Efficient estimation of extreme response of drag-dominated offshore structures by Monte Carlo simulation

Estimation of Extreme Values by the Average Conditional Exceedance Rate Method

“…An underlying premise for the development in this paper is that a rational approach to the study of the extreme values of the sampled time series is to consider exceedances of the individual random variables above given thresholds, as in classical extreme value theory. The alternative approach of considering the exceedances by upcrossing of given thresholds by a continuous stochastic process has been developed in [7,8] along lines similar to that adopted here. The approach taken in the present paper seems to be the appropriate way to deal with the recorded data time series of, for example, the hourly or daily largest wind speeds observed at a given location.…”

“…The viability of this approach has been successfully demonstrated by the authors for mean up-crossing rate estimation for extreme value statistics of the response processes related to a wide range of different dynamical systems, compared with [7,8].…”

Derivation of the Probability Distribution of Extreme Values of Offshore Structural Response by Efficient Time Simulation Method

“…1). In this study, the following definition of the P-M frequency spectrum [11] has been used: (1) where f is the wave frequency in Hz, is the surface elevation frequency spectrum, H s is the significant waveheight in meters and T z is the mean zero-upcrossing period in seconds.…”

“…Thus, the capability to predict the long-term probability distribution of the response extreme values is of great value to designers. The major obstacle in establishing the probabilistic properties of response is due to the nonlinearity of the wave load mechanism and/or the structural system which leads to non-Gaussian distribution for response [1][2][3][4][5][6][7]. The problem is further compounded by current and by intermittent loading on members in the splash zone, which have a significant effect on the statistical properties of extreme responses [8,9].…”

“…By considering an exponential model for the mean upcrossing rate of high response values, Naess et al [1] have succeeded in reducing the required number of simulated response records without sacrificing the accuracy of the predicted probability distribution of response extreme values. Another efficient version of the time simulation (ETS) technique has recently been introduced which takes advantage of the correlation between surface elevation and their corresponding response extreme values [10].…”