Seepage and Slope Stability Analysis of Earthen Dam: A Case Study of Koga Dam, Ethiopia
Bibliographic record
Abstract
Evaluations of an earth-fill dam throughout its service life must ensure the stability of it against seepage and slope failure. This study presents the seepage and slope stability of the Koga earth-fill dam. The analyses were carried out using a finite element based PLAXIS 2D software, and covers the whole dam body, including 20 m of foundation depth. The behavior of both, the body and the foundation of the dam were described using the Mohr-Coulomb criterion. Assessments of safety factor and quantity of seepage through the main body of the dam and foundation were carried out at different critical loading conditions. In this study, seepage analysis was undertaken of flow rate, pore water distribution and location of phreatic line. Additional actual field data measurements and observatory investigation were also carried out. From the simulated results, the average flow rate of seepage for the entire length of the body of the dam at normal pool level was equal to 0.06085 m3/s, whereas the figure for that through the foundation of the dam was 0.01937 m3/s. Moreover, total seepage through the main body of the dam at the current reservoir level was 0.04982 m3/s, while the actually measured quantity of seepage accumulated at the downstream toe of the dam was 0.04644 m3/s. The simulated and measured seepage discharges are 93.2% similar. Based on the result of this study, the resulting factor of safety values during end of construction, steady state condition and rapid drawdown condition were 1.6221, 1.6136, and 1.2199, respectively. Using recommended design standards: United States army corps of engineers (USACE), British dam society (BDS), and Canadian dam association (CDA), the slope stability analysis of the Koga earth dam at all critical loading conditions are safe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".