Drift speed distribution of icebergs on the Grand Banks and influence on design loads

Stuckey, Paul David (2008) Drift speed distribution of icebergs on the Grand Banks and influence on design loads. Masters thesis, Memorial University of Newfoundland.

[English] PDF - Accepted Version Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Download (9MB)

Abstract

With increasing oil and gas exploration on the Grand Banks during the 1970's and 1980's, there was a need to better understand the risk of icebergs impacting an offshore structure, and the consequences should such an event occur. As a result of industry demand, a probabilistic iceberg design load methodology was developed to estimate the risk of impacts and the resultant impact forces. -- Since the original framework was developed, there have been numerous improvements and enhancements. Distributions and relationships used to define input parameters have been refined due to the availability of new data. Several models have been improved as a result of ongoing research. The author has been extensively involved in many of the updates and improvements to the methodology, including improvements in the eccentricity model, the area-penetration model, and most recently, the drift speed model. -- The iceberg drift speed model, a key component, was developed by balancing the environmental forces acting on the iceberg. The model was deterministic; there was only one iceberg drift speed for a given iceberg in a specific significant wave height. The model agreed with the overall drift speed distribution based on available data. However, with the availability of new data, it was shown the model did not fully capture the randomness observed in the data. -- A new probabilistic drift speed model was developed to replace the deterministic model. It is based on the statistical analysis of available drift speed data. This model addresses the randomness in the data by incorporating probability distributions. The input parameters for the distributions are defined in terms of the iceberg waterline length and the significant wave height.

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