A Stable SBP–SAT FDTD Subgridding Method for T-Junction Blocks
Bibliographic record
Abstract
A stable summation-by-parts simultaneous approximation term (SBP–SAT) finite-difference time-domain (FDTD) subgridding method for electromagnetic simulations is proposed, specifically addressing computational challenges in T-junction block configurations. By integrating SBP operators and SATs into the FDTD framework, a three-block computational scheme is developed, which can be extended to a five-block configuration for regions centered within rectangular subgridding blocks. Our method employs specially designed interpolation matrices that maintain stability and accuracy across diverse grid ratios at interfaces of T-junction blocks. Numerical results validate its high efficiency, accuracy, and flexibility. Compared with traditional SBP–SAT FDTD subgridding methods for aligned blocks, our approach significantly reduces redundant SAT boundary conditions, enhancing the accuracy near boundary regions. These advantages are particularly pronounced in high dimensional and multisubgridding scenarios, establishing the proposed approach as both computationally efficient and straightforward to implement in complex applications.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".