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Record W2108261089 · doi:10.1175/jas-d-12-0221.1

Numerical Simulations of Waves over Large Crater Topography in the Atmosphere

2012· article· en· W2108261089 on OpenAlexaff
Nancy Soontiens, Marek Stastna, Michael L. Waite

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsImpact craterGeologyHydraulic jumpAtmosphere (unit)Stratification (seeds)GeophysicsAtmospheric sciencesMechanicsMeteorologyFlow (mathematics)AstrobiologyPhysics

Abstract

fetched live from OpenAlex

Abstract Numerical simulations are used to investigate waves generated by flow over crater topography of diameter 100 km in an idealized atmosphere. The atmosphere is stratified with a constant buoyancy frequency profile and the background wind is constant. This study describes the development of a low-level jet along the upstream crater slope and its interaction with the cooler air within the crater valley. This interaction results in a hydraulic jump–like structure that acts as a modified topography, forcing a beam of secondary waves. The hydraulic jump is formed by a retreating gravity current as the cool air within the crater readjusts after the initial tilting of potential temperature contours. A two-dimensional simulation is used to compare features such as wave overturning in two and three dimensions. Several variations on the atmosphere’s profile are considered, including an atmosphere with reduced constant stratification and an atmosphere that is unstratified within the crater. These results indicate that the stratification within the crater is an important component in the development of the hydraulic jump. Also, several topographic modifications are included, such as a crater with no rims and a crater with reduced diameter. These comparisons reveal that the crater rims have little impact on the general wave pattern and that the crater curvature can influence wave breaking and lateral deflections. In addition, cases with rotation break the symmetry and induce more overturning in one-half of the crater.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2012
Admission routes1
Has abstractyes

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