A generalised equivalent storm model for long-term statistics of ocean waves

This is the final version of the article. Available from Elsevier via the DOI in this record.To calculate the return periods of individual wave or crest heights, the long-term distribution of sea states must be combined with the short-term distribution of individual wave or crest heights conditional on sea state. This is normally achieved using an equivalent storm model to parameterise the distribution of the maximum wave or crest height in a storm. A new equivalent storm model is introduced that generalises the approach of Tromans and Vanderschuren (1995). The generalised equivalent storm (GES) method is significantly simpler than equivalent storm methods that model the temporal evolution of the significant wave height in a storm. The GES method is applied to long time series of wave buoy measurements for deep and shallow water sites and demonstrated to be more accurate than existing methods at representing the statistical characteristics of measured storms. Return periods of crest heights from the GES method are shown to be more robust to uncertainties in the fitted models of the equivalent storm parameters than estimates from temporal evolution methods such as the equivalent triangular storm and equivalent power storm model.This work was partly funded through EPSRC grant EP/R007519/1

Long-term distributions of individual wave and crest heights

This is the final version of the article. Available from Elsevier via the DOI in this record.This paper considers three types of method for calculating return periods of individual wave and crest heights. The methods considered differ in the assumptions made about serial correlation in wave conditions. The long-term distribution of individual waves is formed under the assumption that either (1) individual waves, (2) the maximum wave height in each sea state or (3) the maximum wave height in each storm are independent events. The three types of method are compared using long time series of synthesised storms, where the return periods of individual wave heights are known. The methods which neglect serial correlation in sea states are shown to produce a positive bias in predicted return values of wave heights. The size of the bias is dependent on the shape of the tail of the distribution of storm peak significant wave height, with longer-tailed distributions resulting in larger biases. It is shown that storm-based methods give accurate predictions of return periods of individual wave heights. In particular, a Monte Carlo storm-based method is recommend for calculating return periods of individual wave and crest heights. Of all the models considered, the Monte Carlo method requires the fewest assumptions about the data, the fewest subjective judgements from the user and is simplest to implement.This work was partly funded through EPSRC grant EP/R007519/1

Modeling time varying and multivariate environmental conditions for extreme load prediction on offshore structures in a reliability perspective

Ph.DDOCTOR OF PHILOSOPH