Effect of roughness on shear behavior of red clay – concrete interface in large-scale direct shear tests
Bibliographic record
Abstract
Few studies have focused on evaluating regular surface roughness and its effect on interfacial shear behavior of the red clay – concrete interface. This paper presents the results of a series of laboratory large-scale direct shear tests conducted using different types of red clay – concrete interfaces. The objective is to examine the effect of surface roughness on these types of soil–concrete interfaces. In the smooth-interface tests, the measured peak and residual shear strength values are very close to each other, with no observed shear dilation. The surface roughness is found to have a remarkable effect on the interfacial shear strength and shear behavior, with the shear strength increasing with increased surface roughness level. The shear dilation is likely to occur on rougher interfaces under lower confining pressure due to the behavior of compressed clay matrices. Owing to the clay matrix’s cohesion and friction, the interfacial shear strength on rough interfaces consists of cohesive and frictional forces between the clay and concrete surfaces. The friction angle value is observed to fluctuate between the clay’s friction angle and the smooth interface’s friction angle. This can be related to the position change of the shear failure slip plane. The confining pressure and surface roughness could change the shear failure plane’s position on the interface. Furthermore, the red clay – structure interface is usually known as the weakest part in the mechanical safety assessment.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".