A Bayesian approach to model selection and averaging of hydrostatic-season-temperature-time model

This paper presents a probabilistic approach to model the static dam responses, and monitor its performance using structural health monitoring (SHM) data. In general, the main factors that affects the dam responses are hydrostatic pressure, temperature changes, seasonal variation, and age-related deterioration. In this paper, using these variables two models (i.e., Model-1 and Model-2) have been developed to model, predict and monitor the dam …