DERIVATION OF PROBABILITY DISTRIBUTION PARAMETERS THROUGH L-MOMENTS

Abstract eng:
Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of their response to wave loading is a minimum requirement for efficient probabilistic analysis of these structures. Even if the structural system can be assumed to be linear, due to nonlinearity of the wave loading mechanism and also due to the intermittency of wave loading on members in the splash zone, the response is often non-Gaussian. The (conventional) method of moments is one of the methods which is frequently used to determine the parameters of the adopted probability model from a simulated or measured record of response. However, when higher order moments, such as the 4th moment, are required for derivation of distribution parameters, the parameter values estimated from this method show considerable scatter due to high sampling variability of the 4th moment. In order to avoid this problem, rather than calculating the 4th-order moment (kurtosis) directly from its definition (henceforth referred to as the conventional method of moment), two indirect methods (i.e., the low-order method of moments and the linear method of moments) have been used for estimating its value. As a way of demonstration, these alternative methods have been applied to simulated sample records from symmetric Pierson-Holmes distributions. The results show that in most cases the sampling variability of the estimated values of the kurtosis determined from the linear method of moment is smaller than corresponding values derived from the other two methods.

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