Offshore steel trestles (OSTs) are exposed to severe marine environments with stochastic wave and current loads, making structural safety assessment challenging and difficult. Reliability analysis is a suitable way to consider both wave and current loading intensity uncertainties, but the implicit and complex limit state functions of the reliability analysis usually imply huge computational costs. This paper proposes an efficient reliability analysis framework for OST using the kriging model of optimal linear unbiased estimation. The surrogate model is built with stochastic waves, current parameters, and the corresponding load factors. The framework is then used to evaluate the reliability of an example OST subjected to wave and current loads at three limit states of OST, including first yield (FY), full plastic (FP), and collapse initiation (CI). Three different distributions are used for comparison of the results of failure probability and reliability index. The results and the computational cost by the proposed framework are compared with that from the Monte Carlo sampling (MCS) and Latin hypercube sampling (LHS) method. The influences of sample number on the prediction accuracy and reliability index are investigated. The influence of marine growth on the reliability analysis of the OST is discussed using MCS and the kriging model. The results show that the reliability analysis based on the kriging model can obtain the reliability index for the OST efficiently with less calculation time but similar results compared with MCS and LHS. With the increase of the number of samples, the prediction accuracy of the kriging model increases, and the corresponding failure probability fluctuates greatly at first and then tends to be stable. The reliability of the example OST is reduced with the increase of marine growth, regardless of the limit state.

Typhoon is a disastrous weather system, which usually induces strong waves, currents, and surges along the coastal area, and causes severe hydrodynamic loads on the elevated pile cap foundation, which is widely used to support the sea-crossing bridge. Estimating the hydrodynamic loads under typhoons is essential to ensure the bridge's safety. This paper develops an environmental contour-based framework that can estimate the extreme hydrodynamic loads induced by typhoons while considering the correlation among environmental conditions. The elevated pile cap foundation of the Xihoumen Rail-cum-road Bridge was used to illustrate the framework. The SWAN+ADCIRC model was employed to simulate the environmental conditions under typhoons. The pair-copulas were adopted to construct joint probability distributions, and the environmental contours with a given return period were then established by the inverse first-order reliability method. Given the hydrodynamic model and short-term peak value of structural response, the AK-LHS method was then used to find the maximum hydrodynamic loads based on the environmental contours. The environmental contour constructing methods, and selection methods of short-term peak values were compared and discussed. The main findings include: 1) ignoring correlations of the environmental conditions overestimates the extreme hydrodynamic loads and results in a conservative design; 2) the estimation of extreme hydrodynamic loads is affected by the selection and fitting of short-term peak values significantly; and 3) the extreme hydrodynamic loads estimated by either Rosenblatt or Nataf transformation shows similar results.

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