A method for characterizing and analyzing the structural behavior of concrete dams in cold regions
Xiao Fu, Maomei Wang, Gang Zhao, Yi Xu, Yitong Qi, Chongshi Gu
TL;DR
This paper introduces a new method to analyze how concrete dams behave in cold regions by using advanced data analysis techniques.
Contribution
The novel approach combines variational mode decomposition and a deep learning algorithm to better understand dam behavior in cold climates.
Findings
The method effectively extracts useful information from dam monitoring data.
It accounts for cold-related factors like freeze-thaw cycles in structural behavior analysis.
The model helps identify potential risks and improve dam safety in cold regions.
Abstract
Aiming at the gross error and data missing in the monitoring sequence of concrete dam, the variational mode decomposition method and the gated recurrent unit depth learning algorithm are respectively used to extract the effective information of the monitoring sequence. On the basis of the research on the characteristics of the traditional concrete dam structural behavior characterization model, the paper explores the expression mode of the effect of cold wave, freeze-thaw, wintering layer and other influencing factors. In order to reflect the correlation between the monitoring measurement values, the space coordinate variable is introduced to establish the monitoring measurement change characterization model, so as to realize the characterization and analysis of the structural behavior changes of concrete dams in cold regions and the quantitative analysis of various influencing factors.…
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Taxonomy
TopicsDam Engineering and Safety · Hydrological Forecasting Using AI · Concrete Properties and Behavior