Heat Transfer in the Core Compressor Under Ice Crystal Icing Conditions
Bibliographic record
Abstract
It has been recognised in recent years that high altitude atmospheric ice crystals pose a threat to aircraft engines. Instances of damage, surge and shutdown have been recorded at altitudes significantly greater than those associated with supercooled water icing. It is believed that solid ice particles can accrete inside the core compressor, although the exact mechanism by which this occurs remains poorly understood. Development of analytical and empirical models of the ice crystal icing phenomenon is necessary for both future engine design and this-generation engine certification. A comprehensive model will require the integration of a number of aerodynamic, thermodynamic and mechanical components. This paper studies one such component, specifically the thermodynamic and mechanical processes experienced by ice particles impinging on a warm surface. Results are presented from an experimental campaign using a heated and instrumented flat plate. The plate was installed in the Altitude Icing Wind Tunnel (AIWT) at the National Research Council of Canada (NRC). This facility is capable of replicating ice crystal conditions at altitudes up to 9 km and Mach numbers up to 0.55 [1]. The heated plate is designed to measure the heat flux from a surface at temperatures representative of the early core compressor, under varying convective and icing heat loads. Heat transfer enhancement was observed to rise approximately linearly with both total water content and particle diameter over the ranges tested. A Stokes number greater than unity proved to be a useful parameter in determining whether heat transfer enhancement would occur. A particle energy parameter was used to estimate the likelihood of fragmentation. Results showed that when particles were both ballistic and likely to fragment, heat transfer enhancement was independent of both Mach and Reynolds numbers over the ranges tested.
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".