Scaling Methodology of the FAA Burner for Pre-Qualification Fire Tests of Aircraft Engine Panels
Bibliographic record
Abstract
Abstract The main objective of this work is to design a small kerosene burner to study the fireproofing capacity of aircraft composite materials exposed to an open flame. The standards AC20-135 and ISO-2685 describe how the fireproofing tests have to be performed and serve as guidelines to set the requirements for the design of a small kerosene burner as a less costly alternative to the larger FAA burner. The burner is fed with liquid jet-A fuel and air, which is flowing around the injector in a cylindrical chamber. The combustion generates an unconfined flame. The fuel injector selected is a Delavan spill-return pressure atomizer. There is a custom 3D printed plastic axial swirler at the inlet of the combustion area to promote better mixing between air and jet-A droplets. A computational fluid dynamic analysis (CFD) is presented to better understand the aerodynamic of the burner and to design adequately the swirler. The design of the burner allows changing easily the swirler to test swirlers with different vane angles. An experimental test bench is designed to test the effect of these swirlers on the heat flux measurements under multiple combinations of burner power and equivalence ratio at four axial locations. The experimental investigation allows selecting the final configuration and parameters for the burner. The chosen swirler has 15 vanes that are oriented at the exit at 25° to the burner axis. The best axial location for the measurements from the burner face to the position of the calorimeter is at 7.6 cm (3 in.). It is possible to generate a flame with a diameter smaller than 6.4 cm (2.5 in.) while reaching the required heat flux of 116 kW/m2. This accommodates smaller coupon sizes for the composite material and reduces cost for pre-certification FAA testing. To achieve this flame configuration, the burner power should be set between 10 kW and 20 kW with an equivalence ratio from 0.7 to 0.9.
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 | 0.001 | 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".