A scattering-chamber approach for solving finite rough surface scattering problems
Bibliographic record
Abstract
In this paper a new method is derived for the computation of scattering from a finite, rough free surface. The free surface is infinite in extent but only a portion of it is rough. In order to reduce the amount of numerical computation for such a problem, it is desirable to restrict the computations to the interval of roughness, even for remote sources and receivers. This can be easily done in the case that the rough portion of the surface is only directed into the surrounding fluid medium. In this case, the use of the appropriate half-space Green’s function will restrict the integral equation to the interval of roughness only. However, for general deformations this Green’s function cannot be used. The use of truncated integral equations utilizing the free space Green’s function is discussed. An alternate approach is then described. A system of boundary conditions is derived for a finite curve containing the interval of roughness and a surrounding contour in the fluid half-space. The resulting equations are solved using the method of wave-field superposition. The derived method is also easily generalized to the case that the rough surface under consideration is the upper boundary of a waveguide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".