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Record W4409855774 · doi:10.4043/35990-ms

Effects of Particle Morphology on the Interface Friction Angle of Sands

2025· article· en· W4409855774 on OpenAlexaboutno aff
Ali Seiphoori, Thi Lim Duong, Mahmoud A. Salehi

Bibliographic record

VenueOffshore Technology Conference · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsMorphology (biology)Particle (ecology)Interface (matter)Materials scienceMechanicsComposite materialGeologyPhysicsContact angle

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.216
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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