Theoretical Solutions for Finite-Span Wings of Arbitrary Shapes Using Velocity Singularities
Bibliographic record
Abstract
This paper presents a new method of solution for the e nite-span wings of arbitrary shapes, which avoids the dife culties of the previous methods. This method uses velocity singularities in the Trefftz plane to derive the contributions in the solution of the circulation distribution caused by the changes in the spanwise variation of the wing chord and incidence. The new functions derived for these contributions contain both natural and forced symmetry and antisymmetry terms (which are absent in the previous methods ) and thus represent a correct mathematical modeling of the physical problemsthat lead to highly accurate theoretical solutions. The method has beenvalidatedbycomparisonwiththesolutionsobtainedbyRasmussenandSmithandCarafoliforrectangularand tapered wings of uniform incidence, and with the panel method results by Katzand Plotkin. Accurateand efe cient theoretical solutions of aeronautical interest are then obtained for wings with asymmetric incidence distributions caused by symmetric and antisymmetric dee ections of e aps and ailerons and for wings with curved leading and trailing edges and variable incidence, which are dife cult to model in current panel methods.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".