Abstract
Displacement monitoring data modeling is important for evaluating the performance and health conditions of concrete dams. Conventional displacement monitoring models of concrete dams decompose the total displacement into the water pressure component, temperature component, and time-dependent component. And the crack-induced displacement is generally incorporated into the time-dependent component, thus weakening the interpretability of the model. In the practical engineering modeling, some significant explaining variables are selected while the others are eliminated by applying commonly used regression methods which occasionally show instability. This paper proposes a crack-considered elastic net monitoring model of concrete dam displacement to improve the interpretability and stability. In this model, the mathematical expression of the crack-induced displacement component is derived through the analysis of large surface crack’s effect on the concrete dam displacement to improve the interpretability of the model. Moreover, the elastic net method with better stability is used to solve the crack-considered displacement monitoring model. Sequentially, the proposed model is applied to analyze the radial displacement of a gravity arch dam. The results demonstrate that the proposed model contributes to more reasonable explaining variables’ selection and better coefficients’ estimation and also indicate better interpretability and higher predictive precision.
Highlights
Structural safety monitoring of concrete dams depends on visual observation and monitoring data analysis with the purpose of, as early as possible, identifying eventual anomalous behavior which could deteriorate the dam. e analysis results can help the dam administrative department take corresponding measures to eliminate the impact of abnormal behavior [1]
Displacement monitoring data have been widely acknowledged as a significant source for the performance and health condition assessments of concrete dams [2] because it directly reflects the structural behavior
Based on the assumption that the residual error sequence of multiple linear regression (MLR) models is uncorrelated and that multicollinearity does not exist among those explanatory variables, the optimal unbiased estimates of MLR model coefficients can be obtained using the least-squares method [7]
Summary
HST models have been used to analyze the monitoring data of Mathematical Problems in Engineering many dams, and various methods have been proposed to obtain the specific expressions and coefficients of practical models [8,9,10,11,12,13,14,15,16]. It is necessary to analyze a large surface crack’s effect on concrete dam displacement, and a crack-considered monitoring model is yet to be built to improve interpretability.
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