The seepage safety and sliding stability of a clay-core rockfill dam in Africa were examined through a combination of in-situ testing and numerical simulations under various working conditions. The findings indicate that, compared to conventional geological surveys and laboratory test data, in-situ parameters obtained from field direct shear and permeability tests provide greater accuracy and reliability. A numerical model based on the in-situ permeability coefficient was established, demonstrating its capability to reflect the seepage behavior of the dam and confirming that no seepage failure occurs under steady-state conditions. The calculated safety factors for sliding stability meet regulatory requirements across all conditions, and the introduction of a safety coefficient, S, allows for the quantification of the dam’s sliding stability margin. This study provides an analytical framework that integrates in-situ testing with multi-source data fusion, offering valuable insights for the safety assessment of similar projects.

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Seepage and Anti-Sliding Stability Analysis of a Clay Core Rockfill Dam Based on In-Situ Data

  • Siyuan Xu,
  • Fengzhe Tian,
  • Yanbin Cui,
  • Xiaojia Wang

摘要

The seepage safety and sliding stability of a clay-core rockfill dam in Africa were examined through a combination of in-situ testing and numerical simulations under various working conditions. The findings indicate that, compared to conventional geological surveys and laboratory test data, in-situ parameters obtained from field direct shear and permeability tests provide greater accuracy and reliability. A numerical model based on the in-situ permeability coefficient was established, demonstrating its capability to reflect the seepage behavior of the dam and confirming that no seepage failure occurs under steady-state conditions. The calculated safety factors for sliding stability meet regulatory requirements across all conditions, and the introduction of a safety coefficient, S, allows for the quantification of the dam’s sliding stability margin. This study provides an analytical framework that integrates in-situ testing with multi-source data fusion, offering valuable insights for the safety assessment of similar projects.