Generalized h-p Triangles and Tetrahedra for Adaptive Finite Element Analysis in Parallel Processing Environments
Bibliographic record
Abstract
New families of triangle and tetrahedron elements are proposed for h-p adaptive finite element analysis (AFEA) in parallel processing computational environments. The elements are constructed based on very-high-order arbitrarily piecewise-continuous polynomial bases, which span the full range of local mesh refinements, and a very broad variety of the primary local distributions of degrees of freedom (DOF), that are provided by conventional and irregular h-p adaptive refinements. Irregular-cut continuity constraints are used to maintain the conformity and modeling integrity of the new h-p elements on the external edges (faces) of the triangles (tetrahedra), to permit the seamless introduction and use of the elements within conventional AFEA formulations. The potential benefits, and related costs, of these new elements are investigated for electromagnetics applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".