Research on Parameter Estimation of Concrete Creep Based on Gamma Model

Abstract

Concrete creep is usually used as a deterioration index to characterize the service performance of concrete structures under long-term loading. The primary aim of this investigation is to use Gamma stochastic process to simulate the uncertainty of concrete creep process. When the parameter c and scale parameter β were random variables and their prior distributions were known, the posterior distribution and estimation of parameter c and scale parameter β could be obtained by the Bayesian theorem. As a special case, the analytical expression, where the parameter c was a given value, the prior distribution of paramater β followed the posterior distribution of the Gamma distribution, and posterior estimation, was established. Finally, given parameters b and c, the model parameters of Gamma process was estimated by the classical moment estimation, maximum likelihood estimation, the Bayesian inference, posterior moment estimation and posterior maximum likelihood estimation in conjunction with two sets of concrete creep data. Then the stochastic process of concrete creep was simulated. Based on the minimum sum of square errors as a criterion, the results of above five methods were compared. The comparison results show that the Bayesian estimation, which is deemed the best method, and the posterior parameter estimation, are superior to the classical parameter estimation.