Abstract
The present paper examines a semi-empirical framework for the estimation
of added resistance in arbitrary wave heading under consideration of
uncertainty quantification. In this respect, the calibration of the
formula’s parameter vector is conducted based on particle swarm
optimization as well as a database of model test results comprising 25
different ships and around 1100 samples. In the first iteration, the
minimization of reducible systematic uncertainty is of interest and the
effect of four objective functions on prediction accuracy is evaluated.
Moreover, two different parameter combinations were obtained for blunt (CB≥0.70)
and slender-type ships. Conversely, the irreducible statistical
uncertainty, i.e. the inherent noise of the experimental data, is taken
into account by a quantile regression procedure. Applying this approach,
a 90% prediction interval for the formula’s estimates is implemented
using the skewed version of the superior loss function in the previous
iteration. The practical relevance of an uncertainty estimate for the
prediction of the added resistance is emphasized in the final part, in
which the proposed approach is validated in regular waves against model
test data and other well-established prediction methods. In general, the
validation studies suggest satisfactory performance and reliability of
the adapted semi-empirical formulation.
| Original language | English |
|---|---|
| Article number | 111040 |
| Journal | Ocean Engineering |
| Volume | 251 |
| Number of pages | 15 |
| ISSN | 0029-8018 |
| DOIs | |
| Publication status | Published - 2022 |
Keywords
- added resistance
- Semi-empirical formula
- Uncertainty quantification
- Parameter calibration
- Swarm intelligence algorithm
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