Time-varying identification model for dam behavior considering structural reinforcement

Abstract

Mathematical relationship model between structural response and its influence factors is often used to identify and assess dam behavior. Under the action of loads, changing material property, structural reinforcement and so on, dam behavior expresses the uncertain variation characteristics. According to the prototypical observations, objective and subjective uncertain information on dam behavior before and after structural reinforcement, support vector regression (SVR) method is combined with Bayesian approach to build the time-varying identification model for dam behavior after structural reinforcement. Firstly, a static SVR model identifying dam behavior is established. Secondly, Bayesian approach is adopted to adjust dynamically the calculated results of static identification model. A method determining the Bayesian prior distribution and likelihood function is developed to describe the objective and subjective uncertainty on dam behavior. Emphasizing the importance of recent information on dam behavior, an algorithm updating in real time the Bayesian parameters is proposed to reflect the characteristic change of dam behavior after structural reinforcement. Lastly, the displacement behavior of one actual dam undergoing structural reinforcements is taken as an example. The identification capabilities of classical statistical model, static SVR model and time-varying model are compared. It is indicated that the proposed time-varying model can provide more accurate fitted and forecasted results, and is more suitable to be used to evaluate the reinforcement effect of dangerous dam.