EFFICIENT SLOPE RELIABILITY UPDATING METHOD BASED ON MONTE CARLO SIMULATION

The traditional Monte Carlo simulation (MCS) could be prohibitively expensive in relatively low-probability slope reliability updating problems caused by the updating of the uncertainty of the uncertain parameters. This paper aims to propose an efficient slope reliability updating method based on MCS. The slope failure probability for the original probability distribution of input uncertain parameters is first calculated using the MCS and the corresponding failure samples are extracted. Then, the slope failure probabilities for any other probability distributions of input uncertain parameters are directly obtained based on the failure samples. Two slope examples are investigated to demonstrate the validity of the proposed method. The results show that the new efficient slope reliability updating method based on MCS proposed in this paper is simple and efficient in calculating the new updated slope failure probability, as it does not need to re-run the MCS. It not only can deal with the reliability problems with implicit performance functions, but also can solve the slope reliability problems involving single and multiple variables.