Grouting of cracks in concrete dams: numerical modelling and structural behaviour
Bibliographic record
Abstract
Abstract Grouting is often considered to reinstate water tightness and displacement continuity in cracked concrete dams. Grouting alters the state of stress, deformation, and the strength of a dam in many ways. The state of stress prior to grouting is altered by the injection pressure that often increases the crack opening. This new state of stress will be ‘locked‐in’ as the grout sets. Excessive injection pressure may also induce hydro‐fracturing. Obviously, composite action of structurally repaired cracks will be fully effective only for incremental load applications occurring after the completion of the grouting programme. The state‐of‐practice concerning structural response of cracked dams during and after grout injection is reviewed in this paper. The existing methods for structural analysis of dam rehabilitation by crack grouting, and the required modifications for modelling the hardened grout in the repaired dam are discussed. State‐of‐the‐art techniques using contact elements are defined (i) to model the hardened grout in cracks of repaired dam; and (ii) to investigate the structural response of the rehabilitated dam to subsequent loading conditions. A 90 m high‐gravity dam is considered in comparative analyses for numerical simulations of the incidence of grouting on the structural responses of cracked dams.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".