Numerical investigation of installation effects on condensation trail evolution during the vortex phase.
Bibliographic record
Abstract
Condensation trails (contrails) contribute significantly to the non-CO₂ climate impacts of aviation, with their effect estimated to be up to twice that of CO₂ emissions (Lee et al., 2021). Under specific atmospheric conditions, contrails can persist for several hours, potentially spanning tens of hours. To develop effective strategies for mitigating their climate impact, it is essential to investigate the processes that underlie their formation and evolution.The formation and evolution of contrails are influenced by various factors, including the aircraft generating them (Unterstrasser et al., 2014). A recent study by Saulgeot et al. (2023) demonstrated that engine position affects the radiative properties of induced contrails. However, this analysis was based on a 2D assumption and initiated calculations at the onset of the vortex phase. Building on and extending this work, we present a 3D numerical study of contrail evolution during the vortex phase for different engine positions. Large-Eddy Simulations (LES) are initialized using Reynolds-Averaged Navier-Stokes (RANS) simulations conducted in the near-field of a realistic aircraft geometry, representative of a Boeing 777.Three distinct engine positions are analyzed: one at 34% of the wingspan (typical of B-777 or A-320), another at 60% (outboard engine of a B-747), and a more academic configuration at 80%. The latter position aligns the propulsive jet with the wingtip vortex position, as predicted by elliptical wing loading theory, and represent the optimal configuration in the 2D study. Initialization involves extruding a slice of the RANS domain, obtained from prior simulations, onto the LES domain over a length corresponding to the wavelength of Crow instabilities, using the methodology developed by Bouhafid et al. (2024). This approach allows for the simulation of both contrail formation and its subsequent evolution over longer timescales. Microphysical processes, including soot-induced condensation, are modeled using an Eulerian approach (Khou et al., 2015). The simulations will extend up to 5 minutes after the effluent is ejected from the engine.Simulation results reveal distinct aerodynamic behaviors, particularly in the lifetime of vortex dipoles, which are influenced by variations in jet proximity to wingtip vortices. These differences affect the resulting plumes, influencing both their spatial dispersion and the microphysical properties within them. As a result, the three configurations show variations in ice crystal radii and survival rates. These differences, in turn, impact the optical properties of the contrails, particularly their optical thickness.
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 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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".