Uncertainty based model averaging for prediction of long-time prestress losses in concrete structures

Abstract

Prestressed concrete structures are widely used in long span bridge girders and nuclear power plants. Long-time creep and shrinkage in concrete cause loss of prestress forces in the concrete structures. The creep and shrinkage models existing in the literature are empirical in nature. Each model has been developed on the basis of an arbitrary selection of data sets among all the data sets available. In this study it is claimed that each model contains some information about the creep and shrinkage patterns in the concrete structures. A single best model is developed in this study using all existing models, based on the concept of model averaging. In model averaging all the models are updated independently based on the short-time measurements. Weights are assigned to each model based on the likeliness of predictions from that model to the actual measurements. The time period for short-time measurements is evaluated using stochastic simulations. The proposed single best model for creep and shrinkage, and the time period for short-time measurements are (i) first validated against experiments reported in the Northwestern University (NU) database, and (ii) then used to predict the long-time losses of prestress forces in the concrete beams and slabs cast in the laboratory.