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Record W2181699934

What drives intermittent aeolian saltation at high-frequency?

2012· article· en· W2181699934 on OpenAlexaff
Chris H. Hugenholtz, Cheryl McKenna Neuman, B. Li, Thomas E. Barchyn, Steven Sanderson

Bibliographic record

VenueEGUGA · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAeolian processesMechanicsWind tunnelSediment transportGeologyWind speedAirflowMeteorologyEnvironmental sciencePhysicsGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

Most aeolian sediment transport models are predicated on the assumption that transport results from an equilibrium in the momentum transfer between the wind and grains in the airstream. However, it is difficult to confirm this longstanding conceptualization in the field because at certain scales transport is highly intermittent, spatially nonuniform (i.e. streamers) and difficult to predict based on wind alone, even when surface conditions are ideal. While it might be important to filter this variability (i.e. time-averaging) for predictive purposes, it is also important to evaluate discrepancies between measurements and models over a range of timescales and levels of transport. To address this, we measured saltation at high frequency under controlled conditions in a wind tunnel. The goal was to determine how the statistical properties of saltation change under different flow conditions, and whether the steady state approximation of the saltation system commonly used in models is an accurate characterization of the transport system at high-frequency. We performed a series of experiments by applying a constant airflow to a granular surface and recording the aeolian transport rate near the bed with a laser particle counter at 10 Hz. From experimental runs at different constant velocities we resolved differences in the statistics of transport that hint at the underlying controls. At low free-stream velocities saltation was highly intermittent. Long periods (> 1 min) without detectable saltation were interrupted by brief ‘pulses’ of saltation activity so that the gap between the typical transport rate and the mean was large, yielding right-skewed (pseudo power law) frequency-magnitude distributions. We interpret these conditions in the context of bed state since flow remained constant. Near threshold parts of the bed develop into a critical state such that the size of saltation pulses is unpredictable. This bears some resemblance to the concept of self-organized criticality. However, when free-stream velocity was much higher the statistical properties and character of the transport series changed, ultimately yielding continuous saltation and more symmetric frequency-magnitude distributions. This suggests that saltation activity near the threshold of motion is strongly imprinted by the bed state, but once saltation becomes continuous the flow velocity exerts more influence on transport rate. Greater emphasis on the bed state from a granular physics perspective may improve the understanding of saltation at high resolution.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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