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Record W4411236974 · doi:10.1029/2024jf008218

Quantification of Particle Velocities and Energy Regime in an Aeolian Abrasion Chamber

2025· article· en· W4411236974 on OpenAlexafffund
Joanna E. Bullard, Lucrecia Alvarez‐Barrantes, Cheryl McKenna Neuman, Patrick O’Brien

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsTrent University
FundersRES’EAU-WaterNETNatural Environment Research Council
KeywordsAeolian processesAbrasion (mechanical)Particle (ecology)GeologyMaterials scienceGeotechnical engineeringGeomorphologyComposite material

Abstract

fetched live from OpenAlex

Abstract Particle breakdown and fine sediment production by wind abrasion is of long‐standing interest in aeolian science as it contributes to erosion and dust production on Earth and other planetary bodies. The process of aeolian abrasion is largely measured in laboratories to enable standardization of parameters and allow simulation of saltation over long time periods. To be effective, abrasion simulators must reproduce particle interactions similar to those observed in the natural environment. This paper quantifies the particle velocities, pathways and energy regime within a widely used “test‐tube” abrasion chamber. For 17 different sand samples, the instantaneous two‐dimensional vertical and horizontal velocity components of particles moving within the chamber were sampled using a laser Doppler anemometer. Similar to a natural saltation cloud, the movement of particles in the chamber is stochastic and there is a positive relationship between the air inflow rate and the depth of the saltation layer. For air inflow of 14.9 m s −1 , particle velocities range from 0.01 to 3.2 m s −1 with median velocity for all particles in the chamber varying from 0.29 to 0.56 m s −1 , and total energy ranging from 0.54 to 1.38 J kg −1 . These values are similar to those determined for natural saltation clouds. For a constant air inflow rate, the mean total particle velocity increases with particle size. Air inflow rate has a significant effect on mean total particle velocity but between 10 and 100 g the quantity of sample tested is not important. The contribution of this type of experiment to understanding aeolian abrasion processes is evaluated.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.039
GPT teacher head0.324
Teacher spread0.285 · 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 designObservational
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

Citations1
Published2025
Admission routes2
Has abstractyes

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