Elastic–plastic–creep behavior of high rockfill dams: a case study on Lianghekou CRFD
Bibliographic record
Abstract
The instantaneous loading and time-dependent creep deformations occur simultaneously during the lifetime of rockfill dams, but their proportions in monitoring records are still unclear. In previous works, loading and creep were generally simulated independently in turn. This uncoupled method may induce misleading conclusions in interpreting dam behaviors. In this paper, an advanced elastic–plastic–creep model is applied to capture the interaction of loading and creep under complex conditions with varying loading rates based on a benchmark example of 295 m high Lianghekou core wall rockfill dam. The instantaneous elastic–plastic parameters of rockfills are calibrated by large-scale triaxial tests (including 300 and 800 mm in diameter) and the time-dependent creep parameters are obtained by back analyses on monitoring records. A series of numerical analyses on the dam are conducted. The loading-creep coupling process of rockfills is successfully captured and the instantaneous and time-dependent creep deformations are explicitly separated. The 800 mm diameter triaxial test weakens the size effect and provides an acceptable representation for the instantaneous behaviors of prototype rockfills. The good agreement between the calculations of the elastic–plastic–creep coupling analysis and measurements indicates creep contributes about 8%–15% to total construction deformation. The work provides guides for properly interpreting and evaluating actual dam behaviors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".