Numerical simulation of a hot-air anti-icing system
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Bibliographic record
Abstract
The paper presents results of the numerical simulation of a hot-air anti-icing system model. A 20 Navier-Stokes CFD code is used to simulate jet impingement on (a) a flat plate and (b) th e inner surface a slat of a multi-element airfoil, a modified RAE 2822 airfoil. The j?at plate case is used to validate numerical predictions by comparison with known empirical conelations. Since these correlations are being used in most of the anti-icing simulation codes, the slat case is used to determine their applicability to concave surfaces. The results indicate that the empirical correlations are not n&able enough for use in anti-icing simulations. The CFD code is then coupled to an ice accretion and antiicing simulation code, CANICE. The overall computational prvcedum is presented with the help of an example. The merits of using the CFD tool in conjunction with the CANICE code are discussed. NOMENCLATURE c, = specific heat of air = airfoil chord length ii slot-tc+wall distance/height h = heat-transfer coefficient k = thermal conductivity L W C = liquid water content M = freestream Mach number MVD = median volumetric droplet diameter ti ?z mass flow rate NZ6 = Nusselt number, hs/kf Pr = Prandtl number, pk/Cp ke = heat flux = freestream Reynolds number, V,c/v Res = jet Reynolds number, isS/~ S = hydraulic diameter of slot, 2x width St = Stanton number, h/pre,VrerCP FL = surface arc length measured from origin = temperature Tf = film temperature, (Tw + Tin)/2 V = airspeed, velocity Q = angle of attack relative to chord line P = fluid viscosity v = kinematic viscosity, p/p P = fluid density i.2 = mean velocity at the inlet slot * Postdoctoral Fellow. Member AIAA. t Ph. D. Student Member AIAA. 4 Bombardier Aeronautical Chair Professor. Associate Fellow AIAA. Copyright @ 2000 by Farooq Saeed, FranGois Morency, and Ion Paraschivoiu. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. Subscripts: anti = anti-icing f = fluid, film in = inlet out = outlet ref = reference s = static t = total w = wall X = local 00 = freestream value INTRODUCTION Atmospheric icing presents a major hazard to aircraft operat ing under natural icing condit ions and is a cause of major concerns for the certification authorities as well as the aircraft manufacturers. The steady rise in the global aviation traffic means an increased likelihood of encounter ing natural icing conditions. This suggest an increased frequency of icing related accidents unless a considerable amount of effort is focused on the various safety issues concerning in-flight aircraft icing. To enhance flight safety under natural icing conditions, FAA has recently initiated a multi-year icing plan’>’ to address the various issues related to in-flight aircraft icing. One of the several key tasks outl ined in the plan is to ensure the validity and reliability of icing simulation/modeling methods currently being used/developed. In an effort to support the objectives of the FAA Icing Plan, and facilitate Bombardier Aerospace in the certification process, the main focus of research under the Bombardier Aeronautical Chair at l?cole Polytechnique, MontrCal, has been the development of a reliable ice accretion and anti-icing simulation code CANICE.3-5 The development of CANICE has
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it