Demonstration of a Conceptual Design Tool for Multiple Lifting Elements
Bibliographic record
Abstract
The design of high lift devices during the conceptual design phase of transport aircraft requires highly iterative methods in order to develop an efficient product. A conceptual design tool has been developed to support the analysis of these multiple lifting elements. The method employed is based on a modified higher order potential flow method that uses elements of distributed vorticity and a fixed or relaxed wake model. Although small differences exist between the predictions of both wake models, both compute lift and induced drag values which compare well with the NASA Trap wing data experiment, with the fixed wake model being computationally faster. Section pressure distributions show that the computed difference between the upper and lower pressure coefficients shows good agreement with the experimental data at 65% halfspan, but underpredicts the pressure difference closer to the wingtip. Results of a trade study on the relative placement of a trailing edge flap tend to agree with the expected trends. The tool is computationally efficient; a single angle of attack analysis can be completed in minutes on a personal computer. To further reduce the time needed for an analysis, a fixed wake analysis can be completed in, on average, 20% less time than a relaxed wake analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".