Bibliographic record
Abstract
Abstract A new hybrid finite‐volume time‐domain integral equation (FVTD/IE) algorithm for the solution of Maxwell's Equations on unstructured meshes of arbitrary flat‐faceted volume elements is presented. A time‐domain IE‐based numerical algorithm is applied on the boundary of the computational domain to determine the incoming fluxes for the boundary facets of the mesh. This method is a global grid‐truncation technique similar to the method previously introduced for the finite‐difference time‐domain scheme by Ziolkowski et al. The three main advantages of this IE truncation method are that (1) it allows geometrical objects to be located (almost) arbitrarily close to the mesh boundaries without compromising the physics of the problem, (2) it couples the physics of unconnected meshes so that distant scatterers can be surrounded by their own local mesh, thus reducing total mesh size, and (3) the same IE formulation can be used to compute electromagnetic field values at points outside the mesh. Currently, the main disadvantage is that an acceleration scheme for performing the IE update, which requires integrating field components on an interior surface at a retarded time, is not available. Computational results are presented for the scattering from a perfectly electrical conducting sphere and compared numerically with the analytic time‐domain solution as well as the solution obtained using a large spherical outer mesh boundary with local absorbing boundary conditions. Results are excellent and show almost no reflections from the mesh boundary even when the observation point is located close to the corner of the cubically shaped outside mesh boundary. Results are also presented and validated for the scattering from two objects that are contained inside their own unconnected meshes. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".