Abstract
Due to their large cargo carrying capacities, ships are an environmentally and economically efficient mode for transporting cargo. During winters, the ships must navigate in ice-prone waters and hence shipping in ice-covered waters is an important engineering topic. To protect human lives and the environment during the shipping operations, we must understand the forces the ship hull sustains during the shipping operations. However, because of many uncertainties in the ice microstructure, and the ice breaking process, the forces required for breaking the ice cannot be resolved deterministically, but rather statistically. This work analyzed full-scale ice load data and the measured covariate conditions at the instant the load occurred to examine how the load distribution changes in different conditions.
The work used Bayesian hierarchical models with Gaussian process priors to infer how the load probability distribution parameters and their uncertainties change as a function of condition covariates. The ice thickness was modeled using a Gaussian process model with a Student-t error model, whereas the ship speed was interpolated linearly. Different ice load models were compared via their posterior predictions, and the Weibull model was found to have the best posterior predictions. According to the trained models, the ice load levels were changing with conditions, increasing in thicker ice, whereas the speed effect was more convoluted across models.
In addition to analyzing the loads from one bow frame, the research was able to identify local temporal maxima of loads by analyzing force measurements from three adjacent frames in the bow shoulder area. After identifying the peak loads from the data, the stereo camera photos were analyzed at the peak load occurrence times to study how the ice response affected the peak load distribution. The work investigated further the cases where the peak load was caused by a rotating ice cusp, studying how the cusp area was affected by the ice thickness and ship speed, and how the peak load was affected by the cusp's size and ship speed. The cusp area increased in slower speeds and thicker ice, whereas the peak loads increased with slower speeds and larger cusps.
Translated title of the contribution | Laivan runkoon kohdistuvan jääkuormajakauman ennustaminen eri jää- ja operointiolosuhteissa |
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Original language | English |
Qualification | Doctor's degree |
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Print ISBNs | 978-952-64-1797-4 |
Electronic ISBNs | 978-952-64-1798-1 |
Publication status | Published - 2024 |
MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- full-scale
- ice load
- ice conditions
- Bayesian hierarchical model
- Gaussian process