Eulerian–Lagrangian CFD-microphysics modeling of a near-field contrail from a realistic turbofan
Why this work is in the frame
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Bibliographic record
Abstract
Aircraft contrails contribute to climate change through global radiative forcing. As part of the general effort aimed at developing reliable decision-making tools, this paper demonstrates the feasibility of implementing a Lagrangian ice microphysical module in a commercial CFD code to characterize the early development of near-field contrails. While engine jets are highly parameterized in most existing models in a way that neglects the nozzle exit-related aspects, our model accounts for the geometric complexity of modern turbofan exhausts. The modeling strategy is based on three-dimensional URANS simulations of an aircraft nozzle exit involving a bypass and a core jet (Eulerian gas phase). Solid soot and ice particles (dispersed phase) are individually tracked using a Lagrangian approach. The implemented microphysical module accounts for the main process of water-vapor condensation on pre-activated soot particles known as heterogeneous condensation. The predictive capabilities of the proposed model are demonstrated through a comprehensive validation set based on the jet-flow dynamics and turbulence statistics in the case of compressible, turbulent coaxial jets. Simulations of contrail formation from a realistic nozzle-exit geometry of the CFM56-3 engine (short-cowl nozzle delivering a dual stream jet with a bypass rate of 5.3) were also carried out in typical cruise flight conditions ensuring contrail formation. The model provides reliable predictions in terms of the plume dilution and ice-particle properties as compared to available in-flight and numerical data. Such a model can then be used to characterize the impact of nozzle-exit parameters on the optical and microphysical properties of near-field contrails.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it