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Record W2047412693 · doi:10.2136/sssaj2000.6441226x

Elastic Wave Velocities in Partially Saturated Ottawa Sand

2000· article· en· W2047412693 on OpenAlexaboutno aff
Doru Velea, F. Douglas Shields, James M. Sabatier

Bibliographic record

VenueSoil Science Society of America Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringTension (geology)Grain sizeStiffnessMechanicsGeologySurface finishMaterials scienceStress (linguistics)Shear (geology)Dry sandComposite materialPhysicsCompression (physics)

Abstract

fetched live from OpenAlex

A theoretical model is needed to predict the macroscopic mechanical properties of soil from the size, shape, and elastic properties of its constituent particles. To test one such model, we compared measured and calculated values of compressional and shear wave velocities in Ottawa sand. The sand was packed in a cylindrical tank ≈0.9 m in diameter and 0.9 m deep. The velocities were measured in the horizontal direction as a function of depth as the zero tension level of the water in the sand was slowly raised. In the air‐dry sand the velocities varied nonuniformly with depth, reaching a maximum value about two‐thirds of the way to the bottom of the tank. When water was introduced into the bottom of the sand, the nonuniform depth dependence was removed. At higher saturations, the velocities gradually decreased until the zero tension level was at the top of the sand. The nonuniform depth dependence in the dry sand has been attributed to the tank wall supporting part of the gravitational stress in the material. A modified Digby (1981) model was found to adequately account for the results in the wet material. A lumped parameter combining the contacts per grain, size, and the grain roughness was used to fit the data. In terms of the model, it is concluded that the water in the contacts between the grains had little effect on the normal contact stiffness, but reduced the tangential contact stiffness to zero.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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 designSimulation or modeling
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

Citations44
Published2000
Admission routes1
Has abstractyes

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