Prediction of Frictional Jacking Forces Using Bayesian Inference

Application of pipe-jacking method in the form of microtunneling has become more popular over the conventional open cut method for the installation of underground infrastructure such as buried sewer pipelines in urban setting in recent years. This is due to the advantages offered by trenchless technology such as reduced disruptions to traffic and the surrounding environment as well as minimized ground settlements. Prediction of frictional jacking forces is a crucial component of the design of pipe-jacking works. In view of the challenges faced in calculating pipe-jacking forces in highly weathered and highly fractured geological formations, this paper proposes the use of Bayesian inference method to predict the frictional jacking forces developed from traversing the weathered rock formations. A probabilistic framework based on Bayesian approach is proposed using a well-established pipe-jacking force model, which considers arching effect from the surrounding ground. The main advantages of Bayesian inference include (i) consideration of uncertainty in deriving the soil parameters and (ii) ability to incorporate prior information and expert judgement from previous research studies into the model in the form of prior distribution. The model uncertainty is expected to be significantly reduced through the sequential updating process when more data become available.