A time-varying non-probabilistic reliability analysis method using surrogate model for the reinforcement effectiveness of damaged concrete gravity dam

Abstract

Evaluation of the effectiveness of reinforcement measures for the diseased concrete gravity dam is a critical issue in the field of hydraulic structural health control. The traditional probabilistic reliability analysis method is constrained by factors such as the randomness of the uncertain parameters, the high nonlinearity of the performance function, etc., when it is applied to the evaluation of the effectiveness evolution of reinforcement measures for the diseased concrete gravity dam. Therefore, a time-varying non-probabilistic reliability (NR) analysis method is proposed in the research. To characterize the uncertainty of the parameters, we adopt the form of interval numbers to present parameters and construct the interval parameter-based reliability analysis framework. Specifically, combining interval mathematics and non-probabilistic reliability theory, the NR calculation model for the gravity dam is proposed. In addition, considering of the aging of the structure, the time-varying NR (TV-NR) calculation model utilized to evaluate the long-term reinforcement effectiveness is established. To tackle the issue of expensive computation existed in the TV-NR model, response surface method (RSM) is coupled in the TV-NR calculation model to replace the original high nonlinearity performance function. Ultimately, the proposed method is verified in engineering examples that it can detect the most possible initial locations and failure processes of the gravity dam varying with time and can efficiently and accurately evaluate the reinforcement effectiveness of the gravity dams. The results indicate that the use of reinforcement measures can provide an improvement for the safety service of gravity dams.