Abstract
Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.
Highlights
In an investigative report on the state of dams, the International Committee on Large Dams points out that the majority of concrete dams in various countries have cracks, in which a total of 243 dams have collapsed due to these cracks [1]
Cracks are one of the hidden dangers in concrete dams, which are greatly dangerous to their safety
The Zillergrund arch dam in Austria, the Zeuzier arch dam in Switzerland, the Revelstoke solid gravity dam in Canada, the Sayano-Shushenskaya gravity arch dam in Russia, the Koyna gravity dam in India, the Pacoima arc dam in America, and the Sefid Rud buttress dam in Iran were seriously affected by cracks
Summary
In an investigative report on the state of dams, the International Committee on Large Dams points out that the majority of concrete dams in various countries have cracks, in which a total of 243 dams have collapsed due to these cracks [1]. By further studying the abnormal behaviors of cracks in concrete dams [5,6,7], it is found that, when such abnormal behavior is observed, mutation occurs to the crack’s aperture sequence In this model, hydraulic pressure, temperature, and timeliness components are the continuous functions of corresponding factors. Where H is the water depth, T is the temperature measurement value, θ is the time-related influence factor, ε is the random error term, and g(⋅) is the part without clear function relation between the crack aperture and the parameter, which is called the nonparametric part of the model. If zmin > 1, the residuals sequence is smooth and the semiparametric model is proved to be effective; we model and analyze the cracks data sequence using the semiparametric model
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