A fast Monte-Carlo method to predict failure probability of offshore wind turbine caused by stochastic variations in soil

Abstract

As spatial seabed soil variations are stochastic and considerable, it is important to predict the changes in the dynamic behavior of offshore structures for safety. Particularly, if the natural frequency of a structure is significantly changed by the soil variations, resonance can cause structural failure; hereafter, this probability is referred to as failure probability. Although several models have been proposed, they require a long computational time to predict failure probabilities. To overcome this limitation, this work proposes a fast method for estimating the failure probability. First, since a very large computation memory is required to construct a finite element model for stochastic soil, block-wise matrix calculations and a dynamic memory allocation technique were adopted. Second, conventional models require a large number of soil samples to calculate the failure probability, which results in heavy computations. A newly developed fast Monte-Carlo (FMC) method is 5.8 times faster than the conventional method with high accuracy (99.41%). This method was applied to offshore wind turbines and successfully predicted various structural characteristics. A noteworthy prediction is that slender and long foundation is more robust to stochastic soil variations than thick and short foundation. The FMC method can be used for preliminary design of offshore structures. © 2021 Elsevier Ltd