Numerical analysis of concrete-faced rockfill dams considering effect of face slab – cushion layer interaction
Bibliographic record
Abstract
In this study, the effect of concrete face slab – cushion layer interface behavior on the performance of face slabs in concrete-faced rockfill dams (CFRDs) is investigated using the finite element method. The body of the CFRD is simulated by the cap elastoplasticity model while the interface zone between the concrete face slab and the gravelly cushion layer is simulated explicitly by an advanced interface constitutive model, developed in the framework of critical state soil mechanics and state parameters, and capable of simulating volumetric behavior and stress path dependency. The effect of elastic and elastoplastic material behavior and water level on the stress and displacement responses of the concrete face slab is examined, and the influence of the roughness at the interface area between the concrete face slab at the contact face and the cushion layer on the performance of the concrete face slab is investigated. Comparison of the results with and without the explicit consideration of the interface behavior shows the importance of incorporating advanced constitutive interface modeling in the design and analysis of CFRDs.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".