Abstract: The moment estimations, such as mean and variance of samples, are quite uncertain in the context of limited geotechnical parameters, which may lead to a large bias in reliability analysis. The same small sample X may come from different populations W*, and the biases between the population mean and variance and the corresponding moment satisfy the law of t and χ2 distribution under assumption of normal distribution. Based on conditional probability principle, virtual population space ?POP and corresponding occurrence probability space ?OCC composed of W* are constructed. The Monte-Carlo simulation methods is used to obtain the failure probability space ?FAI for a simple soil slope. Underlying the full probability formula, a momentary weighting method, denoted by MWM, is proposed to calculate reliability index ?T. The numerical examples show that MWM could effectively narrow the ?T range, and simultaneously reduce the uncertainty caused by parameter estimation error. The mean value of ?T converges to the true value, showing good validity and unbiasedness. Aiming at the characteristics of single batch sampling in actual investigation work, MWM can reduce the distortion degree of reliability analysis in large occasional moment estimation bias cases.

Key words: small sample geotechnical parameters, moment estimation bias, momentary weighting method, soil slope, reliability analysis