Due to errors in handling slurry

concrete

casings

reinforcement cages and other factors

minor or major defects in piles can be introduced during or after pile construction. Therefore this paper aims to propose a procedure to estimate the statistics of multiple defects in bored piles using the Bayesian theory. A Poisson process is adopted to model the occurrence of multiple defects in bored piles. Moreover the formulae of updated mean rate of occurrence are derived with a consideration of detection uncertainties for coring examination. A modified Bayesian sampling method is presented to update the distribution of mean defect size. Then

a method to evaluate the detection probability of coring examination is formulated. Results from numerical example indicate that the detection probability has a significant influence on the Bayesian estimator of mean rate of occurrence. The mean rate of occurrence will be highly underestimated without consideration of detection uncertainties. The updated mean of mean rate of occurrence increases with increasing values of the number of detected defects

while the updated coefficient of variation of mean rate of occurrence decreases. In addition

the uncertainties in mean rate of occurrence and mean defect size can be reduced substantially through the use of prior information