Statistical Investigation of Bearing Capacity of Pile Foundation Based on Bayesian Reliability Theory

Abstract

In order to improve the estimation accuracy of bearing capacity of pile foundation, a newforecast method of bearing capacity of pile foundation was proposed on Jeffrey’s noninformative prior using the MCMC (Markov chain Monte Carlo) method of the Bayesian theory.The proposed approach was used toe stimate the parameters of Normaldistribution.Numerical simulation was used to produce pseudo samples.The parametere stimation of the maximum like lihood method and the Bayesianstatisti caltheory was used to estimate the parametere stimation of the Normaldistribution,which has been compared with the theoretical value of the pseudo sample of Normal distribution.There sult indicates that the forecast model of Normal distribution using the Bayesian methodis better than that of the maximum like lihood method,and the performance of the proposed method was improvedwith increasing of pseudosample number. At last, the proposed method was applied to estimate the parameter of Normal bearing capacity distribution of pile foundation, which shows that the proposed method has a high precision and good applicability.