Hydromechanical analysis of flow behavior in concrete gravity dam foundations
Bibliographic record
Abstract
A key requirement in the evaluation of sliding stability of new and existing concrete gravity dams is the prediction of the distribution of pore pressure and shear strength in foundation joints and discontinuities. This paper presents a methodology for evaluating the hydromechanical behavior of concrete gravity dams founded on jointed rock. The methodology consisted of creating a database of observed dam behavior throughout typical cycles of reservoir filling and simulating this behavior with a distinct element method (DEM) numerical model. Once the model is validated, variations of key parameters including lithology, in situ stress, joint geometry, and joint characteristics can be incorporated in the analysis. A site-specific simulation of a typical reservoir cycle was carried out for Albigna Dam, Switzerland, founded on granitic rock, to assess the nature of the flow regime in the rock foundations and to evaluate the potential for sliding surfaces other than the damrock interface to develop. The factor of safety against sliding of various rock wedges of differing geometry present within the dam foundations was also evaluated using the DEM model and conventional analytical procedures. Estimates of crack propagation patterns and corresponding uplift pressures and factors of safety against sliding along the damrock interface obtained with the DEM were also compared with those from simplified procedures currently used in engineering practice. It was found that in a jointed rock, foundation uplift estimates after crack development obtained from present design guidelines can be too conservative and result in factors of safety that are too low and do not correspond to the observed behavior.Key words: hydromechanical, jointed rock, flow, dam design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".