Effects of Particle Morphology on the Interface Friction Angle of Sands
Bibliographic record
Abstract
Abstract The particle shape of coarse-grained soils, such as sand, influences its geotechnical properties, including the interface friction angle (δres)–a crucial parameter for characterizing soil-pile and soil-pipe interactions in offshore geotechnics. This paper presents an experimental investigation of the effects of particle morphology on sand interface friction angle using a Bromhead ring shear device. We tested three sands –fine silica sand, Hokksund sand, and Ottawa sand—against a smooth steel interface, medium rough sandpaper, and rough sandpaper under normal stresses ranging from 10–50 kPa, corresponding to an equivalent depth of approximately 5–8 meters in typical offshore soils. We determined the shape factors characterized by sphericity and roundness based on image analysis and mathematical computation. Synthesized glass beads with a monodisperse size distribution were also tested as an idealized model system for comparison. Results indicate that particle shape plays a more dominant role than particle size in controlling the interface friction angle. Sands with greater angularity (Hokksund and silica sands) exhibited higher friction angles, whereas rounded Ottawa sand behaved more similarly to spherical glass beads, particularly on rough interfaces. Results revealed a potential competition between particle shape and surface roughness, controlling the dominant frictional mode. These findings offer new insights into the morphologically-driven mechanisms influencing interface friction, providing valuable input for geotechnical design, modeling, and foundation analysis in offshore environments.
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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 | 0.000 |
| 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".