4.6 Article

A Fast Prediction Method for Stability Safety and Reliability of Reservoir Bank Rock Slopes Based on Deformation Monitoring Data

期刊

FRONTIERS IN EARTH SCIENCE
卷 10, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/feart.2022.944299

关键词

reservoir bank slope; deformation monitoring; reliability; slope warning; online judging

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The proposed method in this paper provides a fast prediction of the safety state of reservoir bank rock slope based on time-dependent deformation and rock creep, allowing for online forecasting of stability and reliability coefficients using deformation data. Verification on a left bank slope of the Dagangshan arch dam showed that the method met engineering requirements with errors within 5% for slope stability safety coefficient prediction and within 10% for reliability index prediction. This method offers a new way for rapid prediction of slope engineering safety.
The stability of reservoir bank slopes is critical to the engineering operation's safety. Due to the complexity of geological conditions, the monitoring mode based on deformation monitoring data cannot directly respond to the structural damage stability state, whereas anther mode based on structural calculation is time-consuming and lacks real-time capabilities. To that end, this paper proposes a method for fast prediction of the safety state of reservoir bank rock slope based on the physical significance of time-dependent deformation and rock creep at monitoring points, with the safety coefficient and reliability obtained by numerical calculation as the dependent variables and the slope deformation monitoring sequence as the independent variable, based on full verification of the rationality of numerical calculation. The model can be used to forecast the stability and reliability coefficients of reservoir bank slopes online using deformation data from the field. The application verification of the left bank slope of the Dagangshan arch dam reveals that the average and maximum error of slope stability safety coefficient prediction is within 5% for 90 and 180 days and the average and maximum error of reliability index prediction is within 10%, which meet the engineering requirements and can provide a new way for rapid prediction of slope engineering safety.

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