Reliability assessment on prediction of pile bearing capacity

Abstract

There are many prediction methods that can be used to determine the bearing capacity of pipe pile. However, most of these methods are highly sensitive to specific in situ conditions and hence usually result in significant error. Therefore, it is important to evaluate the reliability of different pile bearing capacity prediction methods. Based on reliability theory, a computer code is developed in this paper to calculate reliability. Random variable statistic properties and corresponding reliabilities for different prediction methods are investigated and analysed. Results show that the reliability index for logarithmic normal distribution is higher than normal distribution. Analysis results demonstrate that the checking point method (JC method) method has a slightly lower efficiency than the Monte-Carlo importance sampling method and the Monte-Carlo direct sampling method. The Monte-Carlo importance sampling method has a higher efficiency than the Monte-Carlo direct sampling method. The Monte-Carlo importance sampling method can be used in major engineering projects. It is concluded that the clustering centre method has higher reliability in predicting pile bearing capacity than the Eslami and Fellenius method, Almeida method and Powell method.