MétaCan
Menu
Back to cohort
Record W2913561434 · doi:10.1115/1.4042817

Trajectory of a Liquid Jet in a High Temperature and Pressure Gaseous Cross Flow

2019· article· en· W2913561434 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMechanicsJet (fluid)Weber numberMomentum (technical analysis)InertiaAerodynamicsTrajectoryAtmospheric pressureShadowgraphyFlow (mathematics)ThermodynamicsPhysicsMeteorologyClassical mechanicsTurbulenceOpticsLaserReynolds number

Abstract

fetched live from OpenAlex

An experimental study of liquid jet injection into subsonic air crossflow is presented. The aim of this study was to relate the jet trajectory to flow parameters, including jet and air velocities, pressure and temperature, as well as a set of nondimensional variables. For this purpose, an experimental setup was developed, which could withstand high temperatures and pressures. Images were captured using a laser-based shadowgraphy system. A total of 209 different conditions were tested and over 72,000 images were captured and processed. The crossflow air temperatures were 25 °C, 200 °C, and 300 °C; absolute crossflow air pressures were 2.1, 3.8, and 5.2 bars, and various liquid and gas velocities were tested for each given temperature and pressure. The results indicate that the trajectory and atomization change when the air and jet velocities are changed while keeping the momentum flux ratio constant. Therefore, it is beneficial to describe the trajectory based on air and jet Weber numbers or momentum flux ratio in combination with one of the Weber numbers. Also, examples are given where both Weber numbers are kept constant but the atomization is changed, and therefore, other terms beyond inertia terms are required to describe the spray behavior. It is also shown that the gas viscosity has to be considered when developing correlations. The correlations that include this term are generally better in predicting the trajectory. Therefore, Ohnesorge numbers in combination with the Weber numbers is used in the present correlations to describe the trajectories.

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.

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 score0.161
Threshold uncertainty score0.471

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 head0.002
GPT teacher head0.185
Teacher spread0.183 · 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