Effect of environmental factors on modal identification of a hydroelectric dam’s hollow-gravity concrete block

Dams are a type of civil infrastructure that can directly impact people’s well-being, as their function is energy production, flood control, or water supply. Therefore, it is worth generating strategies to assess its current condition, since structural changes may occur during its useful life. One h...

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Veröffentlicht in:Journal of civil structural health monitoring 2024-08
Hauptverfasser: Ardila-Ardila, Yeny V., Gómez-Araújo, Iván D., Villalba-Morales, Jesús D., Aracayo, Luis A.
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Sprache:eng
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Zusammenfassung:Dams are a type of civil infrastructure that can directly impact people’s well-being, as their function is energy production, flood control, or water supply. Therefore, it is worth generating strategies to assess its current condition, since structural changes may occur during its useful life. One highly effective approach for evaluating the structural integrity of dams involves monitoring alterations in modal parameters. This method enables the identification of abnormal changes that may arise from structural degradation. Numerous studies have revealed the strong influence of environmental factors on modal parameters, resulting in variations unrelated to structural damage. This paper investigates the effects of environmental factors such as upstream water level and air temperature on the temporal evolution of the identified modal parameters of a hydroelectric dam’s hollow-gravity concrete block. Modal identification is performed through an automatic procedure of estimating modal parameters to 30-min acceleration time series over 3 years of operation. Correlation analysis reveals a distinct relationship between the identified modal parameters and environmental factors. Changes in air temperature exhibit a direct proportional impact on natural frequencies, while fluctuations of the upstream level have an inverse effect. Furthermore, a time lag was observed in the natural frequencies concerning air temperature. Multiple linear regressions were fitted to mitigate the induced effects, incorporating as predictors the upstream water level and the averages of air temperature segments measured prior to the predicted frequency. A reduction in variability of more than 50% was achieved in an out-of-sample 8-month period for the modes linked to the natural frequencies most influenced by environmental factors.
ISSN:2190-5452
2190-5479
DOI:10.1007/s13349-024-00828-3