear. This would improve the prediction of complex bedform roughness in tidal flows.